From 2589f7cdcf96fde451b1048bf628eca19ac733fe Mon Sep 17 00:00:00 2001 From: Ashley Nicolson Date: Tue, 5 May 2026 10:48:42 +0100 Subject: [PATCH 01/17] Add AITK maintainer spotlight --- content/academia/aitk-maintainer-spotlight.md | 95 +++++++++++++++++++ 1 file changed, 95 insertions(+) create mode 100644 content/academia/aitk-maintainer-spotlight.md diff --git a/content/academia/aitk-maintainer-spotlight.md b/content/academia/aitk-maintainer-spotlight.md new file mode 100644 index 00000000..1dbd3b85 --- /dev/null +++ b/content/academia/aitk-maintainer-spotlight.md @@ -0,0 +1,95 @@ +--- +name: Lisa Meeden +institution: Swarthmore College +department: Computer Science +projectName: Artificial Intelligence Toolkit (AITK) +projectRepo: https://github.com/ArtificialIntelligenceToolkit/aitk +maintainerProfiles: + - github: https://github.com/lmeeden1 +badges: ["Academic Maintainer", "Professor"] +description: "An open-source toolkit combining Python libraries and Jupyter notebooks to help diverse audiences explore AI systems, visualise their outputs, and understand their ethical implications." +--- + +## What is Artificial Intelligence Toolkit (AITK), and what does it help people do? + +Artificial Intelligence Toolkit (AITK) is an open-source project that combines Python libraries and computational essays (Jupyter notebooks). It is designed to allow a diverse audience, including those with little or no background in AI, to interact with a variety of AI tools. + +Users can explore how these systems function in more depth, visualise their outputs, and develop a better understanding of their ethical implications. + +## What inspired you to start this project? + +The co-authors of this toolkit have spent over 30 years teaching AI at small liberal arts colleges and wanted better pedagogical tools to give students a concrete, hands-on experience. + +The toolkit focuses on helping users visualise the inner workings of these systems, opening up the "black box." For example, when building a neural network, users can display its structure and visualise activations across all layers based on chosen input values. + +## How does this project connect to your academic work? + +Starting in 2021, the National Humanities Center brought together faculty from fifteen institutions as part of the "Responsible Artificial Intelligence Curriculum Design Project." + +Over two years, the cohort developed new humanities courses, which were first offered during the 2023–24 academic year. Notebooks from AITK were piloted in courses at Bowdoin College, Davidson College, Duke University, Swarthmore College, and University of Utah. + +AITK has also been used regularly in AI courses at Swarthmore College for the past four years. + +## Who contributes to the project? + +The initial release was developed by three faculty members: + +- Douglas Blank, previously a Computer Science professor at Bryn Mawr College, now Head of Research at Comet ML +- James Marshall, a Computer Science professor at Sarah Lawrence College +- Lisa Meeden, a Computer Science professor at Swarthmore College + +In the summer of 2024, three undergraduate students at Swarthmore College made significant additions: + +- Levin Ho +- Morgan McErlean +- Zehua You + +## How are students involved in the project? + +Students contributed a number of new Jupyter notebooks, conducted a UX study, and were co-authors on a paper describing AITK. + +## How is the project used in teaching or coursework? + +The notebooks in AITK are used as lab work in Responsible AI courses, while the Python libraries are used in AI courses at Swarthmore College for more advanced lab work. These notebooks have also been used in a number of workshops for faculty and staff at a variety of institutions to help them learn about AI. + +## What impact has this project had on your students? + +In course evaluations, students frequently mention AITK labs as their favourite and most engaging part of the course. Some students have used AITK to complete independent projects. + +## What impact has the project had beyond the classroom or research? + +The project contributed to a paper entitled "AI Toolkit: Libraries and Essays for Exploring the Technology and Ethics of AI", which was published at the Educational Advances in AI conference in March 2025. + +## What does it take to maintain the project? + +Most upgrades are carried out over the summer, after which the toolkit remains stable during the academic year. + +Because the number of contributors is still relatively small, the team stays in frequent communication about upcoming plans. + +## What have been the biggest challenges in maintaining the project? + +Maintaining a consistent look and feel across all of the Jupyter notebooks included in the toolkit. + +## How do you ensure the project remains sustainable over time? + +Because we continually use the toolkit in our courses, we have a strong, ongoing incentive to maintain it. + +## How do you engage with your community? + +During the National Humanities Center project, the team met regularly (about once a month) to share how resources were being used and to address any issues. + +Since the grant period ended, we generally hear from users via email or at conferences. + +## Have you taken part in any open source programs or events? + +No. + +## What would you love to achieve by showcasing your project? + +AI's impact on society is at an all-time high. The One Hundred Year Study on AI notes that the field has reached an inflection point, where it is urgent to think seriously about the risks and downsides alongside the benefits. + +We believe AITK can help inform the public about both the opportunities and challenges of AI in a clear and practical way. + +## Is there anything else you'd like to share? + +This is my first serious open-source endeavour, and it has been exciting to share our work in this way. From b4e932515aa9249b06f67b75be99324c1e72be2d Mon Sep 17 00:00:00 2001 From: Ashley Nicolson Date: Tue, 5 May 2026 11:00:24 +0100 Subject: [PATCH 02/17] Add maintainer spotlight for Flavio Lozano-Isla This file introduces Flavio Lozano-Isla and his project 'inti', detailing its purpose, impact on students, and integration of AI in teaching and project maintenance. --- content/academia/inti-maintainer-spotlight.md | 132 ++++++++++++++++++ 1 file changed, 132 insertions(+) create mode 100644 content/academia/inti-maintainer-spotlight.md diff --git a/content/academia/inti-maintainer-spotlight.md b/content/academia/inti-maintainer-spotlight.md new file mode 100644 index 00000000..71f0f611 --- /dev/null +++ b/content/academia/inti-maintainer-spotlight.md @@ -0,0 +1,132 @@ +--- +name: Flavio Lozano-Isla +institution: Universidad Nacional Toribio Rodriguez de Mendoza +department: Agronomy Faculty +projectName: "inti: Tools and Statistical Procedures in Plant Science" +projectRepo: https://github.com/Flavjack/inti +projectWebsite: https://inkaverse.com/ +maintainerProfiles: + - github: https://github.com/Flavjack + - orcid: https://orcid.org/0000-0002-0714-669X + - linkedin: https://www.linkedin.com/in/flozanoisla/ +badges: ["Academic Maintainer", "Assistant Professor"] +description: "An R package providing tools and statistical procedures for plant science and experimental design, supporting researchers from experimental planning through data analysis and technical writing." +--- + +## What is inti: Tools and Statistical Procedures in Plant Science, and what does it help people do? + +The inti package is part of the inkaverse project, which was developed for support with tools and statistical procedures for plant science and experimental design. Its main goal is to support researchers throughout the full workflow, from experimental planning and data collection with `tarpuy()`, to data analysis and visualisation with `yupana()`, and technical writing. The project aims to make scientific analysis more accessible, reproducible, and efficient for students, researchers, and professionals. + +## What inspired you to start this project? + +During my PhD, I spent a significant amount of time analysing and organising data from field experiments. This experience inspired me to create a project that supports young scientists in learning statistics and plant science. I wanted to shorten their learning curve by providing an interactive approach that introduces them to the R programming language and helps them transition into data analysis and scientific programming. + +## How does this project connect to your academic work? + +This project aligns with my academic work in teaching, capacity development, and research in plant sciences. As a university professor and researcher, I develop and teach courses related to plant breeding, crop physiology, and data analysis. My teaching emphasises interactive and applied learning to equip students with the skills needed to conduct rigorous scientific research. + +## Who contributes to the project? + +I initially developed the project in collaboration with a colleague from my first professional experience and a university friend. The early phase combined practical field experience with academic insights. + +Currently, the project is maintained and further developed by me alongside a group of students. As an open-source initiative, it also benefits from contributions, feedback, and recommendations from the scientific community. + +## How are students involved in the project? + +Students are primarily involved through testing, identifying bugs, and providing feedback. After receiving training in data analysis and programming, they also contribute to coding and implementing new pipelines. This hands-on experience strengthens their skills while supporting the project's continuous development. + +## How is the project used in teaching or coursework? + +The project is integrated into the Programming and Data Analysis course within the Faculty of Engineering and Agricultural Sciences (FICA) at the Universidad Nacional Toribio Rodríguez de Mendoza. Students use the software for hands-on coding, data analysis, and implementing pipelines, including analysing data for their research and thesis projects. + +## What impact has this project had on your students? + +Participating in this project has significantly improved my students' data analysis and decision-making skills. Many students now apply these skills in roles within private companies. + +The project has also supported their academic progress by reducing the time required to prepare theses, dissertations, and scientific publications, equipping them with practical tools for both academic and professional success. + +## What impact has the project had beyond the classroom or research? + +The project has had a notable real-world impact by improving the analytical skills and employability of students and their future careers. Many participants have transitioned into private-sector roles where they apply what they have learned. + +Beyond academia, the project has fostered a community of practice, encouraging continuous learning and innovation in agricultural data analysis and supporting evidence-based decision-making in real-world contexts. + +## What does it take to maintain the project? + +The project is currently maintained as part of my academic and research activities, alongside contributions from students and the community. It is also supported by GitHub Sponsors and training services provided to private companies. These resources help sustain its development and respond to the evolving needs of the agricultural data analysis community. + +## What have been the biggest challenges in maintaining the project, especially in an academic setting? + +One of the biggest challenges is balancing the project development with teaching responsibilities, research commitments, and student supervision. However, this limitation has been partially mitigated through the active involvement of students, who contribute to the maintenance, continuous development, updating, and refinement of the software, thereby fostering a collaborative and sustainable development framework within the academic context. + +## How do you ensure the project remains sustainable over time? + +To ensure sustainability, the project has been integrated into coursework, where students contribute through coding and testing. Additional support comes from research grants, GitHub Sponsors, and training services. The open-source model also encourages ongoing community contributions. + +## How do you engage with your community? + +We create and share free educational content, including videos and training sessions, to support the community in learning data analysis techniques. + +The software is available as an R package on CRAN, ensuring easy access for users worldwide. We also published all the software under open-source license, encouraging adoption, feedback, and contributions of the community. + +## Have you taken part in any open source programs or events? + +Not yet, but we are interested in participating in open-source programs and events in the future. + +## What would you love to achieve by showcasing your project? + +I would love to highlight the project's impact on capacity development in agricultural data analysis and programming. Showcasing it would increase visibility, attract collaborators, and encourage contributions from scientific, academic, and industry communities. It would also promote accessible tools that simplify research and support scientific innovation. + +## Do you use AI tools in your day to day work on this project? If so, how? + +Artificial intelligence tools are systematically integrated into the daily workflow to enhance, refine, and accelerate both the development and deployment of the software components associated with this educational project. Their application spans code optimisation, debugging, documentation generation, and the automation of repetitive tasks, thereby increasing overall efficiency and reducing development time. + +Furthermore, many contemporary programming environments and platforms incorporate built-in AI functionalities within their interfaces. This facilitates more intuitive coding processes, improves usability, and streamlines implementation across different stages of the software lifecycle. + +## Do you implement AI into your classroom or coursework? If so, what does that look like in practice? + +Yes, artificial intelligence is actively integrated into both classroom instruction and coursework as a complementary tool to support learning processes. In practice, AI-based tools are used to assist students in understanding programming concepts, identifying and correcting coding errors, and exploring alternative solutions in real time. + +This approach creates a more interactive and adaptive learning environment, where students can receive immediate feedback and guidance. The incorporation of AI significantly accelerates the acquisition of programming skills by reducing the learning curve associated with complex concepts and debugging processes. As a result, students can stay engaged and motivated, minimising frustration often experienced in the early stages of programming, and supporting a more efficient and sustained learning experience. + +## Has AI changed how you maintain or manage your project? + +The integration of artificial intelligence has significantly transformed how the project is maintained and managed. AI-assisted programming tools have streamlined development workflows and enabled more efficient maintenance processes, facilitating continuous improvement of the software. + +These tools support automated error detection, code optimisation, and refactoring, which improves overall code quality and robustness. + +## Have you experimented with AI driven or automated workflows in your project? What has that looked like? + +Yes, AI workflows are integrated to support code generation and automate documentation, particularly for R functions. This accelerates development, improves code quality, and enhances reproducibility and collaboration within the project. + +## How do you see your contributors using AI when working on your project? + +Contributors primarily use artificial intelligence as a support tool for programming tasks, especially for debugging and error detection. In practice, AI helps them identify issues more efficiently, suggest improvements, and explore alternative coding solutions. + +At the same time, this interaction supports the progressive development of their programming skills by providing immediate feedback and reinforcing learning through guided problem-solving. + +## What concerns or challenges, if any, do you have about the use of AI in your project or field? + +Although artificial intelligence represents a significant advancement in supporting programming tasks, one of the main challenges is its dependency on prior user expertise. In practice, the effective use of AI-generated code still requires a solid understanding of programming fundamentals, as outputs are not always error-free and often need critical evaluation and correction. + +Without sufficient technical knowledge, there is a risk of misinterpreting suggestions or propagating errors. This highlights the continued importance of foundational skills for the reliable and responsible use of AI in the project. + +## How has your approach to maintaining this project evolved over time? + +The approach to maintaining the project has gradually evolved toward a more collaborative and community-driven model. Initially centred on individual development, it has shifted to actively engaging students in the continuous improvement of the package through feedback, support, and practical contributions. + +In addition, the open-access nature of the project has enabled external users to contribute by refining the codebase, proposing enhancements, and identifying issues. + +## How do you see AI shaping the future of your project or field? + +Artificial intelligence is expected to play a transformative role in shaping the future of the project by enhancing both the development process and user interaction. In software engineering, AI tools will continue to improve code generation, optimisation, and validation, increasing both efficiency and code quality. + +At the same time, AI is likely to be progressively integrated into the software itself, enabling more dynamic and intelligent user interactions through adaptive interfaces and automated assistance. + +## Is there anything else you'd like to share about your project or open source journey? + +As an agronomist, I began my journey without a background in programming. Over time, I recognised the importance of programming and open-source software in research, which shaped my focus on accessible learning for students from non-programming backgrounds. + +I now prioritise teaching basic programming skills in agricultural sciences to expand career opportunities and support data-driven research. + +In addition, I maintain other educational R packages such as GerminaR and huito, which support plant science data analysis and promote accessible, reproducible research practices. From cb8bdfcdb1571043d82eab02941f6c25248491c5 Mon Sep 17 00:00:00 2001 From: Ashley Nicolson Date: Tue, 5 May 2026 11:09:54 +0100 Subject: [PATCH 03/17] Create maintainer spotlight for Spoon project Added spotlight article for Martin Monperrus and the Spoon project, detailing its purpose, academic connections, and community engagement. --- .../academia/spoon-maintainer-spotlight.md | 73 +++++++++++++++++++ 1 file changed, 73 insertions(+) create mode 100644 content/academia/spoon-maintainer-spotlight.md diff --git a/content/academia/spoon-maintainer-spotlight.md b/content/academia/spoon-maintainer-spotlight.md new file mode 100644 index 00000000..00c9dae5 --- /dev/null +++ b/content/academia/spoon-maintainer-spotlight.md @@ -0,0 +1,73 @@ +--- +name: Martin Monperrus +institution: KTH Royal Institute of Technology +department: EECS/TCS +projectName: Spoon +projectRepo: https://github.com/INRIA/spoon/ +projectWebsite: https://spoon.gforge.inria.fr/ +maintainerProfiles: + - github: https://github.com/monperrus + - orcid: https://orcid.org/0000-0003-3505-3383 +badges: ["Academic Maintainer", "Professor"] +description: "An open-source library to analyse, rewrite, transform, and transpile Java source code, providing a well-designed AST and a powerful API for analysis and transformation." +--- + +## What is Spoon, and what does it help people do? + +Spoon is an open-source library to analyse, rewrite, transform, and transpile Java source code. It parses source files to build a well-designed abstract syntax tree (AST) and provides a powerful API for analysis and transformation. It is widely used in both research labs and industry. + +## What inspired you to start this project? + +At the time of its creation, there was no tool available for analysing and transforming Java source code. + +## How does this project connect to your academic work? + +It serves as core infrastructure for about half of our academic papers. + +## Who contributes to the project? + +Faculty, students (PhD, Masters, undergraduate), and external contributors. + +## How are students involved in the project? + +Students contribute by developing new features, fixing bugs, and reviewing code. + +## How is the project used in teaching or coursework? + +It is used in lab exercises in many courses around the world. + +## What impact has this project had on your students? + +Students develop advanced Java skills, gain a deeper understanding of open source, and improve their communication abilities in collaborative environments. + +## What impact has the project had beyond the classroom or research? + +It is used in industry, with an estimated adoption across more than 100 companies. + +## What does it take to maintain the project? + +Maintenance involves pull requests, code review, heavy continuous integration, weekly beta releases, and a couple of releases each year. + +## What have been the biggest challenges in maintaining the project, especially in an academic setting? + +Finding new long-term contributors. + +## How do you ensure the project remains sustainable over time? + +By allocating a fraction of research grants to support this core infrastructure project. + +## How do you engage with your community? + +Through extensive use of GitHub issues and pull request comments. + +## Have you taken part in any open source programs or events? + +Yes, Google Summer of Code. + +## What would you love to achieve by showcasing your project? + +To attract new contributors and increase visibility. + +## Is there anything else you'd like to share about your project or open source journey? + +Thanks for the GitHub platform, it's great. From 995feddc15de102ec498b3122be42abcdbc93600 Mon Sep 17 00:00:00 2001 From: Ashley Nicolson Date: Tue, 5 May 2026 11:19:45 +0100 Subject: [PATCH 04/17] Create maintainer spotlight for PersonalAnalytics project Added a detailed maintainer spotlight for the PersonalAnalytics project, including its purpose, history, community involvement, and future directions. --- ...personal-analytics-maintainer-spotlight.md | 144 ++++++++++++++++++ 1 file changed, 144 insertions(+) create mode 100644 content/academia/personal-analytics-maintainer-spotlight.md diff --git a/content/academia/personal-analytics-maintainer-spotlight.md b/content/academia/personal-analytics-maintainer-spotlight.md new file mode 100644 index 00000000..2a07c214 --- /dev/null +++ b/content/academia/personal-analytics-maintainer-spotlight.md @@ -0,0 +1,144 @@ +--- +name: Andre Meyer +institution: University of Zurich +department: Department of Informatics +projectName: PersonalAnalytics +projectRepo: https://github.com/HASEL-UZH/PersonalAnalytics +projectWebsite: https://hasel.dev/PersonalAnalytics +maintainerProfiles: + - github: https://github.com/casaout + - github: https://github.com/HASEL-UZH/ + - orcid: https://orcid.org/0000-0002-5532-1181 +badges: ["Academic Maintainer", "Senior Researcher"] +description: "An open-source, privacy-focused self-monitoring tool for knowledge workers and researchers that runs locally, collecting computer interaction data without sending anything to the cloud." +--- + +## What is PersonalAnalytics, and what does it help people do? + +PersonalAnalytics is an open-source, privacy-focused self-monitoring tool for knowledge workers and researchers. It runs locally on Windows and macOS, collecting computer interaction data – such as active applications, window titles, and self-reported mood and productivity – without sending anything to the cloud. + +Researchers use it as a ready-made foundation for field studies: rather than building data collection infrastructure from scratch, they can fork the project, add their own trackers or interventions, and run studies with real participants. Individuals can also use it simply to reflect on their own work habits. + +The project started as a tool for studying software developers, but has since expanded to knowledge workers more broadly – and is now evolving into a full research platform enabling privacy-conscious data donation and cross-study collaboration. + +## What inspired this project? + +We originally wanted to help software developers to better understand their own work habits, time spent at work, and how that relates to productivity. To achieve this, we aimed to develop a personalised and privacy-sensitive tool to capture and visualise different types of computer interaction data. + +Inspired by tools like Fitbit, which promote physical activity, we wanted to provide actionable insights through retrospection. The project attracted interest from Microsoft Research, leading to me being invited to internships and research collaborations that continue up until today. + +Over time, we realised that the data collection and visualisation capabilities could benefit a broader audience, including researchers and even the general public. In summer 2024, we began evolving the project from a software that we use for our own studies to an infrastructure that is accessible to other researchers and practitioners (aka D2USP). Since then, we have onboarded several studies and are continuing to expand into new use cases. + +These include extending retrospection features, integrating new data sources such as Calendars and biometric data (e.g. sleep quality, exercise activity), and making insights more personalised through locally running language models. + +## How does this project connect to your academic work? + +The project has been developed and maintained for over 10 years and originally started as my master's thesis. In 2024, we began a complete rewrite, to make it more easily maintainable and extensible for Windows and macOS, update the UI, improve update mechanisms as well as refining how study participants can donate data when participating in studies. + +Overall, PersonalAnalytics was used with more than a thousand study participants leading to more than a dozen peer-reviewed scientific publications. In addition, it has been used by dozens of student projects for their bachelor or master theses. + +## Who contributes to the project? + +Besides me as the main, long-term contributor to the project, we occasionally are able to hire research developers who make substantial contributions. In addition, students and other external contributors occasionally provide bugfixes, updates or adaptions/refinements to the tool. + +## How are students involved in the project? + +Many computer science or data science students we supervise want to build tools that improve some aspect of knowledge workers' lives – productivity, focus, sleep, context switching. PersonalAnalytics gives them a ready-made foundation: they fork it, add their intervention, run a validation study with real participants, and often contribute improvements back via PRs. + +## How is the project used in teaching or coursework? + +Besides student theses, we also feature PersonalAnalytics in our Human Aspects of Software Engineering course, where students learn how to study developers' work lives through qualitative and quantitative data collection. + +## What impact has this project had on your students? + +Students hone their coding and data analysis skills, and gain experience with Git workflows, CI/CD, and developing open source software. + +## What impact has the project had beyond the classroom or research? + +The project has contributed to more than a dozen peer-reviewed publications at top-tier conferences and journals, along with many student reports. + +It has been used in field studies involving approximately 1,500 developers and knowledge workers worldwide, and is also used in a university spin-off, Flowlabs. FlowLabs aims to foster flow and focused work, such as by visualizing availability for interruptions in the office through a physical traffic-light like lightbulb, the FlowLight. + +## What does it take to maintain the project? + +Maintaining PersonalAnalytics means balancing the needs of very different users: PhD students running short-term studies, external researchers building on the platform, and the occasional individual contributor from the open source community. I serve as the long-term anchor – the person who holds institutional memory across student cohorts and research cycles. + +On the technical side, we've invested in automating various aspects, such as CI/CD via GitHub Actions and data donations, including automated code signing, to keep contribution friction low. + +One unexpected but rewarding part of this work is seeing how the infrastructure gets picked up in ways we didn't anticipate – one of our studies, for example, directly inspired the Good Day Project at GitHub, led by Eirini Kalliamvakou (Research Advisor at GitHub). + +## What have been the biggest challenges in maintaining the project, especially in an academic setting? + +Perhaps the deeper challenge is structural: academic incentives reward publications, not maintenance. Keeping a project alive and well-documented across a decade – through student turnover, shifting funding, and evolving technology – requires a kind of sustained commitment that academia doesn't formally recognize or reward. + +## How do you ensure the project remains sustainable over time? + +In 2025, the project received approximately 150,000 USD in funding from the Digital Society Initiative at the University of Zurich to establish PersonalAnalytics as an official university research infrastructure. In practice, this means we can now hire dedicated research developers rather than depending solely on (PhD) students with limited tenure on the project. It also means we can invest in documentation, onboarding, and the kind of unglamorous maintenance work that keeps a platform reliable for external researchers. + +## How do you engage with your community? + +We actively engage with the community through Github's issues and PRs. At the same time, we maintain an active documentation, including videos and showcases of app uses and studies, as well as offering demos to researchers when helpful. + +## Have you taken part in any open source programs or events? + +Not yet – being featured in Maintainer Month is a first, and we're excited about it. + +## What would you love to achieve by showcasing your project? + +I hope it inspires other researchers and educators to see what's possible when you treat a student project as a long-term investment – from a master's thesis to something that positively influences how knowledge workers think about productivity and wellbeing. + +Beyond that, I'd love to connect with other maintainers facing similar challenges – particularly around sustaining open source projects in academic settings, where funding is uncertain and contributors cycle through on two- or three-year timescales. If this feature helps start that conversation, that's already a win. + +And of course: more contributors, more studies, more researchers building on the platform rather than reinventing the wheel. + +## Do you use AI tools in your day to day work on this project? If so, how? + +Yes, we use AI assistants and agents across most stages of development: brainstorming and mocking new features, refining specifications, coding, testing, bug fixing, and updating documentation. + +That said, we approach it deliberately. The human always remains in the driver's seat — we never push a change that hasn't been reviewed by a person. + +We're also mindful of a subtler risk: over-relying on AI can accumulate cognitive debt. If AI always writes the code, you stop deeply understanding your own codebase. So we try to use it as a thinking partner, not a replacement for understanding. + +## Do you implement AI into your classroom or coursework? If so, what does that look like in practice? + +Yes — preparing students for the realities of modern software engineering means teaching them to use AI responsibly. We encourage using AI tools to improve productivity, particularly in terms of output, while being clear about the risks: increased cognitive load, unlearning, growing dependency, and rising expectations. + +We also try to set realistic expectations around productivity gains. The numbers look impressive for greenfield projects, but in practice — when working on brownfield or legacy codebases like PersonalAnalytics — the gains are much more modest. Integrating AI well into the software development lifecycle is genuinely hard, and something companies are still figuring out as the space evolves. + +## Has AI changed how you maintain or manage your project? + +Yes, noticeably. We spend less time on coding and more on specification and validation — thinking carefully about what we want to build before building it, and rigorously assessing quality afterward. In some ways, AI has shifted the bottleneck rather than removed it. + +We've also become more cautious about releases. We now run apps longer as field previews before pushing updates, partly because AI-generated code can be subtly wrong in ways that aren't immediately obvious. + +## Have you experimented with AI driven or automated workflows in your project? What has that looked like? + +We've experimented in targeted ways: auto-generating PR and commit summaries, and using AI to keep documentation up to date. Nothing fully autonomous — these are human-reviewed steps within an otherwise manual workflow. We're cautious about going further until the quality and reliability justify it. + +## What concerns or challenges, if any, do you have about the use of AI in your project or field? + +Our main concerns centre on what happens when AI becomes the default rather than a deliberate choice. Cognitive debt is real — over-reliance can quietly erode understanding of your own codebase, and that's hard to recover from. + +The concern we see most clearly with students is blind trust. There's a lot of excitement around AI tools, which is understandable, but junior developers in particular can be prone to accepting AI output without question, lacking the experience to spot subtle errors or challenge flawed assumptions. Teaching that skepticism is increasingly important. + +## How has your approach to maintaining this project evolved over time? + +Over time, AI has meaningfully changed the pace of maintenance. We can create and iterate on features more quickly, even rapidly prototyping ideas that would previously have taken much longer to explore. + +The trade-off is that we now invest more in validation, testing, and code review. Speed without rigour creates more problems than it solves. + +Perhaps the most practical change is that it's become easier to keep the project alive alongside other work. Within a few hours a week, I can now achieve what previously would have required much more time, which matters a lot for an academic project without dedicated engineering resources. + +## How do you see AI shaping the future of your project or field? + +AI will shape both what PersonalAnalytics does and the field it studies. Within the tool itself, we're interested in integrating local LLMs to provide personalised, data-driven insights, helping users understand their own patterns in ways that are genuinely useful and privacy-friendly. + +More broadly, AI-assisted coding is here to stay, and that's a good thing. But it comes with responsibility, particularly for educators. We need to teach the next generation of engineers to use these tools thoughtfully, still learning the fundamentals properly while managing reliance and avoiding cognitive debt. + +Finally, as a software engineering community, we need to take expectation management around productivity seriously. Assuming developers will suddenly deliver 50% more output is not only unrealistic today, it risks creating burnout and stress when reality doesn't match the hype. Studying and communicating realistic gains is something our field is well positioned to contribute to. + +## Is there anything else you'd like to share about your project or open source journey? + +Looking back, if there's one thing I'd encourage other academics to do, it's to open-source your research tools. The paper gets cited; the tool gets used, extended, and occasionally inspires work you never anticipated. + +Looking ahead, I'm particularly excited about integrating local LLMs to provide personalized, data-driven insights – helping users make sense of their own patterns without compromising privacy. From 3f11eaee25fad192fb6b3a61f544ad8533613e1b Mon Sep 17 00:00:00 2001 From: Ashley Nicolson Date: Tue, 5 May 2026 11:28:59 +0100 Subject: [PATCH 05/17] Create maintainer spotlight for preCICE team Added a detailed spotlight on the preCICE team, including project description, contributors, and impact on research and education. --- .../academia/precice-maintainer-spotlight.md | 97 +++++++++++++++++++ 1 file changed, 97 insertions(+) create mode 100644 content/academia/precice-maintainer-spotlight.md diff --git a/content/academia/precice-maintainer-spotlight.md b/content/academia/precice-maintainer-spotlight.md new file mode 100644 index 00000000..8243398f --- /dev/null +++ b/content/academia/precice-maintainer-spotlight.md @@ -0,0 +1,97 @@ +--- +name: The preCICE team, introduced by Gerasimos Chourdakis +institution: University of Stuttgart +department: Institute for Parallel and Distributed Systems +projectName: preCICE +projectRepo: https://github.com/precice/precice +projectWebsite: https://precice.org/ +maintainerProfiles: + - github: https://github.com/MakisH + - orcid: https://orcid.org/0000-0002-3977-1385 +badges: ["Academic Maintainer", "Research Associate"] +description: "A coupling library and ecosystem for general partitioned multi-physics and multi-scale simulations, enabling researchers to couple existing simulation codes without reinventing application-specific solutions." +--- + +## What is preCICE, and what does it help people do? + +preCICE is a coupling library and ecosystem for general partitioned multi-physics and multi-scale simulations, including surface and volume coupling. "Partitioned" means that preCICE couples existing programs or solvers capable of simulating a subpart of the complete physics involved in a simulation. + +This approach provides the flexibility needed to maintain a reasonable time-to-solution for complex coupled problems. The software offers convenient methods for transient equation coupling, communication, and data mapping. + +## What inspired you to start this project? + +We are a team of doctoral candidates and researchers who have been developing this project for several years. Our mission is to enable researchers to use their existing simulation codes to solve more complex problems than originally intended, without having to reinvent new simulation codes or application-specific coupling solutions. + +## How does this project connect to your academic work? + +We consider the software itself as the main outcome of our research. We do study and implement computational methods, and we collaborate with domain specialists to test these methods and the software on various applications. + +## Who contributes to the project? + +Mostly doctoral candidates, Master's thesis students, and student assistants, with supervision and review from faculty. As the community grows, we also get more contributions from researchers around the world, and we are trying to make such community contributions easier and enable community participation in more aspects of the project, such as organizing workshops together. + +## How are students involved in the project? + +Students contribute independent code components, small features, test cases, examples, and documentation. + +## How is the project used in teaching or coursework? + +It is often used as a basis for theses and is offered as an option in project-based courses. We also draw examples from it for our Research Software Engineering courses at the University of Stuttgart and at the Technical University of Munich. Using the software is part of a training course delivered at workshops. + +## What impact has this project had on your students? + +Many students make their first FOSS contributions through this project, and some continue contributing afterward. Since the library is used by other codes, students also contribute to third-party codebases. + +## What impact has the project had beyond the classroom or research? + +A few years ago, we could point to more than 100 research groups worldwide that were using preCICE. We collaborate with researchers from universities and research centers in the EU and the US, and adoption in industry is gradually increasing. We can no longer tell who all the users asking questions in our forum or publishing results are, and this feels very fulfilling. + +Today, preCICE is being used, for example, at the AWI Institute of Glaciology in Germany for ice sheet simulations, at NASA Glenn Research Center for simulating hierarchical materials, at Heriot-Watt University in the UK for coupling with deep learning in active flow control, and at Hokkaido University in Japan for simulating parafoils for Martian exploration. + +## What does it take to maintain the project? + +The team consists mostly of seven doctoral candidates across collaborating groups at the University of Stuttgart and the Technical University of Munich. We are multiple maintainers, each overlooking different parts of the project. For example, Frédéric Simonis (@fsimonis) is maintaining the core library repository, while I am making sure that the ecosystem we build around this library works together as a whole. + +Since before COVID-19, the team has been collaborating online on GitHub, communicating via Matrix/Gitter, and holding short weekly video calls. We have in-person team meetings three to four times per year for three days. The core library is released every six months, with additional components released independently. + +Everything is developed openly on GitHub, with an extensive CI pipeline and system tests across repositories. Every ecosystem component lives in its own repository, an approach that comes with a tradeoff: for example, our CI infrastructure often becomes complicated, but students can take ownership of their newly developed component and focus on that without worrying they will break anything. + +## What have been the biggest challenges in maintaining the project? + +Since we are employed at universities, we are required to balance research and teaching responsibilities, which often have continuous deadlines. Finding longer periods of focused time for development can be challenging. + +Another challenge comes from interoperability with third-party software. This requires frequent switching between different codebases, languages, and infrastructure levels. Many components are developed in short-term student projects, so maintaining them after those projects end can be difficult, especially when third-party software introduces breaking changes. + +## How do you ensure the project remains sustainable over time? + +We apply for research funding, typically through the German Research Foundation, and collaborate with research groups interested in improving the software. + +We also attract student projects, organize user workshops, engage new users at conferences, and prioritize documentation and open communication. Many of these activities currently happen alongside or even instead of traditional research outputs. + +## How do you engage with your community? + +We host an active community forum on Discourse, organize yearly week-long workshops, and maintain extensive documentation, contribution guidelines, and a code of conduct. + +We are also working on defining guidelines and best practices for developing and publishing community codes based on FAIR principles, and we discuss these with the community in a structured way. + +## Have you taken part in any open source programs or events? + +We previously did not participate in such programs, considering our project too niche to attract contributors that are not already in the field. However, in 2026, we are participating for the first time in the Google Summer of Code and are excited to mentor motivated contributors on topics that we identified as fitting for beginners. The experience as a new organization in today's coding landscape has been a bit overwhelming so far, but we are identifying strategies and missing infrastructure for welcoming contributions at scale. We are learning a lot through this process. + +## How do you see your contributors using AI when working on your project? + +We do notice new contributors using AI to write code or their pull request descriptions. This has definitely enabled more people to contribute, but has also made it more difficult for us to triage and review contributions. While AI-enabled reviewing tools can be partially helpful, we would need workflows to improve contributions (code and description) before they get on the public tracker. Community contributions are precious, and it is difficult to ask a new contributor to go through several review iterations, especially if now the benefit of this human connection (e.g., learning and sticking to the community) is unclear. Since many other communities have similar issues, I hope we will find solutions together. + +## Do you use AI tools in your day to day work on this project? + +The code we develop is often short but involves looking into academic literature and software documentation, navigating different codebases, and talking to users. AI tools help us, for example, navigate this vast amount of information (especially dense or incomplete software documentation), visualize data, or summarize previous communication. Besides coding, I certainly value the research and writing process, and I so far prefer using AI tools similarly to any other auxiliary tools. + +## What would you love to achieve by showcasing your project? + +So far, the project has mainly been applied within a narrow field, but it is now expanding into new domains. We believe other communities could benefit from using what we have developed rather than building separate solutions. + +As we maintain a growing number of repositories with a relatively small team, we are also looking to attract contributors and maintainers with expertise we may not have. Broader feedback would be especially valuable as we define interoperability standards. + +## Is there anything else you'd like to share? + +This work would not have been possible if we were constantly under pressure to produce traditional academic publications, or without the efforts of collaborating groups to secure long-term funding for maintainers. A big thank you to everyone who helped create this environment. From cb8e38eb34dd32be67e9f0e783a11f8e8eb8e227 Mon Sep 17 00:00:00 2001 From: Ashley Nicolson Date: Tue, 5 May 2026 11:44:33 +0100 Subject: [PATCH 06/17] =?UTF-8?q?Create=20maintainer=20spotlight=20for=20N?= =?UTF-8?q?atalja=20=C4=8Cerkasova?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Added a maintainer spotlight for Natalja Čerkasova, detailing her role, project contributions, and the impact of the SWAT+ model in environmental management. --- .../academia/swatplus-maintainer-spotlight.md | 179 ++++++++++++++++++ 1 file changed, 179 insertions(+) create mode 100644 content/academia/swatplus-maintainer-spotlight.md diff --git a/content/academia/swatplus-maintainer-spotlight.md b/content/academia/swatplus-maintainer-spotlight.md new file mode 100644 index 00000000..ba9d1c48 --- /dev/null +++ b/content/academia/swatplus-maintainer-spotlight.md @@ -0,0 +1,179 @@ +--- +name: Natalja Čerkasova +institution: Texas A&M AgriLife +department: Research +projectName: Soil and Water Assessment Tool Plus (SWAT+) +projectRepo: https://github.com/swat-model/swatplus +projectWebsite: https://swat.tamu.edu/ +maintainerProfiles: + - github: https://github.com/NataljaC + - orcid: https://orcid.org/0000-0003-2894-3935 +badges: ["Academic Maintainer", "Associate Research Scientist"] +description: "An open-source hydrological model that simulates water quality and quantity for watershed management, soil erosion assessment, and non-point source pollution analysis, co-developed by the USDA Agricultural Research Service, Texas A&M AgriLife Research, and Colorado State University." +--- + +## What is SWAT+, and what does it help people do? + +This project focuses on the collaborative development of the Soil and Water Assessment Tool Plus (SWAT+) on GitHub. SWAT+ is an open-source hydrological model that simulates water quality and quantity, co-developed by the USDA Agricultural Research Service, Texas A&M AgriLife Research, Colorado State University, and other contributing institutions worldwide. + +We use GitHub to foster a community-driven process-based model, enabling researchers and developers to contribute through issues, pull requests, and shared documentation. This effort aims to enhance SWAT+'s capabilities for assessing soil erosion, non-point source pollution, and watershed management under changing land use and climate scenarios. + +By leveraging GitHub's platform, we are building a robust, community-maintained tool for global application in environmental modelling and water resource management. + +## What inspired this project? + +SWAT+ builds on over 45 years of continuous development, originating from the original legacy SWAT model. This long history highlights its importance as a key tool for watershed management and environmental modelling. + +With the retirement of several original developers, even though they remain active contributors, we recognised the need to ensure the model's long-term sustainability and continued evolution. Our goal is to transition development to future generations through a community-driven approach. + +By using GitHub, we aim to encourage collaboration and ensure that this tool remains valuable for researchers, practitioners, and policymakers worldwide. + +## How does this project connect to your academic work? + +SWAT+ is the cornerstone of my academic portfolio. As both a power user and a co-developer, I utilize the model across a vast scalar range: from high-resolution studies of small watersheds to complex, global-scale environmental analyses. + +My research creates a continuous feedback loop; while my studies rely on the model's predictive power, the new algorithms and modules I co-develop are integrated back into the core SWAT+ code. + +My academic work both benefits from and contributes to SWAT+'s ongoing development, helping to ensure its continued relevance and improvement. + +## Who contributes to the project? + +Long-standing contributions continue from the USDA Agricultural Research Service, Texas A&M AgriLife Research, and Colorado State University. Important contributions come from Vrije Universiteit Brussel (VUB), Kiel University (Germany), and Klaipeda University (Lithuania). Thousands of active users provide the "front-line" feedback, bug reports, and validation studies that drive the model's iterative improvement. Original developers who continue to provide expertise also remain essential contributors. + +## How are students involved in the project? + +Many users are MSc or PhD students. They contribute through adoption, testing, feedback, co-design, and, in some cases, direct code contributions. + +## How is the project used in teaching or coursework? + +SWAT+ is often part of coursework and, in some cases, a core teaching tool in hydrology and environmental modelling classes. We also deliver workshops — from basic to advanced, to code development — to support learning and adoption. + +## What impact has this project had on your students? + +Students develop strong practical skills in hydrological modelling and environmental analysis, which are directly applicable to real-world problems. + +They also gain experience with open-source collaboration and community-driven development. This exposure improves their job prospects in areas such as water resource management, environmental consulting, and research. + +We have also seen increased engagement and motivation when students contribute to a project with real-world impact. + +## What impact has the project had beyond the classroom or research? + +SWAT+ has had a profound real-world impact, evolving from a research tool into a cornerstone for environmental decision-making. It is utilized globally by researchers and practitioners, supported by a body of more than 6,500 peer-reviewed publications as of May 2026. + +The model's versatility has led to its adoption by major governmental and private entities: + +- **Regulatory agencies:** Used extensively by the USDA Natural Resources Conservation Service and the Environmental Protection Agencies (EPA) in many countries. +- **Private sector:** Environmental consulting firms rely on its outputs for local planning. +- **Corporate sustainability:** Through the Field to Market Alliance, major corporations leverage SWAT+ to calculate critical sustainability metrics, particularly those related to carbon sequestration. + +To further its capabilities, we recently secured NordForsk funding for the RE-FOREST project to enhance the SWAT+ forest growth module for Nordic-Baltic ecosystems. This initiative integrates sustainable forest management with water health modelling to ensure forest resilience in a changing climate. + +Because community adoption is so widespread, SWAT+ serves as a primary vehicle for professional development. Its use in workshops and training programs helps both students and seasoned professionals build the modelling skills necessary to tackle modern environmental challenges. + +We organize at least one international conference annually for the global SWAT community. This year's conference will be held in Thessaloniki, Greece, bringing together developers and users to share the latest innovations in the field. + +## What does it take to maintain the project? + +Maintaining the SWAT+ GitHub repository is a continuous effort that balances core code stability with community-driven innovation. Sustaining the project requires: + +- Rigorous management of the source code to ensure that updates remain backward compatible and scientifically validated. +- Managing pull requests and issues from a global contributor base, ensuring that bug fixes and new features from various research groups are peer-reviewed and integrated correctly. +- Utilizing automated testing pipelines to verify that changes to the model do not disrupt existing hydrological or agricultural simulations across different climate zones. +- Keeping the technical documentation and user manuals updated so that researchers using the tool can implement the latest model versions effectively. +- Ensuring the repository remains an open-access resource, fostering transparency in environmental modelling and allowing projects to share advancements with the wider scientific community. + +We have established initial workflows, though these are still being refined, and we follow flexible release schedules to accommodate the evolving nature of the project. + +## What have been the biggest challenges in maintaining the project? + +Balancing project work with teaching and research responsibilities is a major challenge. + +Securing sustainable funding for long-term maintenance is difficult, as most funding bodies prioritize "novel research" over the critical, unglamorous work of software updates and bug fixes. + +Transitioning from isolated development to a collaborative, GitHub-based ecosystem required a significant cultural and technical shift, requiring synchronized efforts across multiple international institutions. + +We face a chronic shortage of personnel and funds with the niche qualifications required to bridge the gap between complex environmental science and robust code development. + +## How do you ensure the project remains sustainable over time? + +We actively pursue dual-purpose research grants that fund both high-level model application and the underlying engine development. + +By integrating SWAT+ into university coursework and involving student research assistants, we cultivate the next generation of developers. This creates a steady talent funnel of users who transition into contributors. + +We leverage formal partnerships with organizations like the USDA and various research institutes to share the burden of maintenance and expand our pool of technical resources. + +We are investing in documentation and a GitHub-centric workflow. This lowers the barrier to entry for new developers and ensures that the project's technical knowledge is decentralized and well-preserved. + +Through international conferences and workshops, we foster a global ecosystem of users who provide peer support, bug reporting, and feature suggestions, reducing the maintenance load on the core team. + +## How do you engage with your community? + +We maintain a robust digital presence through Google Groups and dedicated user forums, providing a space for real-time troubleshooting and collaborative problem-solving among thousands of global users. + +We provide comprehensive, open-access technical documentation that is continuously updated to reflect model advancements and user needs. + +We organize workshops and training programs designed to bridge the gap between theoretical modelling and practical application for both students and professionals. + +Each year, we organize a major international conference — such as this year's event in Thessaloniki, Greece — serving as a global summit for developers and researchers to present new findings and coordinate the model's future direction. + +By utilizing GitHub for version control, we invite the community to participate directly in the project's evolution through code contributions, bug reporting, and peer review. + +## Have you taken part in any open source programs or events? + +SWAT+ has moved to a fully open-source model on GitHub, marking a shift toward transparent, community-driven science. The SWAT+ development group organises and actively participates in regional open-science dialogues on how open-source modelling can address various environmental issues. + +However, we have not yet participated in any open-source programmes or events through GitHub. + +## What would you love to achieve by showcasing your project? + +We aim to showcase SWAT+ as the premier open-source modelling tool for solving complex water and land-management challenges, particularly as we integrate new modules and capabilities. By highlighting our move to a collaborative GitHub ecosystem, we hope to attract a new wave of scientist-developers who can contribute niche expertise, ensuring the model evolves as fast as the environmental challenges we face. + +SWAT+ is a leading example of the FAIR principles in action. By hosting our code on GitHub and providing open-access documentation, we ensure our modelling tools are Findable, Accessible, Interoperable, and Reusable for the entire scientific community. + +Showcasing our work helps us connect with global policy-makers, industry leaders, and funding bodies to secure the resources needed for long-term technical maintenance. Ultimately, we want to show how high-quality, FAIR-compliant process-based modelling can be translated into practical, sustainable land and water management policies worldwide. + +## Do you use AI tools in your day to day work on this project? If so, how? + +Yes. In my day-to-day work, I have found myself increasingly using AI to draft source code modifications and troubleshoot or debug user issues. I have also started using AI to help design tools and extensions that support this repository. + +## Do you implement AI into your classroom or coursework? If so, what does that look like in practice? + +N/A. + +## Has AI changed how you maintain or manage your project? + +Yes. Members of our team have started using AI more often to help with writing comments, documentation, commit messages, and pull requests. We also use it when dealing with merge conflicts or when we need help explaining changes more clearly. It has helped make some maintenance tasks faster, especially when the work involves writing, summarizing, or organizing technical details. + +## Have you experimented with AI-driven or automated workflows in your project? + +Members of our team have slowly started to implement limited AI-driven workflows to help with our documentation efforts. So far, this has mostly involved using AI to assist with generating documentation support that helps explain the codebase. + +## How do you see your contributors using AI when working on your project? + +I see contributors using AI mostly as a support tool for understanding the codebase and helping them prepare source code submissions. I think it could be especially helpful for contributors who are new to the project, as long as they still review and understand the changes they are submitting. + +## What concerns or challenges, if any, do you have about the use of AI in your project or field? + +The main concerns with using AI in this project are: + +- **Accuracy and trust:** AI-suggested code can be helpful for fixing potential bugs, but it can sometimes look right without fully matching the scientific logic or intent of the model. +- **Overreliance:** If one leans on AI too much for new code, it is possible to lose connection with what the code is actually doing. Even when AI writes efficient code, it can drift from the core scientific logic if a person is not closely involved in the process. +- **Empowerment:** Many aspiring developers feel empowered by AI, but can become overconfident in their work and ultimately frustrated when a solution provided by AI does not work as expected. + +## How has your approach to maintaining this project evolved over time? + +The approach to maintaining this project is still evolving. While the SWAT+ source code was open source before migrating to GitHub, we have never had such a heavily community-facing process before, and our team is learning better ways to maximise GitHub's capabilities in maintaining this project. We are still exploring the available tools, and are on a steep learning curve. + +## How do you see AI shaping the future of your project or field? + +Three years ago, we likely would have said that AI could only help with simple code completion, basic suggestions, or perhaps act as a source code reference. However, the accelerating pace of AI development continues to surpass our expectations. + +Beyond our current applications, I believe our reliance on AI will grow as the technology matures. Ultimately, I foresee process-based models such as SWAT+ being coupled with AI/ML to increase their predictive accuracy and computational speed. AI can be used to develop model setup tools, suggest calibration strategies, and much more. + +My team and I are actively exploring these research directions; however, as with everything in academia, our progress is subject to the availability of funding and talent. + +## Is there anything else you'd like to share? + +While the model carries a 45-year legacy of scientific development, our journey on GitHub is just beginning. We are currently in the process of transforming decades of world-class hydrological research into a modern, transparent, and community-driven ecosystem. + +It is a privilege to steward such a significant legacy project into the era of Open Science. We are excited to see how the global community will continue to build upon this foundation to solve the environmental challenges of the next 45 years. Thank you for providing a platform that recognises the value of both scientific rigour and open-source collaboration. From 81ad2face2a54294c021c79b974982b5cac4b7ea Mon Sep 17 00:00:00 2001 From: Ashley Nicolson Date: Tue, 5 May 2026 12:26:06 +0100 Subject: [PATCH 07/17] Create maintainer spotlight for Jonathan I. Maletic Added a maintainer spotlight for Jonathan I. Maletic, detailing his work with srcML and its impact on education and research. --- .../academia/srcml-maintainer-spotlight.md | 83 +++++++++++++++++++ 1 file changed, 83 insertions(+) create mode 100644 content/academia/srcml-maintainer-spotlight.md diff --git a/content/academia/srcml-maintainer-spotlight.md b/content/academia/srcml-maintainer-spotlight.md new file mode 100644 index 00000000..d97031f6 --- /dev/null +++ b/content/academia/srcml-maintainer-spotlight.md @@ -0,0 +1,83 @@ +--- +name: Jonathan I. Maletic +institution: Kent State University +department: Department of Computer Science +projectName: srcML +projectRepo: https://github.com/srcML +projectWebsite: http://www.srcML.org +maintainerProfiles: + - github: https://github.com/jmaletic + - orcid: https://orcid.org/0000-0001-5289-135X +badges: ["Academic Maintainer", "Professor"] +description: "An open-source infrastructure for the exploration, analysis, and manipulation of source code, providing an XML format and a multi-language parsing tool that converts source code into srcML." +--- + +## What is srcML, and what does it help people do? + +srcML (pronounced "sõrs em el") is an infrastructure for the exploration, analysis, and manipulation of source code. It is also an XML format for source code, as well as a lightweight, highly scalable, robust, multi-language parsing tool that converts source code into srcML. + +It is an open-source software application licensed under GPL. + +## What inspired you to start this project? + +We needed a source code parser for research in program comprehension, reverse engineering, and software visualisation. It also needed to preserve formatting and comments in the code. At the time, nothing existed that addressed this problem. + +The project has now been under development for over 20 years. + +## How does this project connect to your academic work? + +Many of my graduate students use srcML in their thesis and dissertation research, and I rely on it for most of my own research. It has been supported by the National Science Foundation and is widely used nationally and internationally in software engineering research. + +I also use it in my undergraduate programming course (CSII). + +## Who contributes to the project? + +The project is mainly supported by faculty and students, including Dr. Michael Collard from the University of Akron, Dr. Michael Decker from Bowling Green State University, and myself. + +## How are students involved in the project? + +Graduate and undergraduate students contribute to coding, documentation, testing, and general maintenance. + +## How is the project used in teaching or coursework? + +At KSU, it is used in CSII as part of a project. Students work with the abstract syntax information generated from srcML, represented as an abstract syntax tree. + +They traverse this tree and insert lines of code into programs to instrument them for profiling. + +## What impact has this project had on your students? + +All of my students have benefited significantly from being involved in this project. It has supported their research, helped them develop programming and project management skills, and improved their understanding of open-source systems. + +It has also strengthened their ability to work effectively within a development team. + +## What impact has the project had beyond the classroom or research? + +There are hundreds of srcML users, hundreds of publications that use srcML, and there has been substantial adoption in industry. + +## What does it take to maintain the project? + +The project follows a pull request model for contributions. Releases are made when ready, typically on a yearly basis. + +## What have been the biggest challenges in maintaining the project, especially in an academic setting? + +It is very difficult to build real software in an academic environment. I have given entire talks on this topic. + +## How do you ensure the project remains sustainable over time? + +We have secured funding from the National Science Foundation through the CISE CIRC program. This support has been instrumental in moving the project from a research prototype to usable infrastructure. + +## How do you engage with your community? + +Engagement has primarily taken place at academic conferences in software engineering, through tutorials and technical seminars. These interactions allow us to meet stakeholders and gather feedback. + +## Have you taken part in any open source programs or events? + +No, although we have considered participating in Google Summer of Code. + +## What would you love to achieve by showcasing your project? + +It is a very useful tool for software engineers. Showcasing it would help broaden the user base and raise awareness of its potential applications. + +## Is there anything else you'd like to share about your project or open source journey? + +It has been a fun 25 years. From b703f6e64b1681d3d43fa7fe7ee13a750e8e8779 Mon Sep 17 00:00:00 2001 From: Ashley Nicolson Date: Tue, 5 May 2026 12:38:13 +0100 Subject: [PATCH 08/17] Add maintainer spotlight for GYRE Added a spotlight on Rich Townsend, detailing his work on the GYRE Stellar Oscillation Code, its applications in asteroseismology, and the project's impact on education and research. --- content/academia/gyre-maintainer-spotlight.md | 103 ++++++++++++++++++ 1 file changed, 103 insertions(+) create mode 100644 content/academia/gyre-maintainer-spotlight.md diff --git a/content/academia/gyre-maintainer-spotlight.md b/content/academia/gyre-maintainer-spotlight.md new file mode 100644 index 00000000..85d0c6f1 --- /dev/null +++ b/content/academia/gyre-maintainer-spotlight.md @@ -0,0 +1,103 @@ +--- +name: Rich Townsend +institution: University of Wisconsin-Madison +department: Astronomy +projectName: GYRE Stellar Oscillation Code +projectRepo: https://github.com/rhdtownsend/gyre +projectWebsite: https://gyre.readthedocs.io/en/stable/ +maintainerProfiles: + - github: https://github.com/rhdtownsend + - orcid: https://orcid.org/0000-0002-2522-8605 +badges: ["Academic Maintainer", "Professor"] +description: "A software tool for simulating oscillations of stars, widely used in asteroseismology to constrain the internal structure and composition of stars by comparing observed oscillation frequencies against theoretical predictions." +--- + +## What is GYRE, and what does it help people do? + +GYRE is a software tool for simulating oscillations of stars. Just like the strings of a guitar vibrate at specific frequencies when plucked, stars can undergo oscillations at specific frequencies when they are disturbed by internal or external forces. We can't hear these oscillations, but we can measure their effect on the brightness of the star. By comparing their frequencies against the predictions made using GYRE, we can establish constraints on the internal structure and composition of stars — a technique known as "asteroseismology". + +## What inspired you to start this project? + +The project was originally created as a proof of concept for a numerical technique. I had written stellar oscillation codes before GYRE, but they all suffered from the same numerical issue. I wrote GYRE to test out a new idea for circumventing this issue (which turned out to be successful). Soon after developing GYRE, I released it under an open-source license, and it was quickly adopted by the wider community as a go-to tool for analysing the asteroseismic data being obtained by NASA's Kepler mission. + +## How does this project connect to your academic work? + +It has been central to my research for over a decade, and serves as a test bed for developing and evaluating new numerical techniques. + +## Who contributes to the project? + +The project is primarily maintained by me, with contributions from graduate students, undergraduates, and external contributors. + +## How are students involved in the project? + +Most of my students work on research that makes use of GYRE, and in the process of this research it is often necessary to extend GYRE's capabilities — giving them the opportunity to contribute new functionality (and supporting documentation) to the project. + +## How is the project used in teaching or coursework? + +It is used in specialised courses at other universities, and in summer schools that are focused on GYRE and an open-source stellar structure/evolution code (MESA) that GYRE can couple to. Participants span a range of career stages, extending from undergraduates through to emeritus professors. I haven't yet integrated GYRE into my regular teaching, because our curriculum currently lacks any classes that explicitly cover asteroseismology. + +## What impact has this project had on your students? + +Students develop programming and numerical modelling skills through their involvement in the project. They also get their first experience of involvement in an open-source project, introducing them to topics (e.g., using git, writing documentation, creating testing frameworks) that aren't often covered in programming classes. + +## What impact has the project had beyond the classroom or research? + +GYRE has been used in more than 600 publications and is widely adopted within the asteroseismology field. It is now also being applied to model the tides that arise in binary star systems and star-planet systems. + +## What does it take to maintain the project? + +A fair amount of work! Over the past year, I've probably spent hundreds of hours responding to issues opened by users, adding new features to the code, and implementing optimizations to speed up runtimes. + +## What have been the biggest challenges in maintaining the project? + +Balancing development work with research output and academic incentive structures is a key challenge. Maintaining and improving GYRE primarily benefits its users rather than me, whereas in academia metrics focus on the number of papers published and the citations these garner. + +## How do you ensure the project remains sustainable over time? + +I secure research grants from NASA and the NSF. These are usually focused on addressing a specific scientific question, but typically involve work on GYRE to improve/extend it as part of the research effort. The grants are my primary mechanism for supporting the graduate and undergraduate students within my group. + +## How do you engage with your community? + +Primarily through ensuring that the project documentation is as thorough and accessible as possible, and that issues opened by users are responded to in a timely manner. I also participate in the summer schools mentioned previously, and present seminars advertising GYRE at other educational institutions. + +## Have you taken part in any open source programs or events? + +No. + +## What would you love to achieve by showcasing your project? + +To highlight the sustainability and long-term impact of academic open-source software. + +## Do you use AI tools in your day to day work on this project? + +Yes — I started using Claude about 6 months ago; I've found it useful in suggesting where further optimizations to the code might be possible. + +For small and/or automatable changes (e.g., a global rename of a variable), I find Claude to be a great time-saver. But I remain hesitant about letting it make significant changes to the code architecture; I don't want to get to a point where I don't understand the code. + +## Do you implement AI into your classroom or coursework? + +I don't use AI in the classroom yet, as I'm still getting familiar with the technology and its upsides/downsides. + +## Has AI changed how you maintain or manage your project? + +For small and/or automatable changes it has been a great time-saver. I have not yet experimented with AI-driven or automated workflows in the project. + +## How do you see your contributors using AI when working on your project? + +Not sure; contributions from others remain too infrequent for me to assess how they use AI. + +## What concerns or challenges, if any, do you have about the use of AI in your project or field? + +For me, the biggest risk is in ending up with a code that nobody (human) understands. An important aspect of my project is not only the code, but the understanding of what numerical methods are/can be/should be used to solve stellar oscillation problems. I don't want that institutional knowledge to get lost. + +## How has your approach to maintaining this project evolved over time? + +Since I migrated the project to GitHub, there hasn't been much change to the maintenance side of things. But I'm hoping to change this in the near future, using techniques such as continuous integration. + +## How do you see AI shaping the future of your project or field? + +I think my specific subfield — stellar oscillation codes — is too niche to benefit greatly from AI. But I do see AI having a big impact on asteroseismology, by opening up new ways to mine measurements of stellar oscillations. + +## Is there anything else you'd like to share? + +It's been my experience that open source enables unexpected collaborations and long-term partnerships, and I've greatly benefitted from both of these. From 9ba624f94118e54df93e1240a94164661573d682 Mon Sep 17 00:00:00 2001 From: Ashley Nicolson Date: Tue, 5 May 2026 13:19:09 +0100 Subject: [PATCH 09/17] Adding xDSL maintainer spotlight content Adding xDSL maintainer spotlight --- content/academia/xdsl-maintainer-spotlight.md | 150 ++++++++++++++++++ 1 file changed, 150 insertions(+) create mode 100644 content/academia/xdsl-maintainer-spotlight.md diff --git a/content/academia/xdsl-maintainer-spotlight.md b/content/academia/xdsl-maintainer-spotlight.md new file mode 100644 index 00000000..36849356 --- /dev/null +++ b/content/academia/xdsl-maintainer-spotlight.md @@ -0,0 +1,150 @@ +--- +name: Sasha Lopoukhine, Mathieu Fehr, Tobias Grosser +institution: University of Cambridge +department: Department of Computer Science and Technology +projectName: xDSL +projectRepo: https://github.com/xdslproject/xdsl/ +projectWebsite: https://xdsl.dev/ +maintainerProfiles: + - github: http://github.com/tobiasgrosser + - orcid: https://orcid.org/0000-0003-3874-6003 +badges: ["Academic Maintainer"] +description: "An accessible, high-productivity compiler framework for experienced and new compiler developers, compatible with MLIR and used in academia and industry for teaching, research, and production compiler development." +--- + +xDSL_logo + + +## What is xDSL, and what does it help people do? + +xDSL is an accessible, high-productivity compiler framework for experienced and new compiler developers. Thanks to its compatibility with [MLIR](https://mlir.llvm.org/) (Multi-Level Intermediate Representation), its users can tap into LLVM's rich ecosystem of production compilers and backends. xDSL is used in both academia and industry for teaching, research and production compiler development. Industry partners who value developer productivity and Python ecosystem integration have repeatedly chosen xDSL as the foundation of their industry-grade software products. + +xDSL leverages Python's portability and ease of installation to minimize setup overhead and enable rapid iteration to both students and domain experts. Type hints and extensive testing ensure efficient editing and high code quality. xDSL's interactive compilation environments (e.g., xdsl-gui and Python notebooks) enable developers to explore transformations in a responsive and visual setting. + +xDSL uses the same textual representation of programs as MLIR, making it easy to combine both frameworks while maintaining compatibility through continuous integration. This enables research and development across the entire compilation stack, from domain-specific optimisations for large-scale computing to low-level assembly representations for specialised hardware. + +## What inspired you to start this project? + +Development speed in compiler design had become an innovation bottleneck in academia and central for the success of innovative hardware companies. Existing C++-based compiler frameworks optimized heavily for minimal compile-time performance, but often at the expense of developer productivity and accessibility. + +While MLIR's novel multi-level approach revolutionized the design of neural network compilers in industry, MLIR's innovations remained less accessible for academic users and industrial stakeholders targeting Python-based developer communities. The complexity of C++ projects and the overheads they introduce for prototyping prevented the wider use of a state-of-the-art MLIR-style compiler design. + +We designed xDSL to answer the question: can we build production-style compilers that make developer productivity a first-class objective? + +## How does this project connect to your academic work? + +xDSL was born as a collaborative research project between the University of Edinburgh (then Cambridge), EPCC, and Imperial College London. Principal investigators [Tobias Grosser](https://grosser.science/), [Michel Steuwer](https://steuwer.info/), [Nick Brown](https://www.epcc.ed.ac.uk/about-us/our-team/dr-nick-brown), [Amrey Krause](https://www.epcc.ed.ac.uk/about-us/our-team/dr-amy-krause), [Gerard Gorman](https://profiles.imperial.ac.uk/g.gorman), and [Paul Kelly](https://profiles.imperial.ac.uk/p.kelly) kicked off a project that aimed to improve the architecture of the [Devito](https://github.com/devitocodes/devito) and [PSyclone](https://www.esiwace.eu/p-syclone/) HPC compilers, which led to work on accelerated stencil computations on [GPUs](https://dl.acm.org/doi/10.1145/3620666.3651344) and the [Cerebras Wafer-Scale Engine](https://dl.acm.org/doi/10.1145/3779212.3790124) as well as our key idea of [federated compilation with xDSL](https://dl.acm.org/doi/10.1145/3696443.3708945) (published at ASPLOS and CGO). In addition, an active research collaboration was formed and numerous follow-up projects were seeded. + +As a cornerstone of the Horizon Europe [CONVOLVE](https://convolve.eu/) compiler workpackage, xDSL developed into a sizable open-source project. At conferences such as CGO, PLDI, and ASPLOS, we published papers on [new ISA-level backend abstractions](https://dl.acm.org/doi/10.1145/3696443.3708952), [first-class verification dialects for MLIR](https://dl.acm.org/doi/10.1145/3729309), and [accelerator configuration overhead modeling](https://dl.acm.org/doi/10.1145/3760250.3762225). Several of our ideas were first prototyped in xDSL and subsequently upstreamed to LLVM, for example the MPI, SMT and (soon) ISA dialects in MLIR. Our CONVOLVE partners (e.g., [KU Leuven](https://micas.esat.kuleuven.be/team/marian-verhelst), [Universidad de Murcia](https://webs.um.es/alexandra.jimborean/miwiki/doku.php), …) as well as other EU projects provided valuable input through their research use of xDSL. This collaboration was reinforced through dedicated xDSL workshops (e.g. ASPLOS and HiPEAC) and hands-on development activities such as the CONVOLVE compiler hackathon, where xDSL was used to support joint experimentation, integration, and co-design across partners. + +Overall, xDSL streamlined our own research, led to significant research collaborations, and enabled many external researchers to collaborate with us. + +## Who contributes to the project? + +xDSL is maintained by a team of students, academics, and industry experts. Increased adoption in production compilers attracts additional open-source contributions. With over 5,000 commits from 125 contributors in total and 34 active contributors in the last 6 months (half of whom had not made prior contributions) the xDSL community grows steadily. Students who leverage xDSL for their dissertation projects frequently upstream changes that would be useful to the broader xDSL community, which leads to a continued inflow of academic contributors. + +## How are students involved in the project? + +PhD students and postdocs are instrumental to the development of xDSL and take on central leadership roles. Their responsibilities include development, code reviews, communication, and even logo and website design. We are frequently approached by students entering compiler development, who often become active members of the project. xDSL serves students as an entry point into both compilers and collaborative open-source software engineering. + +## How is the project used in teaching or coursework? + +xDSL is used in teaching compilers in universities and industry. It is used in introductory compiler courses at University of Edinburgh and TU Berlin. We co-organised two MLIR schools in [winter](https://mlir-school.github.io/summer-2025/past_editions/) and [summer 2025](https://mlir-school.github.io/summer-2025/), which leveraged our interactive xDSL-based tutorial notebooks as an introduction to MLIR-style compiler development. The upcoming [2026 MLIR School](https://mlir-school.github.io/summer-2026/) (Aug 2026 - during the solar eclipse in Spain) will also feature an introduction to MLIR using xDSL. + +xDSL contributors at the 2025 MLIR (Un)School + + +## What impact has this project had on your students? + +xDSL has served as a foundation for a number of research papers and dissertations. Doing research in an open-source project improves collaboration opportunities, and increases visibility in industry. + +We collected some quotes: + +> "xDSL provided the infrastructure that made my doctoral research into tensor data-layout optimization tractable. It enabled highly productive development of experimental intermediate representation design to be paired with existing backend compiler support built into LLVM. I have continued to work with xDSL at Riverlane where we are building compilation tools for quantum error correction that are developed by quantum researchers and FPGA specialists alike. xDSL has provided a toolset that helps to bring these disciplines together, taking advantage of Python's large ecosystem and MLIR's rigorous compiler model." +> +> — Edward Stow, Former PhD student at Imperial College London, Today at Riverlane + +> "In our research, we are using xDSL to quickly iterate on the design of [Tamagoyaki](https://github.com/jumerckx/Tamagoyaki), an equality saturation framework that tightly integrates with existing compiler infrastructure. In contrast to MLIR, which is a vast and complex C++ codebase, xDSL is more approachable, and allows us to focus on our research contributions more directly." +> +> — Jules Merckx, PhD student at Ghent University + + +Jules and Sasha, maintainers of xDSL. + + +> "xDSL was my introduction to compilers. It was incredibly approachable and gave me the confidence to dive deeper into the field. Through it, I created "xdsl-gui," now part of the xDSL ecosystem, as my first attempt at interactive compilation tooling. It visualizes pass application, streamlines pass selection by filtering irrelevant options, and provides real-time IR and performance feedback to help measure optimization impact. xDSL genuinely empowered me and kickstarted my compiler journey. I probably would have had a very different experience if my first exposure had been a more heavyweight system. Later, transitioning to MLIR and related tooling felt smooth thanks to the foundation I built with xDSL." +> +> — Dalia Shaaban, Master Student at ETH Zurich + + +Dalia and Markus, contributors to xDSL + + +## What impact has the project had beyond the classroom or research? + +xDSL is seeing growing adoption in industry. It is used for neural network compilation by AI accelerator startups (engineers from [Synthara](https://synthara.ai/) have recently been making contributions to xDSL), and is used in Google's [LiteRT](http://github.com/google-ai-edge/LiteRT) framework. It is also gaining traction in the quantum compilation space, and is used by [Riverlane](https://www.riverlane.com/), [Xanadu's PennyLane](https://github.com/PennyLaneAI/pennylane) compiler, and [Eclipse's Qrisp](https://github.com/eclipse-qrisp/Qrisp). xDSL's use of Python's type system for compile-time type checking was cited as a motivating example in [PEP 747](https://peps.python.org/pep-0747/). Last year, xDSL was added to the [CPython performance suite](https://github.com/python/pyperformance/tree/b5dfaee6d4da542dc58b2070e018d8449d60d7d9/pyperformance/data-files/benchmarks/bm_xdsl), helping Python core developers optimise typical compiler workloads. + +## What does it take to maintain the project? + +The project is primarily maintained by two PhD students and two researchers in my group, with additional contributions from other students, researchers, and engineers both inside and outside the group. Over the last year, we've had approximately four commits a day, with a median PR review time of around 10.5 hours. + +Contributor onboarding is supported by a detailed "getting started guide", "good first issues" labels, and a robust CI infrastructure. The framework has published 95 releases, and follows a weekly release cycle on PyPI. + +Sasha and Mathieu on their way to presenting xDSL at CGO 2025. + + +## What have been the biggest challenges in maintaining the project, especially in an academic setting? + +The most significant challenges occurred in the early stages of the project, when a large amount of functionality was required to reach compatibility with MLIR. + +Now that this foundation is more stable, contributions can happen in the background and require less time relative to research work. Changes are made and reviewed by students and researchers in the team, allowing them to integrate smoothly alongside other responsibilities. + +## How do you ensure the project remains sustainable over time? + +Sustainability largely comes from shared ownership. As more research groups and industry adopt xDSL, they contribute improvements and maintenance back to the project. This collaborative open-source model helps distribute the long-term maintenance effort across the community. + +## How do you engage with your community? + +We maintain a website and documentation, alongside GitHub Discussions and an open Zulip chat, with 159k total messages and an average of 30 daily active users. We run weekly meetings that are open to the xDSL community, where we discuss ongoing topics in the development and maintenance of xDSL. + +We also provide guidance on pull request formatting and onboarding. On a new member's first day, an existing team member helps them open their first pull request, ensuring early engagement. + +## Have you taken part in any open source programs or events? + +Not yet, but we would be interested in participating in the future. + +## What would you love to achieve by showcasing your project? + +The project is inherently social and becomes more useful as its user base grows. We hope that showcasing it will encourage more people to try it and contribute. In fact, we want to encourage design choices that challenge conventional wisdom, like the idea of writing a compiler in Python. While not the obvious choice for a traditional compiler engineer, the new design point xDSL chose has led to significant innovation which also regularly feeds back to the LLVM community. + +## Do you use AI tools in your day to day work on this project? If so, how? + +Individual contributors use AI, e.g., using editor integrations. + +## Do you implement AI into your classroom or coursework (if applicable)? If so, what does that look like in practice? + +Not at the moment. + +## Has AI changed how you maintain or manage your project? + +AI has led to an increase in patch submissions. We carefully work with contributors to educate them on how to best contribute to an open-source project and added a [CONTRIBUTING.md](https://github.com/xdslproject/xdsl/blob/main/CONTRIBUTING.md) file to help both humans and AI with contributions. Interestingly, best practices in open-source projects, e.g., splitting patches into individual features and having only a small number of patches in-flight hold for both humans and AI patches. + +## How do you see your contributors using AI when working on your project? + +PRs and code contributions may include some AI-generated content, but we do not receive an overwhelming level of AI-generated code. + +## What concerns or challenges, if any, do you have about the use of AI in your project or field? + +Our project has good test coverage, but this coverage still requires humans to inspect the tests. At higher contribution rates, ensuring correctness will become challenging. + +## How has your approach to maintaining this project evolved over time? + +Our workflow has become significantly streamlined over time. The LLVM community has an incredibly efficient workflow which we adopted and evolved. We can meanwhile handle a steady stream of contributions at very low latency, which we are very proud of. + +## How do you see AI shaping the future of your project or field? + +AI will be a powerful tool, which accelerates and even automates our workflows to a large degree. Open-source communities will face pressure to evolve. Yet, they also offer a unique opportunity: they already have humans and machines interact at scale to reach consensus - such workflows will likely gain importance as the use of AI increases. + +## Is there anything else you'd like to share about your project or open source journey? + +My (Tobias') personal academic career started with open-source development and led to a strong desire to perform open-source-first research. I began contributing to open source over 15 years ago as a GCC developer, when I joined the Graphite research project led by Sebastain Pop and Albert Cohen. Since my first day as a student, open source has played a major role in shaping my career. In fact, I wrote almost exclusively open-source code, most of which either became part of or initiated an open-source project. Mathieu and Sasha both develop large-scale open-source projects as core part of their PhD, and give students with xDSL every day the opportunity to engage in open-source-focused research. For us, open-source research is engaging, productive, and incredibly social. We thank the xDSL and wider open-source community for the welcoming and engaging atmosphere they offer! From b173ddd20f1f3955b0e6138a30c3a3e6538005dd Mon Sep 17 00:00:00 2001 From: Ashley Nicolson Date: Tue, 5 May 2026 13:31:23 +0100 Subject: [PATCH 10/17] Create spotlight for Manifold Scholarship maintainer Added a spotlight article for Matthew Gold detailing the Manifold Scholarship project, its impact on digital humanities, and community engagement. --- ...nifold-scholarship-maintainer-spotlight.md | 81 +++++++++++++++++++ 1 file changed, 81 insertions(+) create mode 100644 content/academia/manifold-scholarship-maintainer-spotlight.md diff --git a/content/academia/manifold-scholarship-maintainer-spotlight.md b/content/academia/manifold-scholarship-maintainer-spotlight.md new file mode 100644 index 00000000..c058d460 --- /dev/null +++ b/content/academia/manifold-scholarship-maintainer-spotlight.md @@ -0,0 +1,81 @@ +--- +name: Matthew Gold +institution: CUNY Graduate Center +department: MA Program in Digital Humanities / Ph.D. Program in English +projectName: Manifold Scholarship +projectRepo: https://github.com/ManifoldScholar/manifold +projectWebsite: http://manifoldapp.org +maintainerProfiles: + - github: https://github.com/mkgold + - orcid: https://orcid.org/0000-0001-6173-7194 +badges: ["Academic Maintainer", "Co-Principal Investigator"] +description: "An open-source platform for scholarly publishing that allows publishers to create dynamic projects with embedded notes, files, images, videos, interactive content, and collaborative annotation." +--- + +## What is Manifold, and what does it help people do? + +Manifold is an open-source platform for scholarly publishing developed by the CUNY Graduate Center, University of Minnesota Press, and Cast Iron Coding. + +It allows publishers to create dynamic projects with embedded notes, files, images, videos, and interactive content, as well as collaborative annotation. + +## What inspired you to start this project? + +Manifold was created after the Mellon Foundation sought applications from university presses to explore the future of the digital scholarly monograph. + +Having collaborated on a website to share the first edition of Debates in the Digital Humanities, the CUNY Graduate Center, University of Minnesota Press, and Cast Iron Coding submitted a proposal to Mellon to enable presses to create interactive, web-based editions of their books. The platform features an attractive, responsive design and allows readers to comment on and highlight passages of interest. + +Manifold is now used by dozens of publishers, ranging from large university presses such as the University of London Press to library publishers such as Brown University and the University of Pennsylvania to organizations such as the American Council of Learned Societies. The Manifold code repository on GitHub has received over four thousand commits and has been starred over two hundred and fifty times. + +## How does this project connect to your academic work? + +I work in digital humanities, specifically in digital scholarly publishing. Manifold connects to my work on the future of publishing, as well as on open education and the creation of open educational resources. + +## Who contributes to the project? + +Our development team is the leading contributor to the project, but we receive input on feature development from students and staff, along with contributions from external developers. The project team is listed here: https://manifoldapp.org/history + +## How are students involved in the project? + +Students contribute by creating documentation, running workshops, and providing consultations to students, faculty, and staff who use Manifold. + +## How is the project used in teaching or coursework? + +In some courses, students produce a Manifold edition as their final project. Examples of these projects can be found here: https://cuny.manifoldapp.org/projects/project-collection/cuny-class-projects?collectionOrder=cuny-class-projects + +## What impact has this project had on your students? + +Students have gained experience in digital publishing, creating online critical editions of books, and producing open educational resources to lower textbook costs. This has resulted in skill development, job opportunities, and a deeper understanding of open source projects. + +## What impact has the project had beyond the classroom or research? + +Manifold has been widely adopted by scholarly publishers and is increasingly used as a platform for publishing open educational resources. Manifold texts are now being used in many classes, and students are also using the platform to publish capstone, thesis, and dissertation projects. + +## What does it take to maintain the project? + +Our team meets monthly and communicates daily on Slack. Our development partners at Cast Iron Coding set milestones for each release, which the team collaborates on and tests. After starting with grant funding, we are finding ways to sustain the project through fees from publishers who host with us. + +## What have been the biggest challenges in maintaining the project, especially in an academic setting? + +One of the biggest challenges is securing funding for essential but less visible work, such as updating code libraries and managing dependencies. These areas are often less attractive to funders than developing new features. + +## How do you ensure the project remains sustainable over time? + +We maintain multiple funding streams, including internal support, competitive institutional grants, and grant funding. We also have an active community of Manifold publishers who pay for hosted instances of the platform, and we offer training packages as an additional source of support. + +## How do you engage with your community? + +We hold regular community meetings that give participants the opportunity to connect with one another. These meetings typically include presentations from Manifold publishers and demonstrations of new features. + +## Have you taken part in any open source programs or events? + +We have participated in academic conferences and library events focusing on open-source publishing. + +## What would you love to achieve by showcasing your project? + +We are very proud of Manifold and believe more people should know about it. We also see it as an open-source success story — multi-institutional and sustainable — that could be valuable for others to learn from. + +## Is there anything else you'd like to share about your project or open source journey? + +Sustaining a project like Manifold takes dedicated care from a focused project team. The greatest strength of our team is our successful collaboration between different types of organizations — a digital humanities center, a university press, and a development agency. + +One important note is that Manifold is a platform, and each instance operates independently. Examples include: https://cuny.manifoldapp.org/ | https://manifold.umn.edu/ | https://brown.manifoldapp.org/ | https://alg.manifoldapp.org/ (and many more). From eca366b11010ea21e22608733e7576772118e552 Mon Sep 17 00:00:00 2001 From: Ashley Nicolson Date: Tue, 5 May 2026 13:45:42 +0100 Subject: [PATCH 11/17] Create maintainer spotlight for Wordplay project Added a spotlight on Amy Ko, detailing her project Wordplay, its goals, contributors, and challenges in an academic setting. --- .../academia/wordplay-maintainer-spotlight.md | 73 +++++++++++++++++++ 1 file changed, 73 insertions(+) create mode 100644 content/academia/wordplay-maintainer-spotlight.md diff --git a/content/academia/wordplay-maintainer-spotlight.md b/content/academia/wordplay-maintainer-spotlight.md new file mode 100644 index 00000000..8b6bee6a --- /dev/null +++ b/content/academia/wordplay-maintainer-spotlight.md @@ -0,0 +1,73 @@ +--- +name: Amy Ko +institution: University of Washington +department: The Information School +projectName: Wordplay +projectRepo: https://github.com/wordplaydev/wordplay +projectWebsite: https://wordplay.dev/ +maintainerProfiles: + - github: https://github.com/amyjko + - orcid: https://orcid.org/0000-0001-7461-4783 +badges: ["Academic Maintainer", "Professor"] +description: "An educational programming language designed for young adolescents and their teachers, embracing global, multilingual, ability-diverse, and neurodiverse communities." +--- + +## What is Wordplay? + +Wordplay is an educational programming language designed for young adolescents and their teachers. It starts from the reality that the world is global, multilingual, ability-diverse, and neurodiverse, and strives to embrace and celebrate these differences in its design, as well as in the media it enables youth to create and explore. + +It is a teacher- and student-led project, with contributions from more than 300 K–12 and college students, spanning design, development, localisation, verification, content curation, and governance. + +## What inspired this project? + +I started this project during my 2022/23 sabbatical to examine a single question: what would educational programming languages look like if they were designed for everyone, instead of just white, Western, non-disabled, neurotypical, English-fluent men? + +As a mixed-race, transgender, multilingual scholar who has never fully resonated with the visions of computing that emerged from elite, male-dominated institutions in the US and UK, I wanted to pursue a different vision — one that centres disability, gender, racial, linguistic, and educational justice, rather than the capitalist, extractive values of efficiency and profit. + +## How the project connects to academic work + +Wordplay is one of my core, long-term research projects, expected to continue for 10–20 years. It will be published at the ACM CHI 2025 conference in Yokohama, Japan. + +As a community-engaged project, the focus is on partnership rather than scale. The team works closely with a middle school technology teacher in Bellevue, Washington, whose students are multilingual, immigrants, neurodiverse, and gender diverse. These students help shape the platform and co-design curricula in response to their identities, interests, and visions of computing. They are not only users of the platform, but also contributors to it. + +## Who contributes to Wordplay? + +Middle and high school students, college students, teachers, faculty, postdocs, PhD students, software developers, and disability advocates all contribute to the project. Students contribute to all aspects, including design, development, verification, localisation, content creation, governance, workflow, strategic direction, and fundraising. + +In the past three years, the project has impacted the skills, knowledge, and commitments to justice of more than 400 student contributors. Many share that they had never previously considered who is excluded from computer science because programming languages are not designed for everyone. They often describe not being able to "unsee" how computing is designed for a small subset of humanity, and express a desire for more opportunities to reshape it. + +## What it takes to maintain the project + +I serve as the project facilitator and lead developer. Middle school students and their teachers identify defects, enhancements, and strategic directions, which define the milestones and priorities for the project. + +Undergraduates work on these priorities in partnership with students and teachers, learning software engineering through a year-long directed research group. The project uses continuous integration, fork-based pull request development, and releases are typically made weekly. + +Because contributors are often low-skill and high-turnover, the team structure relies on my stable role as a tenured professor to maintain institutional knowledge, project management, and fundraising. The project currently has no dedicated funding, and given the broader political climate, there is limited expectation of future support. + +## Biggest challenges in an academic setting + +Student learning and turnover are the biggest barriers to progress. While teaching students to a level where they can make meaningful contributions is rewarding, onboarding them alongside their other coursework — and with limited resources to compensate their time — often results in eight weeks of teaching for only two weeks of project contributions. + +As a result, most development work falls to me, often on weekends, since faculty life is too fragmented to allow for the sustained focus that engineering progress requires. + +## Ensuring long-term sustainability + +Several strategies support sustainability: seeking student funding from the NSF (though this is becoming increasingly limited), seeking unrestricted gift funding to remain agile and responsive to student and teacher needs, and negotiating with the Dean to ensure that maintaining the project is recognised as part of teaching and research responsibilities. + +Community engagement centres on local middle school teachers. The team meets with them weekly, gathers their needs, visits classrooms, and involves students in design prioritisation. Due to COPPA regulations, youth under 13 cannot participate directly in the project's Discord server, so teachers are engaged there as representatives of student needs. + +## AI tools and the project + +The team uses some AI-assisted development tools, but only with extreme caution: most contributors are inexperienced software developers and are not yet capable of using AI with intention. This has required additional scaffolding and higher levels of scrutiny on pull requests. + +Machine translation tools are used to generate draft translations of user interface text, documentation, and programming language content, with volunteers auditing and refining the output. This is the one area where semi-automation has proven genuinely useful — it is very hard to find multilingual contributors across all supported languages, and a lower-quality translation is better than none at all. + +Overall, AI has made the project harder to manage. It has made it easier for students and contributors to share low-quality work, increasing the labour involved in quality control. Several communication errors have also arisen from contributors using AI to generate comments in GitHub issues, where the polished English produced by AI is often more confusing than the natural, unpolished writing that more clearly conveys intent. + +For coursework, AI is a subject of critical inquiry as much as a tool — complicating industry claims about value with broader systemic accounts of sustainability, theft, and concentration of power. + +## Open source journey + +At a time when colleges and universities are under pressure, and many marginalised groups are being dismissed or excluded, it is critical to push back and insist that everyone deserves to participate fully in society. + +Highlighting this project is an opportunity to amplify that idea and to support a vision of computing that is inclusive, rather than one that continues to prioritise profit over people. I hope to inspire others to either support Wordplay or to create their own projects that reimagine computing in ways that engage and include everyone. From 363e4e54b0ebae50d99fd3dce97fd3fe17676300 Mon Sep 17 00:00:00 2001 From: Ashley Nicolson Date: Tue, 5 May 2026 14:32:22 +0100 Subject: [PATCH 12/17] Updated Github to GitHub Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com> --- content/academia/personal-analytics-maintainer-spotlight.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/academia/personal-analytics-maintainer-spotlight.md b/content/academia/personal-analytics-maintainer-spotlight.md index 2a07c214..60b20c94 100644 --- a/content/academia/personal-analytics-maintainer-spotlight.md +++ b/content/academia/personal-analytics-maintainer-spotlight.md @@ -77,7 +77,7 @@ In 2025, the project received approximately 150,000 USD in funding from the Digi ## How do you engage with your community? -We actively engage with the community through Github's issues and PRs. At the same time, we maintain an active documentation, including videos and showcases of app uses and studies, as well as offering demos to researchers when helpful. +We actively engage with the community through GitHub's issues and PRs. At the same time, we maintain an active documentation, including videos and showcases of app uses and studies, as well as offering demos to researchers when helpful. ## Have you taken part in any open source programs or events? From 19b30959874aa0626dfa38a8992507e4ab3fd2ae Mon Sep 17 00:00:00 2001 From: Ashley Nicolson Date: Tue, 5 May 2026 14:32:54 +0100 Subject: [PATCH 13/17] Update http to https Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com> --- content/academia/xdsl-maintainer-spotlight.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/academia/xdsl-maintainer-spotlight.md b/content/academia/xdsl-maintainer-spotlight.md index 36849356..e3340d84 100644 --- a/content/academia/xdsl-maintainer-spotlight.md +++ b/content/academia/xdsl-maintainer-spotlight.md @@ -6,7 +6,7 @@ projectName: xDSL projectRepo: https://github.com/xdslproject/xdsl/ projectWebsite: https://xdsl.dev/ maintainerProfiles: - - github: http://github.com/tobiasgrosser + - github: https://github.com/tobiasgrosser - orcid: https://orcid.org/0000-0003-3874-6003 badges: ["Academic Maintainer"] description: "An accessible, high-productivity compiler framework for experienced and new compiler developers, compatible with MLIR and used in academia and industry for teaching, research, and production compiler development." From 035d516f229636569badd3e50814075896cc82c6 Mon Sep 17 00:00:00 2001 From: Ashley Nicolson Date: Tue, 5 May 2026 14:33:56 +0100 Subject: [PATCH 14/17] Fix spelling of Sebastain Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com> --- content/academia/xdsl-maintainer-spotlight.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/academia/xdsl-maintainer-spotlight.md b/content/academia/xdsl-maintainer-spotlight.md index e3340d84..2c276ea3 100644 --- a/content/academia/xdsl-maintainer-spotlight.md +++ b/content/academia/xdsl-maintainer-spotlight.md @@ -147,4 +147,4 @@ AI will be a powerful tool, which accelerates and even automates our workflows t ## Is there anything else you'd like to share about your project or open source journey? -My (Tobias') personal academic career started with open-source development and led to a strong desire to perform open-source-first research. I began contributing to open source over 15 years ago as a GCC developer, when I joined the Graphite research project led by Sebastain Pop and Albert Cohen. Since my first day as a student, open source has played a major role in shaping my career. In fact, I wrote almost exclusively open-source code, most of which either became part of or initiated an open-source project. Mathieu and Sasha both develop large-scale open-source projects as core part of their PhD, and give students with xDSL every day the opportunity to engage in open-source-focused research. For us, open-source research is engaging, productive, and incredibly social. We thank the xDSL and wider open-source community for the welcoming and engaging atmosphere they offer! +My (Tobias') personal academic career started with open-source development and led to a strong desire to perform open-source-first research. I began contributing to open source over 15 years ago as a GCC developer, when I joined the Graphite research project led by Sebastian Pop and Albert Cohen. Since my first day as a student, open source has played a major role in shaping my career. In fact, I wrote almost exclusively open-source code, most of which either became part of or initiated an open-source project. Mathieu and Sasha both develop large-scale open-source projects as core part of their PhD, and give students with xDSL every day the opportunity to engage in open-source-focused research. For us, open-source research is engaging, productive, and incredibly social. We thank the xDSL and wider open-source community for the welcoming and engaging atmosphere they offer! From 5f9f5429665118d7e54f31f51d1005de4ac69884 Mon Sep 17 00:00:00 2001 From: Ashley Nicolson Date: Tue, 5 May 2026 14:46:21 +0100 Subject: [PATCH 15/17] Enhance JPlag maintainer spotlight with demo and images Added demo link and images to the JPlag maintainer spotlight. --- content/academia/jplag-maintainer-spotlight.md | 12 +++++++++++- 1 file changed, 11 insertions(+), 1 deletion(-) diff --git a/content/academia/jplag-maintainer-spotlight.md b/content/academia/jplag-maintainer-spotlight.md index 06d34c9e..797d7ce3 100644 --- a/content/academia/jplag-maintainer-spotlight.md +++ b/content/academia/jplag-maintainer-spotlight.md @@ -5,6 +5,7 @@ department: KASTEL – Institute of Information Security and Dependability projectName: JPlag projectRepo: https://github.com/jplag/JPlag projectWebsite: https://helmholtz.software/software/jplag +projectDemo: https://demo.jplag.de/ maintainerProfiles: - github: https://github.com/tsaglam - orcid: https://orcid.org/0000-0001-5983-4032 @@ -16,7 +17,10 @@ description: "A powerful, open-source plagiarism detection tool for source code JPlag is a powerful, open-source plagiarism detection tool for source code, designed for educational institutions. It detects structural similarities among sets of programs and can identify plagiarism even when the program code has been obfuscated. It presents the results in an interactive report which allows educators to detect and inspect suspiciously similar programs. However, the final decision of identifying plagiarism is left to instructors, given the ethical considerations involved in this task. -JPlag supports more than 15 programming languages. The input code is processed entirely locally, ensuring GDPR–compliance. +JPlag supports more than 15 programming languages. The input code is processed entirely locally, ensuring GDPR–compliance. [Demo available here](https://demo.jplag.de/) + +Screenshot of JPlag Main View + ## What inspired you to start this project? @@ -26,6 +30,9 @@ JPlag was originally developed in 1996 at Karlsruhe Institute of Technology to a It serves both as a research subject and as a practical tool used in teaching. +screenshot JPlag Code View + + ## Who contributes to the project? Researchers at KIT, students, and external contributors. Development has, however, been heavily driven by our team. We would love to have more external contributors. @@ -46,6 +53,9 @@ Students gain real-world open-source experience and develop stronger software en JPlag is used in academic institutions around the world. We know of more than 300 universities that use it to uphold academic integrity in their courses. JPlag has more than 50,000 downloads, is widely cited in research publications and integrated into multiple educational platforms. +Screenshot JPlag Cluster View + + ## What does it take to maintain the project? A core team of doctoral researchers maintains the project, supported by a small team of student developers. From cabf7def9a2f3113dc2c5088c7eeaabb28ec46c2 Mon Sep 17 00:00:00 2001 From: Ashley Nicolson Date: Tue, 5 May 2026 15:44:22 +0100 Subject: [PATCH 16/17] Update Jenkins Warnings plugin spotlight content --- .../jenkins-warnings-ng-maintainer-spotlight.md | 10 ++++++++++ 1 file changed, 10 insertions(+) diff --git a/content/academia/jenkins-warnings-ng-maintainer-spotlight.md b/content/academia/jenkins-warnings-ng-maintainer-spotlight.md index 2011aefd..d425ffe9 100644 --- a/content/academia/jenkins-warnings-ng-maintainer-spotlight.md +++ b/content/academia/jenkins-warnings-ng-maintainer-spotlight.md @@ -12,6 +12,7 @@ badges: ["Academic Maintainer", "Professor"] description: "A Jenkins plugin that automatically collects and visualizes warnings and errors from compilers and static analysis tools, supporting over 150 formats such as CheckStyle, SpotBugs, and StyleCop, with quality gates, trend charts, and Git forensic statistics." --- + ## What is the Jenkins Warnings plugin, and what does it help people do? The Jenkins Warnings Plugin is a Jenkins plugin that automatically collects and visualizes warnings and errors from compilers and static analysis tools — supporting over 150 formats such as CheckStyle, SpotBugs, and StyleCop. After each build, teams get a detailed report showing new, fixed, and outstanding issues, filterable by severity, category, package, or module, with annotated source code views and trend charts over time. Quality gates can be defined to fail a build automatically when issue thresholds are exceeded, keeping code quality under continuous control. @@ -24,10 +25,14 @@ The plugin's functionality is also available as standalone actions for GitHub an The project was initially created to visualise code quality within an industry team. It later expanded through community contributions and was adapted for teaching and grading purposes. +Photo_1 + ## How does this project connect to your academic work? It is used for grading student projects and teaching software engineering practices. +Photo_3 + ## Who contributes to the project? Besides me as the maintainer, students, members of the Jenkins community, and other contributors that use the plugin in their projects. @@ -40,6 +45,8 @@ Students contribute tests and features as part of their thesis work. Since they It is used in software engineering and testing courses. Students use the plugin to grade their projects and provide feedback on their code. +Photo_2 + ## What impact has this project had on your students? Student engagement increases, as their contributions become part of a real-world project. @@ -48,6 +55,7 @@ Student engagement increases, as their contributions become part of a real-world The plugin is used on approximately 10% of Jenkins instances worldwide. The GitHub companion is also used by many projects to monitor code quality and provide feedback on pull requests. + ## What does it take to maintain the project? Issues are opened by users. I prioritise the issues that I am going to implement based on severity, content and importance. @@ -68,6 +76,8 @@ I was a Jenkins governance board member over the past two years. I participate i The project has participated in Hacktoberfest and Google Summer of Code. +Photo_5 + ## What would you love to achieve by showcasing your project? To highlight the connection between industry and education. From 28c541d71a644e2b26b1d2c731311b1c8074a7c8 Mon Sep 17 00:00:00 2001 From: Ashley Nicolson Date: Tue, 5 May 2026 15:58:58 +0100 Subject: [PATCH 17/17] Add image to scikit-robot maintainer spotlight Added an image to enhance the visual appeal of the scikit-robot spotlight article and provide a better understanding of the project. --- content/academia/scikit-robot-maintainer-spotlight.md | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/content/academia/scikit-robot-maintainer-spotlight.md b/content/academia/scikit-robot-maintainer-spotlight.md index 4902e28b..30689495 100644 --- a/content/academia/scikit-robot-maintainer-spotlight.md +++ b/content/academia/scikit-robot-maintainer-spotlight.md @@ -16,12 +16,16 @@ description: "A lightweight, pure-Python library for robotic kinematics, motion Scikit-robot is a lightweight, pure-Python library for robotic kinematics, motion planning, visualization, and control. It is designed to make robotics more accessible by allowing users to easily simulate, control, and extend robots using Python. By lowering the barrier to entry, it helps students, researchers, and engineers quickly turn their ideas into working robotic systems without needing to deal with complex underlying implementations. Over the past year the library has grown to include a full-body inverse-kinematics solver that treats the floating base as a solved degree of freedom (via new PlanarJoint and FloatingJoint primitives), differentiable and batched kinematics implemented in JAX, ROS 2 robot interfaces (e.g., a parameterised PandaROS2RobotInterface for multi-arm setups), and humanoid models such as JAXON JVRC. This makes scikit-robot increasingly viable not only for educational use but also for whole-body humanoid and dual-arm research. +scikit-robot + + ## What inspired you to start this project? The story behind Scikit-robot began with a desire to make robotics more accessible and approachable. At the Information Systems Engineering Laboratory, we had long relied on EusLisp, a powerful robot programming language, but it had limitations such as integration challenges and less accessible documentation. During my time as a graduate student, I started thinking about how to preserve EusLisp's strengths while combining them with Python's simplicity and ecosystem. Inspired by tools like NumPy and Scikit-learn, I saw the need for a robotics library that was easy to start with and versatile in its applications. This led to the creation of Scikit-robot. + ## How does this project connect to your academic work? Scikit-robot is deeply connected to my academic work and originated from my graduate research at the Information Systems Engineering Laboratory. It became a core part of my efforts to lower the barriers to robot development.