Scientific Software developer | Performance Optimizer | High-Performance Python Expert
I am a Computational Physicist specializing in building and optimizing high-throughput data pipelines for the analysis of astronomical data. I thrive at the intersection of heavy math, massive data, and performance engineering.
- Top 50 Contributor to PyCBC: I contribute production-level code to the primary software stack used by the global LIGO-Virgo-KAGRA collaboration for gravitational-wave detection.
- Creator of mfNRcatpy: A published Python package on PyPI for numerical relativity analysis, built with industry-standard packaging and documentation.
- Participated in optimizing pycbc_multi_inpiral identifying bottlenecks using profilers like cprof2dot and scalene. See PyGRB_performance repository.
- HPC Orchestrator: Expert in managing terabyte-scale workloads across thousands of CPU cores on international supercomputers (Galileo100).
- Languages: Python (Expert/Cython/Numba), C++ (Scientific), SQL, Bash.
- Computing: SLURM, HTCondor, MPI, Distributed Computing (Dask/Ray).
- Optimization: Performance Profiling, Memory Management, Vectorization.
- Data: Time-Series Analysis, Bayesian Inference, Signal Processing.
I am currently seeking Remote opportunities in Space-Tech, High-Performance Computing, or Quantitative Research where I can apply my experience in optimizing complex data systems to solve real-world engineering bottlenecks.
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