I build end-to-end AI systems—from raw data pipelines to production-ready ML models—across domains like Generative AI, Computer Vision, and NLP.
I combine deep research skills with scalable engineering to create impactful AI solutions.
- 🎓 M.S. Computer Science (AI) @ USC (Jan 2025 – Dec 2026)
- 💼 AI Engineer @ BlackBuckInsights | Former Data Scientist @ Koantek
- 🌱 Learning: LLM fine-tuning, RAG pipelines, AI inference optimization
- 📍 Los Angeles, CA
Languages:
Frameworks & Libraries:
MLflow, Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn
Cloud & Platforms:
GenAI & Tools:
Prompt Engineering, LoRA/QLoRA, PEFT, LangChain, ChromaDB, FAISS, Hugging Face, Docker
| Project | Description |
|---|---|
| Glaucoma Detection | 🩺 Semantic segmentation of optic disc/cup using U-Net variants; improved DICE score from 71% → 81% with CLAHE preprocessing |
| RAG Chatbot | 📄 Context-aware document QA from PDFs, SQL DBs & URLs using LangChain agents and LLaMA 3 |
| Supply Chain Chatbot | 🏭 Agentic workflow for dynamic SQL generation & decision-making |
| Recommendation Engine | 🛒 ALS + Apriori mining; boosted engagement 30%, AOV 15%, conversions 35% |
| Time Series Forecasting | 📈 SARIMAX & FBProphet for generator demand; MAPE 9.1%, Azure MLOps deployment |
| MRI Neural Synthesis | 🧠 CycleGAN to generate MRI contrasts; reduced cost & improved diagnosis speed |
- 🥇 Top 10 — Databricks Hackathon (LLM fine-tuning)
- 🥇 Data Science Innovators Award
- 📜 Databricks Certified Data Scientist
- 🥇 Gold Badge in Python & SQL (HackerRank)
