Graduate Researcher - UConn MINDS Lab
(2026-05)
Multimodal LLM-Based Dietary Recommendation System
- Built Python ETL pipelines to clean, merge and structure 2021-2023 NHANES and USDA FNDDS datasets for downstream modeling
- Designed a multimodal recommendation workflow combining structured health & nutrition data, text inputs, and food-image
- Implemented FAISS-based semantic search to retrieve food-nutrition records for personalized recommendation generation
- Compared LLM-only, RAG, and rule-guided RAG pipelines to evaluate recommendation safety, personalization, and guideline alignment
- Integrated LLaMA Vision outputs with FNDDS food records to support image-based dietary recommendation workflows
Research Assistant - Indian Association for the Cultivation of Science, Kolkata - Kolkata, India
(2022-08 - 2025-08)
- Collected, cleaned, and organized PPMS and MPMS datasets using Excel and Pandas for research analysis
- Analyzed magnetic, thermal, and transport data in Python to identify trends, anomalies and material-property
- Applied linear, nonlinear regression and spline fitting to quantify temperature and field-dependent trends
- Transformed raw instrument output into derived variables for statistical analysis, visualization, and modeling
- Reviewed scientific literature to develop hypotheses, plan experiments and write technical summaries
