About Me
CS undergrad specializing in AI/ML — focused on NLP, LLMs, and computer vision. I implement research papers from scratch and ship end-to-end ML systems: real-time inference pipelines, agentic AI apps, and full-stack GenAI products.
Skills & Technologies
Work Experience
AI/ML Research Intern
Engineered an end-to-end geospatial ML pipeline in Python predicting healthcare accessibility across Himachal Pradesh using real-world spatial datasets. Built and evaluated predictive models with Scikit-learn, transforming raw geospatial features into actionable public health insights.
Projects
Semantic Product Recommendation System
Built a production-grade RAG pipeline with sentence embeddings, LLM query expansion, and hybrid semantic-plus-engagement scoring for context-aware ranking. Engineered a Redis caching layer cutting end-to-end latency from 3–5s to sub-100ms.
CHINTU – Geopolitical Knowledge Graph
Built a full-stack intelligence system ingesting GDELT world events into a TigerGraph knowledge graph linked by causal influence edges. Used LLM intent extraction to route queries to whitelisted GSQL; rendered interactive D3 force-directed subgraphs in a Next.js frontend.
MindMirror – Cognitive Load Estimation
Built a real-time CV pipeline with MediaPipe and OpenCV extracting behavioral signals (eye tracking, blink rate, facial action units) on the AVCAffe dataset. Benchmarked XGBoost ensemble models with feature engineering; deployed full-stack with FastAPI for adaptive HCI research.
BlueSignal – AI Flood Crowdsourcing Platform
Built a real-time emergency platform using SSE for citizen-to-authority streaming, with CLIP-ViT image verification and DistilBERT report classification.
Education
B.Tech in Computer Science with AI & ML
Computer Science