AI Engineer • Full-Stack Developer • Problem Solver

Full-Stack Predictive Dashboard for Explainable Risk Modeling

• Meta-Dynamic Ensemble: Engineered a hybrid model fusing XGBoost (spatial severity) and LSTM (temporal volume) forecasting across 20,000+ national records.
• Explainable AI (XAI): Integrated an interpretable logic layer to surface primary risk drivers, ensuring transparency for tactical decision-making.
• Conversational Intelligence: Built a RAG-powered assistant using Gemma 3 and ChromaDB for natural language interrogation of vectorized datasets.
• Stack: FastAPI, Next.js 14, TensorFlow, XGBoost, Leaflet.js.

• Architecture: Hybrid RAG merging FAISS Vector Search with live Web Search.
• Engineering: Built a non-blocking pipeline using Celery & Redis for async PDF processing.
• UI/UX: Custom PDF Viewer with bi-directional interactive citations and dynamic model switching (Gemini Flash/Pro).

Research Internship

• Multimodal AI: Fine-tuned LLaVA for technical multimodal tasks, improving accuracy in processing airworthiness and defense document intelligence.
• Scalable R&D: Authored deployment-ready documentation and optimized pipelines for high-security, defense-grade datasets.

• AI/ML: PyTorch, TensorFlow, XGBoost, Scikit-learn, LangChain, HuggingFace.
• Backend: Python, FastAPI, Flask, PostgreSQL, Redis, Celery, Docker.
• Frontend: Next.js, React, Tailwind CSS, Recharts, Leaflet.js.
• Databases: SQL, ChromaDB, FAISS.

Building things that make people’s lives easier — one project at a time.