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At ANRF AISEHack Phase 2 (IIT Delhi), my team Binary Bombers placed 2nd of 21 with a ConvLSTM + Fourier Neural Operator model that forecasts PM2.5 up to 16 hours ahead. At ANRF AISEHack 2.0 (GalaxEye) in Goa, Team Apes placed 3rd nationally, forecasting crop yield for 966 farm plots from six Capella X-band SAR scenes without any ground-truth labels.
On the generative-AI side I build agents and RAG applications: a LangGraph agent with human-in-the-loop and autonomous review modes, a multimodal RAG assistant for video and audio in English and Hinglish, and this portfolio's own grounded assistant and read-only MCP server. In classical ML and deep learning I have shipped explainable credit-risk scoring with XGBoost and SHAP, a graph neural network for research-topic classification, and a BiGRU emotion classifier.
I care about results that hold up: leakage-safe validation, honest baselines, and reporting what did not work alongside what did. I'm looking for AI/ML engineering internships and roles in machine learning, computer vision and remote sensing, or generative AI.