About
I'm an ML engineer and repeat founder who's spent the past five years deploying AI systems that reach millions, from a national disease surveillance pipeline scanning 400M+ media sources for India's NCDC, to a TB treatment adherence model flagging 100K+ high-risk patients across 15 states. I've published at ACL and NeurIPS, built products from zero to pilots, and I'm always looking for the next hard problem where ML can create genuine real-world impact.
Full experience →Projects
Products, research prototypes, and experiments.
A simulation platform that lets product teams test copy, features, and pricing against AI-generated customer personas, shipping decisions in minutes instead of weeks. Built on FastAPI, Postgres (pgvector), Redis, and Docker.
An adaptive assessment co-pilot targeting each student's mastery gaps in real time via an LLM judge loop over a skill graph. Field-piloted across after-school learning centers.
A peer-to-peer rental marketplace for high-value scuba gear across India's dive communities, validated via a no-code MVP using a landing page, WhatsApp coordination, and UPI payments.
Research
Peer-reviewed papers at top conferences, focused on AI for public health at national scale.
A national-scale, real-time, multi-stage and multi-lingual disease outbreak detection pipeline deployed with India's NCDC, scanning 400M+ media sources, issuing 100K+ alerts, and verifying 5K+ outbreaks through the Media Scanning and Verification Cell.
A similarity-encoded ensemble model deployed across 15 Indian states that flags high-risk TB patients likely to drop off treatment, covering 100K+ patients with fairness-aware reweighting to ensure equitable recall in underserved districts.
