Research
Published work
Peer-reviewed papers at top ML and NLP venues, focused on deploying AI for public health impact at national scale.
Health Sentinel: An AI Pipeline For Real-time Disease Outbreak Detection
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.
Read case study →Predicting Treatment Adherence of Tuberculosis Patients at Scale
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.
Read case study →Interests
What I work on
AI for Public Health
Building ML systems that improve healthcare delivery — from disease surveillance to treatment adherence prediction — at population scale.
Real-time NLP Pipelines
Multi-stage, multi-lingual NLP systems that process millions of documents to extract actionable intelligence in real time.
Fairness in ML
Ensuring equitable model performance across underserved populations through fairness-aware training and evaluation.