Summary
Balagopal Unnikrishnan is a PhD candidate in Computer Science at the University of Toronto and a Vector and Schwartz Reisman Fellow with 7+ years in AI research and engineering focused on computer vision, NLP, and generative models. He builds end-to-end deep learning systems—data curation, algorithm design, deployment, and commercialization—and has a track record translating research into clinical tools that reduced pneumothorax triage turnaround by a median of 27 minutes. His thesis and publications (14+ papers, including Nature Digital Medicine) target shortcut learning and mitigation of spurious correlations in healthcare models, and he’s evaluated 13 mitigation algorithms at scale across 140K+ chest X-rays. Prior industry work at A*STAR/Institute for Infocomm Research produced commercialized algorithms and semi-supervised methods to cut annotation effort and address domain shift. He teaches foundational ML and AI-in-medicine courses, runs clinical deployment pipelines across imaging modalities, and combines rigorous evaluation metrics with practical system engineering to ensure research ships safely.
11 years of coding experience
2 years of employment as a software developer
AI Product Manager Nanodegree Program Artificial Intelligence, AI Product Manager Nanodegree Program Artificial Intelligence at Udacity
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of Toronto
Master's degree Intelligent Systems / Knowledge Engineering, Master's degree Intelligent Systems / Knowledge Engineering at National University of Singapore
High School Indian School Certificate (ISC), High School Indian School Certificate (ISC) at Loyola School Thiruvananthapuram
Bachelor of Technology (B.Tech.) Computer Science and Engineering, Bachelor of Technology (B.Tech.) Computer Science and Engineering at College of Engineering Trivandrum
English, Malayalam