Rahul Krishnan is an Assistant Professor at the University of Toronto and a Vector Institute member who applies principled machine learning to healthcare and computational biology problems. With 11 years of experience spanning academia and industry—including a PhD from MIT, a senior researcher role at Microsoft Research, and graduate work at NYU—he blends theoretical rigor with practical system-building. His research background includes inference algorithms for RNA folding and ML-driven solutions in medical imaging and pathology, reflecting a focus on learning methods that address real-world biomedical challenges. Comfortable moving between deep technical research and collaborative interdisciplinary teams, he brings both compiler- and systems-level experience from earlier industry roles. Based in Toronto, he combines a strong academic publication trajectory with hands-on algorithm development that targets translational impact.
11 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy (PhD), Machine Learning, Doctor of Philosophy (PhD), Machine Learning at Massachusetts Institute of Technology
Master of Science (M.S.), Computer Science, Master of Science (M.S.), Computer Science at New York University
BEng, Computer Engineering + PEY, BEng, Computer Engineering + PEY at University of Toronto
Indian Secondary Certificate (ISC), Indian Secondary Certificate (ISC) at The Cathedral and John Connon School
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