Summary
Ankit Vani is a machine learning researcher with 13 years of experience focused on representation learning, semantic understanding, and methods for systematic reasoning using dynamic memory and unbounded computation. He completed a PhD track at Mila where his work centered on enabling models to reason about the world, and has research stints at Meta FAIR, ServiceNow, and industry roles applying ML to satellite imagery and NLP. Recently joining RBC Borealis, he is exploring representation learning and the dynamics of sharpness-aware optimization beyond mere loss-surface smoothing. His projects bridge theory and practice, spanning in-context compositionality studies, self-supervised model structure emergence, and applied tasks like detection and segmentation. Based in Boston, he combines deep academic training with hands-on industry research, often probing why learning algorithms generalize rather than just how to make them fit. Ankit’s profile reflects a consistent curiosity about the computational principles of intelligence, not just model performance metrics.
13 years of coding experience
9 years of employment as a software developer
High School, High School at New Era Senior Secondary School
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Université de Montréal
Master of Science - MS Computer Science, Master of Science - MS Computer Science at New York University
Bachelor of Engineering - BE Computer Engineering, Bachelor of Engineering - BE Computer Engineering at Savitribai Phule Pune University