Summary
Ronak Mehta is a Co-Founder and research scientist focused on provable and guaranteed-safe AI, combining 11 years of experience spanning PhD-level ML research and applied engineering. His dissertation work developed scalable methods for identifying influential features, parameters, and samples—an approach he now applies to interpretability, alignment, and safety tooling. He has built memory-augmented and editable ML systems in industry (Orca DB) and is accelerating alignment research through Coordinal Research and the ML Alignment & Theory Scholars program. Comfortable moving between theory and production, he has a track record of turning statistical ML and fairness research into practical tools and automated research systems. Based in San Francisco with deep academic roots from the University of Wisconsin–Madison, he’s currently shipping projects in provable-safe AI that aim to make alignment research faster and more reliable.
11 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Computer Science, Doctor of Philosophy (Ph.D.) Computer Science at University of Wisconsin-Madison
Bachelor of Engineering (B.Eng.) Computer Engineering, Bachelor of Engineering (B.Eng.) Computer Engineering at University of Michigan
English, Spanish, Gujarati, Hindi