federated-learning
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David Lazerson
David Lazerson is the co-founder and CEO of Briya, a healthcare technology company that connects hospitals, research institutions, and life sciences organizations so they can share de-identified, real-world patient data securely and in compliance with U.S. and European privacy rules. A physicist and cognitive scientist by training and a former Israeli military cyber operations officer, Lazerson built Briya on cryptography, federated learning, and zero-knowledge proofs, and in 2025 launched Briya AIRE, a clinical-grade AI research assistant that lets researchers ask questions in plain language instead of writing code.
Ajit Tharaken
Ajit Tharaken is the CEO of Consilient, a Washington, D.C. fintech building federated-learning AI to catch financial crime without ever moving a bank's data. A Columbia-trained computer scientist, he previously ran Opus Global (Alacra) through its sale to NICE Actimize, then led NICE Actimize's Data Intelligence business. He pitches a blunt thesis: the global anti-money-laundering system is outdated, and the fix is letting institutions train AI models locally and share the intelligence, not the data.
Vaikkunth Mugunthan
Vaikkunth Mugunthan is the co-founder and CEO of Dynamo AI, a San Francisco company that builds privacy, security, and compliance guardrails for enterprise generative AI. An MIT PhD in computer science with a Harvard minor in privacy, fairness, and law, he turned years of federated-learning and differential-privacy research into a venture-backed startup serving Fortune 500 firms in finance, insurance, electronics, and automotive. He was named to Forbes 30 Under 30 Asia 2025, captained MIT's cricket team, plays the violin, and has traveled to 16 countries.
Osman Mian
Osman Ali Mian is an early-career AI researcher specializing in causal discovery and trustworthy machine learning. He completed his PhD magna cum laude at CISPA Helmholtz Center for Information Security (Saarland University, Germany) and is now a postdoctoral researcher at the Institute for Artificial Intelligence in Medicine (IKIM) in Essen. He has published at top-tier venues including AAAI, ICML, AISTATS, and KDD, and won an Outstanding Paper Award at AAAI 2026 — marking him as a rising star in causal ML.
Dilawar Mahmood
Dilawar Mahmood is a machine learning engineer at ZeroEntropy (YC W25) in San Francisco, best known for four years at Apple where he optimized on-device models for Siri and Spotlight - work he once presented directly to Tim Cook at the Steve Jobs Theater. A Norwegian-educated engineer who left a comfortable career track to attend the Recurse Center and rediscover what programming actually feels like, he builds distributed ML frameworks in his spare time and is on record hating vibe coding.