Senior Lecturer #USydCompSci at the University of Sydney. Postdocs IBM Research and Stanford; PhD at Columbia. Converts ☕ into puns: sometimes theorems. He/him.

Professor at Penn, Amazon Scholar at AWS. Interested in machine learning, uncertainty quantification, game theory, privacy, fairness, and most of the intersections therein

Assistant Prof of CS at the University of Waterloo, Faculty and Canada CIFAR AI Chair at the Vector Institute. Joining NYU Courant in September 2026. Co-EiC of TMLR. My group is The Salon. Privacy, robustness, machine learning. http://www.gautamkamath.com

OpenAI and MIT faculty (on leave)

Assistant Prof at Columbia || Studying data science and its interactions with human behavior || Applications in education, healthcare, and online platforms. https://hannahql.github.io/

Assistant Professor at Stanford Machine learning, algorithm design, econ-CS https://vitercik.github.io/

Professor and Head of Machine Learning Department at Carnegie Mellon. Board member OpenAI. Chief Technical Advisor Gray Swan AI. Chief Expert Bosch Research.

machine learning research

I study algorithms/learning/data applied to democracy/markets/society. Asst. professor at Cornell Tech. https://gargnikhil.com/. Helping building personalized Bluesky research feed: https://bsky.app/profile/paper-feed.bsky.social/feed/preprintdigest

Assistant Prof at Penn CIS | Postdoc at Microsoft Research | PhD from UT Austin CS | Co-founder LeT-All

Statistics professor at the University of Illinois Urbana-Champaign. I do high-dimensional statistics, network analysis, some optimization, and matrix analysis Postdoc @ Penn, PhD @ Johns Hopkins I also love running

CMU postdoc, previously MIT PhD. Causality, pragmatism, representation learning, and AI for biology / science more broadly. Proud rat dad.

Research Director, Founding Faculty, Canada CIFAR AI Chair @VectorInst. Full Prof @UofT - Statistics and Computer Sci. (x-appt) danroy.org I study assumption-free prediction and decision making under uncertainty, with inference emerging from optimality.

CS PhD Student @ MIT, interested in safe and reliable machine learning.

I like to talk about ML & 3D. University of Tokyo alumni. Previously: Virginia Tech, Stanford Biodesign. Visiting Fellow @ MSR Big Data

I work on AI at OpenAI. Former VP AI and Distinguished Scientist at Microsoft.

Assistant professor of CS at UC Berkeley, core faculty in Computational Precision Health. Developing ML methods to study health and inequality. "On the whole, though, I take the side of amazement." https://people.eecs.berkeley.edu/~emmapierson/

Cofounder & CTO @ Abridge, Raj Reddy Associate Prof of ML @ CMU, occasional writer, relapsing 🎷, creator of d2l.ai & approximatelycorrect.com

Machine Learning | Stein Fellow @ Stanford Stats (current) | Assistant Prof @ CMU (incoming) | PhD @ MIT (prev) https://andrewilyas.com