Mathematician at UCLA. My primary social media account is https://mathstodon.xyz/@tao . I also have a blog at https://terrytao.wordpress.com/ and a home page at https://www.math.ucla.edu/~tao/
Professor of Statistics at University of Warwick; computational methods, Monte Carlo, gradient flows and fun things like those.
Ph.D. student in Machine Learning and Domain Adaptation for Neuroscience at Inria Saclay/ Mind.
Website: https://tgnassou.github.io/
Skada: https://scikit-adaptation.github.io/
Doing mathematics, also as a job. Now at Uni Bremen, was at TU Braunschweig. Only here for the math. Optimization, inverse problems, imaging, learning - stuff like that.
Research scientist at Apple | machine learning, optimization, language modeling
pierreablin.com
Machine learning researcher @Stanford. https://petersen.ai/
ELLIS PhD student @HelmholtzMunich, Student Researcher @Apple. Interested in ML, Single-Cell Genomics, and People.
TMLR Homepage: https://jmlr.org/tmlr/
TMLR Infinite Conference: https://tmlr.infinite-conf.org/
Google Chief Scientist, Gemini Lead. Opinions stated here are my own, not those of Google. Gemini, TensorFlow, MapReduce, Bigtable, Spanner, ML things, ...
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
Professor at Penn, Amazon Scholar at AWS. Interested in machine learning, uncertainty quantification, game theory, privacy, fairness, and most of the intersections therein
Computer science, math, machine learning, (differential) privacy
Researcher at Google DeepMind
Kiwi🇳🇿 in California🇺🇸
http://stein.ke/
Associate Professor of Computer Science at Northeastern University in Boston. Dad. Imposter.
Senior Lecturer #USydCompSci at the University of Sydney. Postdocs IBM Research and Stanford; PhD at Columbia. Converts ☕ into puns: sometimes theorems. He/him.
Associate professor at U of Toronto. Computer science and math research: (differentially) private data analysis, geometry, discrepancy, optimization.
Computer science professor at Carnegie Mellon. Researcher in machine learning. Algorithmic foundations of responsible AI (e.g., privacy, uncertainty quantification), interactive learning (e.g., RLHF).
https://zstevenwu.com/
Assistant Professor of Computer Science at the University of Virginia. I work on Responsible AI (differential privacy & fairness) and machine learning for science and engineering (differentiable optimization) | http://nandofioretto.github.io
Professor of computer science at Boston University. Not related to any economists, living or dead, as far as I know.
ML & Privacy Prof at the University of Melbourne, Australia. Deputy Dean Research. Prev Microsoft Research, Berkeley EECS PhD. @bipr on the X bird site. He/him.
