#WordOfTheDay #IdiomOfTheDay #PhraseOfTheDay
When I make myself acquainted with new vocabulary I'll share here.
Personal account: @aumur.bsky.social
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.
Prof of machine learning at University of Helsinki. Interested in (differential) privacy and open source software.
Assistant professor at Georgia Tech in ISyE. I do mechanism design, differential privacy, fairness, and learning theory, mostly.
Postdoc @Penn; Ph.D. @Caltech; MSc @Columbia and @Supélec.
He/him.
🤖
new arXiv preprints mentioning "differential privacy" or "differentially private" in the title/abstract/metadata
- unrelated quantum/FL papers
+ updates from https://differentialprivacy.org
[Under construction.]
Algorithms, predictions, privacy.
https://theory.stanford.edu/~sergei/
Differential Privacy. Machine Learning. Apple.
Assistant Professor @Dept. Of Computer Science, University of Copenhagen, Ex Postdoc @MPI-IS, ETHZ, PhD @University of Oxford, B.Tech @CSE,IITK.
