PhD student at the University of Pennsylvania. Prev, intern at MSR, currently at Meta FAIR. Interested in reliable and replicable reinforcement learning, robotics and knowledge discovery: https://marcelhussing.github.io/
All posts are my own.
Computer science, math, machine learning, (differential) privacy
Researcher at Google DeepMind
Kiwi🇳🇿 in California🇺🇸
http://stein.ke/
Professor at Penn, Amazon Scholar at AWS. Interested in machine learning, uncertainty quantification, game theory, privacy, fairness, and most of the intersections therein
cs phd @upenn advised by Michael Kearns, Aaron Roth, and Duncan Watts| previously @stanford | she/her
https://psamathe50.github.io/sikatasengupta/
Associate professor at U of Toronto. Computer science and math research: (differentially) private data analysis, geometry, discrepancy, optimization.
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.
Assistant prof at JHU CS. Interested in theory of ML, privacy, cryptography. All cat pictures my own and do not represent the cats of my employer
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
wharton stats phd — ml theory, ml for science
prev: comp neuro, data, physics
working with Edgar Dobriban and Konrad Körding
also some sports (esp. philly! go birds)
PhD student at University of Alberta. Interested in reinforcement learning, imitation learning, machine learning theory, and robotics
https://chanb.github.io/
CS PhD student at UPenn studying strategic human-AI interaction. On the job market! Nataliecollina.com
Machine Learning @ University of Edinburgh | AI4Science | optimization | numerics | networks | co-founder @ MiniML.ai | ftudisco.gitlab.io
Associate Professor at CS UWaterloo
Machine Learning
Lab: opallab.ca
PhD student at @cmurobotics.bsky.social working on efficient algorithms for interactive learning (e.g. imitation / RL / RLHF). no model is an island. prefers email. https://gokul.dev/. on the job market!
Professor at UT Nuremberg, Germany
I’m 🇫🇷 and I work on RL and lifelong learning. Mostly posting on ML related topics.
Organic machine turning tea into theorems ☕️
AI @ Microsoft Research ➡️ Goal: Teach models (and humans) to reason better
Let’s connect re: AI for social good, graphs & network dynamics, discrete math, logic 🧩, 🥾,🎨
Organizing for democracy.🗽
www.rlaw.me
doing a phd in RL/online learning on questions related to exploration and adaptivity
> https://antoine-moulin.github.io/
PI at Helmholtz AI, Faculty at TU Munich, Fellow at Zuse School for reliable AI, Branco Weiss Fellow, ELLIS Scholar.
Prev: Cambridge CBL, St John's College, ETH Zürich, Google Brain, Microsoft Research, Disney Research.
https://fortuin.github.io/
Associate professor in machine learning at the University of Amsterdam. Topics: (online) learning theory and the mathematics of explainable AI.
www.timvanerven.nl
Theory of Interpretable AI seminar: https://tverven.github.io/tiai-seminar
