Paul Ungermann
@upicchini.bsky.social
Full Professor at @deptmathgothenburg.bsky.social | simulation-based inference | Bayes | stochastic dynamical systems | https://umbertopicchini.github.io/
@marcelhussing.bsky.social
PhD student at the University of Pennsylvania. Currently, intern at MSR. Interested in reliable and replicable reinforcement learning and using it for knowledge discovery: https://marcelhussing.github.io/ All posts are my own.
@stein.ke
Computer science, math, machine learning, (differential) privacy Researcher at Google DeepMind Kiwi🇳🇿 in California🇺🇸 http://stein.ke/
@aaroth.bsky.social
Professor at Penn, Amazon Scholar at AWS. Interested in machine learning, uncertainty quantification, game theory, privacy, fairness, and most of the intersections therein
@sikatasengupta.bsky.social
cs phd @upenn advised by Michael Kearns, Aaron Roth, and Duncan Watts| previously @stanford | she/her https://psamathe50.github.io/sikatasengupta/
@thesasho.bsky.social
Associate professor at U of Toronto. Computer science and math research: (differentially) private data analysis, geometry, discrepancy, optimization.
@thejonullman.bsky.social
Associate Professor of Computer Science at Northeastern University in Boston. Dad. Imposter.
@optimistsinc.bsky.social
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
@gautamkamath.com
Assistant Prof of CS at the University of Waterloo, Faculty and Canada CIFAR AI Chair at the Vector Institute. Joining NYU Courant in September 2025. Co-EiC of TMLR. My group is The Salon. Privacy, robustness, machine learning. http://www.gautamkamath.com
@chanpyb.bsky.social
PhD student at University of Alberta. Interested in reinforcement learning, imitation learning, machine learning theory, and robotics https://chanb.github.io/
@ncollina.bsky.social
Penn CS PhD student and IBM PhD Fellow studying strategic algorithmic interaction. Calibration, commitment, collusion, collaboration. She/her. Nataliecollina.com
@kfountou.bsky.social
Associate Professor at CS UWaterloo Machine Learning Lab: opallab.ca
@claireve.bsky.social
Group Leader in Tübingen, Germany I’m 🇫🇷 and I work on RL and lifelong learning. Mostly posting on ML related topics.
@rachel-law.bsky.social
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
@antoine-mln.bsky.social
doing a phd in RL/online learning on questions related to exploration and adaptivity > https://antoine-moulin.github.io/
@timvanerven.nl
Associate professor in machine learning at the University of Amsterdam. Topics: (online) learning theory and the mathematics of interpretable AI. www.timvanerven.nl Theory of Interpretable AI seminar: https://tverven.github.io/tiai-seminar
@amartyasanyal.bsky.social
Assistant Professor @Dept. Of Computer Science, University of Copenhagen, Ex Postdoc @MPI-IS, ETHZ, PhD @University of Oxford, B.Tech @CSE,IITK.
@bipr.bsky.social
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.
@gavin-brown.bsky.social
Postdoc at UW CSE. Differential privacy, memorization in ML, and learning theory.
@zstevenwu.bsky.social
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/
@gkdziugaite.bsky.social
Sr Research Scientist at Google DeepMind, Toronto. Member, Mila. Adjunct, McGill CS. PhD Machine Learning & MASt Applied Math (Cambridge), BSc Math (Warwick). gkdz.org
@djfoster.bsky.social
Principal Researcher in AI/ML/RL Theory @ Microsoft Research NE/NYC. Previously @ MIT, Cornell. http://dylanfoster.net RL Theory Lecture Notes: https://arxiv.org/abs/2312.16730
@carl-allen.bsky.social
Laplace Junior Chair, Machine Learning ENS Paris. (prev ETH Zurich, Edinburgh, Oxford..) Working on mathematical foundations/probabilistic interpretability of ML (what NNs learn🤷♂️, disentanglement🤔, king-man+woman=queen?👌…)
@idanattias.bsky.social
Postdoc researcher at IDEAL Institute in Chicago, hosted by UIC and TTIC. My research interests are in machine learning theory, data-driven sequential decision-making, and theoretical computer science. https://www.idanattias.com/
@quanquangu.bsky.social
Professor @UCLA, Research Scientist @ByteDance | Recent work: SPIN, SPPO, DPLM 1/2, GPM, MARS | Opinions are my own
@pontilgroup.bsky.social
Computational Statistics and Machine Learning (CSML) Lab | PI: Massimiliano Pontil | Webpage: csml.iit.it | Active research lines: Learning theory, ML for dynamical systems, ML for science, and optimization.
@erfunmirzaei.bsky.social
Researcher @PontilGroup.bsky.social| Ph.D. Student @ellis.eu, @Polytechnique, and @UniGenova. Interested in (deep) learning theory and others.
@mihainica.bsky.social
Mathematician working on probability and ML at U of Guelph in Canada. I also make math videos at https://youtube.com/@MihaiNicaMath
@cyroid.bsky.social
Researcher at Google. Improving LLM factuality, RAG and multimodal alignment and evaluation. San Diego. he/him ☀️🌱🧗🏻🏐 Prev UCSD, MSR, UW, UIUC.
@yulislavutsky.bsky.social
Stats Postdoc at Columbia, @bleilab.bsky.social Statistical ML, Generalization, Uncertainty, Empirical Bayes https://yulisl.github.io/
@mkearnsphilly.bsky.social
CS prof at Penn, Amazon Scholar in AWS. Interested in ML theory and related topics, as well as photography and Gilbert and Sullivan. Website: www.cis.upenn.edu/~mkearns
@yus167.bsky.social
PhD at Machine Learning Department, Carnegie Mellon University | Interactive Decision Making | https://yudasong.github.io
@sologen.bsky.social
Research Goal: Understanding the computational and statistical principles required to design AI/RL agents. Associate Professor at Polytechnique Montréal and Mila. 🇨🇦 academic.sologen.net
@miniapeur.bsky.social
Gradient surfer at UCL. FR, EN, also trying ES. 🇹🇼🇨🇦🇬🇳🇺🇸🇩🇴🇫🇷🇪🇸🇬🇧🇿🇦. Also on Twitter.
@krishnaswamylab.bsky.social
We develop AI methods for science, particularly deep learning methods based on data geometry, topology and dynamics systems.
@twkillian.bsky.social
Senior Research Scientist @MBZUAI. Focused on decision making under uncertainty, guided by practical problems in healthcare, reasoning, and biology.
@pseudomanifold.topology.rocks
Dad · Geometry ∩ Topology ∩ Machine Learning Professor at University of Fribourg While #geometry & #topology may not save the world, they may well save something that is homotopy-equivalent to it. 🏠 https://bastian.rieck.me/ 🏫 https://aidos.group
@aliciacurth.bsky.social
Machine Learner by day, 🦮 Statistician at ❤️ In search of statistical intuition for modern ML & simple explanations for complex things👀 Interested in the mysteries of modern ML, causality & all of stats. Opinions my own. https://aliciacurth.github.io
@pamattei.bsky.social
Research scientist, Inria. Statistical machine learning.
@guillemsimeon.bsky.social
(He/him) Physicist. Machine learning and atoms @ Microsoft Quantum. Barcelona. 🏳️🌈
@pierrealquier.bsky.social
Professor of Statistics @ ESSEC Business School Asia-Pacific campus Singapore 🇸🇬 https://pierrealquier.github.io/ Previously: RIKEN AIP 🇯🇵 ENSAE Paris 🇫🇷 🇪🇺 UCD Dublin 🇮🇪 🇪🇺 Random posts about stats/maths/ML/AI, poor jokes & birds photo 🌈
@martinvoegele.bsky.social
Computational Biophysicist, Amateur Photographer, History+Language Nerd. All views my own. Website: https://martinvoegele.github.io/
@marvinschmitt.bsky.social
🇪🇺 AI/ML, Member @ellis.eu 🤖 Generative NNs, ProbML, Uncertainty Quantification, Amortized Inference, Simulation Intelligence 🎓 PhD+MSc CS, MSc Psych 🏡 marvinschmitt.github.io ✨ On the job market, DMs open 📩
@clementinedomine.bsky.social
•PhD student @ https://www.ucl.ac.uk/gatsby 🧠💻 •Masters Theoretical Physics UoM|UCLA🪐 •Intern @zuckermanbrain.bsky.social| @SapienzaRoma | @CERN | @EPFL https://linktr.ee/Clementine_Domine
@yoshuabengio.bsky.social
Full professor at UdeM, Founder and Scientific Advisor at Mila - Quebec AI Institute, A.M. Turing Award Recipient. Working towards the safe development of AI for the benefit of all. Website and blog: https://yoshuabengio.org/
@richtarik.bsky.social
Professor of CS and Math @ KAUST. Interested in Optimization for Machine Learning. Federated learning guru. Likes 🏓🏋️♂️🎾🏐⛷️⛸️🧘♂️🤿🎹🎸✈️🏔️📷☀️🐈🍅🥚☕️
@mmbronstein.bsky.social
DeepMind Professor of AI @Oxford Scientific Director @Aithyra Chief Scientist @VantAI ML Lead @ProjectCETI geometric deep learning, graph neural networks, generative models, molecular design, proteins, bio AI, 🐎 🎶