https://www.philipamortila.com
CS PhD student at Princeton. https://www.cs.princeton.edu/~smalladi/index.html
RL Researcher | Postdoctoral Associate @mitidss
Interested in RL theory, stochastic optimisation and online learning.
https://muchay.github.io/
Director, Princeton Language and Intelligence. Professor of CS.
San Diego Dec 2-7, 25 and Mexico City Nov 30-Dec 5, 25. Comments to this account are not monitored. Please send feedback to townhall@neurips.cc.
Information and updates about RLC 2026 at Montreal, Quebec, Canada, from August 16 to 19.
https://rl-conference.cc
professor of EECS at MIT, currently visiting IAS. working in theoretical computer science namely algorithm design, complexity theory, circuit complexity, etc.
i'll let you know when P != NP is proved (and when it's not)
Advancing the frontiers of basic science through grantmaking, research and public engagement. Sign up for our newsletter: simonsfoundation.org/newsletter
The world's leading venue for collaborative research in theoretical computer science. Follow us at http://YouTube.com/SimonsInstitute.
Creator of All Thirty Two
Co-Host of the Bootleg Football Podcast.
https://www.youtube.com/c/brettkollmann
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
https://meliao.github.io/
George Lowther. Author of Almost Sure blog on maths, probability and stochastic calculus
https://almostsuremath.com
Also on YouTube: https://www.youtube.com/@almostsure
⛷️ ML Theorist carving equations and mountain trails | 🚴♂️ Biker, Climber, Adventurer | 🧠 Reinforcement Learning: Always seeking higher peaks, steeper walls and better policies.
https://ualberta.ca/~szepesva
https://willett.psd.uchicago.edu/
Worah Family Professor, University of Chicago
National Institute for Theory and Mathematics in Biology (https://www.nitmb.org/)
Institute for AI in the Sky (SkAI, https://skai-institute.org/)
faculty at UW CSE studying experimental design and reinforcement learning
AI research at Broad Institute and Boston University.
Reinforcement Learning / Bandits / Experiment Design
Mexicano 🇲🇽
A field-defining intellectual hub for data science and AI research, education, and outreach at the University of Chicago
https://datascience.uchicago.edu
https://audhuang.github.io/
Associate professor of @umdcs @umiacs @ml_umd at UMD. Researcher in #AI/#ML, AI #Alignment, #RLHF, #Trustworthy ML, #EthicalAI, AI #Democratization, AI for ALL.
Human-centered AI #HCAI, NLP & ML. Director TRAILS (Trustworthy AI in Law & Society) and AIM (AI Interdisciplinary Institute at Maryland). Formerly Microsoft Research NYC. Fun: 🧗🧑🍳🧘⛷️🏕️. he/him.
Secular Bayesian.
Professor of Machine Learning at Cambridge Computer Lab
Talent aficionado at http://airetreat.org
Alum of Twitter, Magic Pony and Balderton Capital
cs phd @upenn advised by Michael Kearns, Aaron Roth, and Duncan Watts| previously @stanford | she/her
https://psamathe50.github.io/sikatasengupta/
PhD at Machine Learning Department, Carnegie Mellon University | Interactive Decision Making | https://yudasong.github.io
Virtual seminar series featuring the latest advances in theoretical reinforcement learning. Seminars (approximately) every Tuesday at 6pm UTC.
> https://sites.google.com/corp/view/rltheoryseminars
Professor, Stanford University, Statistics and Mathematics. Opinions are my own.
PhD student | Interested in all things decision-making and learning
Associate Professor at Princeton
Machine Learning Researcher
Assistant Professor @UWaterloo Statistics and @VectorInst | Prev: Postdoc @Princeton PhD @UofTStatSci
https://mufan-li.github.io/
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/
Researcher @MSFTResearch; Prof @UWMadison (on leave); learning in context; thinking about reasoning; babas of Inez Lily.
https://papail.io
Chief AI Scientist at Databricks. Founding team at MosaicML. MIT/Princeton alum. Lottery ticket enthusiast. Working on data intelligence.
Associate Professor of Electrical Engineering, EPFL.
Amazon Scholar (AGI Foundations). IEEE Fellow. ELLIS Fellow.
kwang-sung jun. assistant professor at the u of arizona. ml, online learning, and bandits! i am a fan of regret minimalism, both in life and research.
Assistant Prof @ UC Riverside. Research on Efficient ML, RL, and LLMs. CS PhD @ UW Madison.
yinglunz.com
AI professor at Caltech. General Chair ICLR 2025.
http://www.yisongyue.com
Director of the Center for the Advancement of Progress
Anti-cynic. Towards a weirder future. Reinforcement Learning, Autonomous Vehicles, transportation systems, the works. Asst. Prof at NYU
https://emerge-lab.github.io
https://www.admonymous.co/eugenevinitsky
Blog: https://argmin.substack.com/
Webpage: https://people.eecs.berkeley.edu/~brecht/
web: http://maxim.ece.illinois.edu
substack: https://realizable.substack.com
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.
full-time ML theory nerd, part-time AI-non enthusiast
International Conference on Learning Representations https://iclr.cc/
Professor at Northwestern CS. Economics, by courtesy. Study mechanism design, economics of algorithms, regulation of algorithms, AI and society. https://sites.northwestern.edu/hartline/
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
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
doing a phd in RL/online learning on questions related to exploration and adaptivity
> https://antoine-moulin.github.io/
Professor at UT Nuremberg, Germany
I’m 🇫🇷 and I work on RL and lifelong learning. Mostly posting on ML related topics.
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!
CS PhD student at UPenn studying strategic human-AI interaction. On the job market! Nataliecollina.com
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
anmolkabra.com
ML PhD at @cornellbowers.bsky.social: LLM reasoning, agents, and AI for Science. Can cycle, run, juggle. Currently trying combinations.
Mathematics -- Statistics Theory (math.ST)
source: https://export.arxiv.org/rss/math.ST
maintainer: @tmaehara.bsky.social
Postdoc at UW CSE. Differential privacy, memorization in ML, and learning theory.
Associate Professor of Computer Science at Northeastern University in Boston. Dad. Imposter.
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
source: https://arxiv.org/rss/stat.ML
maintainer: @tmaehara.bsky.social
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/
Computer science professor at Carnegie Mellon. Researcher in machine learning. Algorithmic foundations of responsible AI (e.g., privacy, uncertainty quantification), interactive learning (e.g., imitation/reinforcement learning).
https://zstevenwu.com/
So far I have not found the science, but the numbers keep on circling me.
Views my own, unfortunately.
Señor swesearcher @ Google DeepMind, adjunct prof at Université de Montréal and Mila. Musician. From 🇪🇨 living in 🇨🇦.
https://psc-g.github.io/
UC Berkeley Professor working on AI. Co-Director: National AI Institute on the Foundations of Machine Learning (IFML). http://BespokeLabs.ai cofounder
Cofounder & CTO @ Abridge, Raj Reddy Associate Prof of ML @ CMU, occasional writer, relapsing 🎷, creator of d2l.ai & approximatelycorrect.com
Machine learning researcher. Professor in ML department at CMU.
Machine Learning Professor
https://cims.nyu.edu/~andrewgw
Assistant Prof at Penn CIS | Postdoc at Microsoft Research | PhD from UT Austin CS | Co-founder LeT-All
I work on AI at OpenAI.
Former VP AI and Distinguished Scientist at Microsoft.
Research scientist at OpenAI working on reasoning and RL. Previously PhD student at Stanford University working with Percy Liang and Tengyu Ma.
Professor of computer science at University of Copenhagen. Interested in random things & their application (especially to algorithms and privacy). rasmuspagh.net
Professor of Computer Science at Cambridge.
Professor and Department Chair of Electrical Engineering and Computer Sciences, UC Berkeley. Research Scientist (part-time) at Google. Founder, AddisCoder. 🇻🇮🇺🇸🇪🇹
Professor @UCLA, Research Scientist @ByteDance | Recent work: SPIN, SPPO, DPLM 1/2, GPM, MARS | Opinions are my own
Lecturer in Maths & Stats at Bristol. Interested in probabilistic + numerical computation, statistical modelling + inference. (he / him).
Homepage: https://sites.google.com/view/sp-monte-carlo
Seminar: https://sites.google.com/view/monte-carlo-semina
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
Senior Lecturer #USydCompSci at the University of Sydney. Postdocs IBM Research and Stanford; PhD at Columbia. Converts ☕ into puns: sometimes theorems. He/him.
