PhD student at the University of Pennsylvania. Prev, intern at MSR, and Meta FAIR. Interested in reliable and replicable reinforcement learning, robotics and knowledge discovery: https://marcelhussing.github.io/
All posts are my own.
cs phd @upenn advised by Michael Kearns, Aaron Roth, and Duncan Watts| previously @stanford | she/her
https://psamathe50.github.io/sikatasengupta/
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.
doing a phd in RL/online learning on questions related to exploration and adaptivity
> https://antoine-moulin.github.io/
Prof at TU Nuremberg, PI at Helmholtz AI, Fellow at Zuse School for reliable AI, Branco Weiss Fellow, ELLIS Scholar.
Prev: TUM, 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
Information theory, probability, statistics. Churchill Professor of Mathematics of Information @UofCambridge: dpmms.cam.ac.uk/person/ik355/ 🧮 #MathSky 🧪 #Science
[used to be @yiannis_entropy at the other place]
Assistant Professor @Dept. Of Computer Science, University of Copenhagen, Ex Postdoc @MPI-IS, ETHZ, PhD @University of Oxford, B.Tech @CSE,IITK.
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.
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/
Assistant Professor at BU CDS
EconCS | Theory of CS | MD+AI+DS4SG | MD4SG co-founder
Previously Columbia, UW, Oberlin. Views are mine alone.
www.kiragoldner.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 2026. Co-EiC of TMLR. My group is The Salon. Privacy, robustness, machine learning.
http://www.gautamkamath.com
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
CNRS researcher in linear programming
Theoretical Computer Science professor @ U. of Michigan-Ann Arbor.
Opinions are mine and may evolve over time.
repost ≠ endorsement.
Policy: I don't interact with anonymous profiles.
Join AAUP.
he/him/his.
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
Professor, Computer Science, New York University. Interested in Algorithms.
Senior Lecturer #USydCompSci at the University of Sydney. Postdocs IBM Research and Stanford; PhD at Columbia. Converts ☕ into puns: sometimes theorems. He/him.
Complexity, in all its forms.
Associate Professor of Computer Science at Columbia University.
http://www.henryyuen.net
Associate professor at U of Toronto. Computer science and math research: (differentially) private data analysis, geometry, discrepancy, optimization.
Professor at Northwestern CS. Economics, by courtesy. Study mechanism design, economics of algorithms, regulation of algorithms, AI and society. https://sites.northwestern.edu/hartline/
Associate Professor of Computer Science at Northeastern University in Boston. Dad. Imposter.
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)
Assistant Professor at the University of Michigan.
I design fast graph algorithms in dynamic/distributed/local settings.
https://sites.google.com/site/thsaranurak/
Computation & Complexity | AI Interpretability | Meta-theory | Computational Cognitive Science
https://fedeadolfi.github.io
On the job market!
Director, Center for Tech Responsibility@Brown. FAccT OG. AI Bill of Rights coauthor. Former tech advisor to President Biden @WHOSTP. He/him/his. Posts my own.
Mathematician and Theoretical Computer Scientist (#mathematics, #TCS) interested in #Consciousness and #NeuroAI (#Neuroscience, #AI). Distinguished Career Prof of CS at CMU, Emerita. President, Assoc for MathConscSci (AMCS) (https://amcs-community.org)
PhD student at TCS BU.
Interested in sublinear algorithms and quantum.
On the job market!
Professor, Stanford University, Statistics and Mathematics. Opinions are my own.
Postdoctoral Research Scientist @Columbia. Previously postdoc @BU_CDS @TelAvivUni and PhD @Princeton.
https://www.divyarthimohan.com
Associate professor of Computer Science at Drexel University. Interested in mechanism design, game theory, algorithms, fair division.
https://www.cs.drexel.edu/~gkatz/
CS professor at UW, research focus in theory of ML, fairness, and econCS
Assistant professor at UMich. I do theoretical computer science and graph theory.
Theoretical Computer Science @ EPFL
Faculty at the University of Colorado. Interested in theoretical computer science, and especially lattices. Also: mountains, running, music.
https://home.cs.colorado.edu/~hbennett/
Official account for the 2026 IEEE Symposium on Foundations of Computer Science (FOCS), to be held in New York, USA, Nov 8–11, 2026.
🔗 https://focs.computer.org/
Faculty @ Harvard Econ + Harvard Computer Science, past: MSR HebrewU, classical (opera) singer, father of two (+a pug) | tweets my own, repost≠endorse
https://yannai.gonch.name/
Assistant Professor at Stanford
Machine learning, algorithm design, econ-CS
https://vitercik.github.io/
Professor and Head of Algorithms, Data Structures and Foundations of Machine Learning at Computer Science, Aarhus University
Postdoc at UW CSE. Differential privacy, memorization in ML, and learning theory.
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
Professor of Computer Science, @TelAvivUni | @ACM SIGECOM Chair | Research areas: Econ&CS, Algorithmic Game Theory, Market Design
🇨🇦 Theoretical computer scientist. Assistant professor at @stfx-university.bsky.social. Website: taylorjsmith.xyz.
Professor of Computer Science at Cambridge.
Associate Professor, Department of Computer Science, Johns Hopkins University.
https://www.cs.jhu.edu/~mdinitz/
JAX & Flax @ GoogleDeepmind
Gemini, neural net frameworks & performance
video games, and other random things
she/her, wife of a wife 🌈
Research Scientist, Google DeepMind / Ex-academic / Deep learning to help people write code / ❤️s:🐱🐶☕️🍕
Research Scientist at DeepMind. Opinions my own. Inventor of GANs. Lead author of http://www.deeplearningbook.org . Founding chairman of www.publichealthactionnetwork.org
Neuro + AI Research Scientist at DeepMind; Affiliate Professor at Columbia Center for Theoretical Neuroscience.
Likes studying learning+memory, hippocampi, and other things brains have and do, too.
she/her.
Developing AI responsibly.
Senior Staff Research Scientist at Google DeepMind. Opinions are my own.
ML, history, coding, space, science and everything in between. Personal profile. Research Eng @ DeepMind (Google). Views my own, etc.
Senior Research Scientist at Google DeepMind.
🌐 jasmijn.bastings.me
Researching planning, reasoning, and RL in LLMs @ Reflection AI. Previously: Google DeepMind, UC Berkeley, MIT. I post about: AI 🤖, flowers 🌷, parenting 👶, public transit 🚆. She/her.
http://www.jesshamrick.com
stealth // Gemini RL+inference @ Google DeepMind // Conversational AI @ Meta // RL Agents @ EA // ML+Information Theory @ MIT+Harvard+Duke // Georgia Tech PhD
📍{NYC, SFO, YYZ}
🔗 https://beirami.github.io/
Jack of all trades, master of some
•ⒶⒾ@DeepMind
•Personal account
•Mostly AI/ML/CS/biotech/physics/math/complexity/art/animals
•They/Any
•⚛️🏳️🌈🇬🇧🇨🇦🇺🇸🇪🇺
CS prof at University of Waterloo and Research Scientist at Google DeepMind.
Research Scientist @ Google Deepmind. Opinions are my own.
minsukchang.com
RL researcher at DeepMind
https://schaul.site44.com/ 🇱🇺
Research Scientist at Google DeepMind
Blog: https://sander.ai/
🐦: https://x.com/sedielem
Research Scientist at Google DeepMind (WaveNet, Imagen 3, Veo, ...). I tweet about deep learning (research + software), music, generative models (personal account).
I can be described as a multi-agent artificial general intelligence.
www.jzleibo.com
Research Engineer at Google DeepMind. AlphaFold, LLMs, Physics and Civic Tech. tfgg.me
Research scientist at NVIDIA. Learned physics models, generative video & more.
RS at Google DeepMind and Honorary Lecturer at UCL. Building general world models to solve AGI :)
Research Scientist @ Google DeepMind. Previously Meta (FAIR), Reddit, PhD UCL, MSc Oxford. samvelyan.com
Research Scientist @DeepMind | Previously @OSFellows & @hrdag. RT != endorsements. Opinions Mine. Pronouns: he/him
distributed (diloco) + modularity (dipaco) + llm @ deepmind | continual learning phd @ sorbonne
Research Scientist @ Google DeepMind. Previously @ OpenAI. Building AGI. 🤖
Research scientist at Google Deepmind, Gemini Pretraining. Birds, poetry, games, robots
📍London 🔗 edouardleurent.com
Assistant Professor at UW and Staff Research Scientist at Google DeepMind. Social Reinforcement Learning in multi-agent and human-AI interactions. PhD from MIT. Check out https://socialrl.cs.washington.edu/ and https://natashajaques.ai/.
AI, sociotechnical systems, social purpose. Research director at Google DeepMind. Cofounder and Chair at Deep Learning Indaba. FAccT2025 co-program chair. shakirm.com
Senior Research Scientist at Google DeepMind. AGI Alignment researcher. Views my dog's.
RL & Meta-Learning @ DeepMind.
Research Director @GoogleDeepMind. Co-lead of Veo, working on generative models of video and their fun applications.
Señor swesearcher @ Google DeepMind, adjunct prof at Université de Montréal and Mila. Musician. From 🇪🇨 living in 🇨🇦.
https://psc-g.github.io/
Research Scientist@Google DeepMind
Assoc Prof@York University, Toronto
mbrubake.github.io
Research: Computer Vision and Machine Learning, esp generative models.
Applications: CryoEM (cryoSPARC), Statistics (Stan), Forensics, and more
Researcher at Google DeepMind. Previously Arnold group at Caltech. Making useful molecules!
Scientist @ Google DeepMind
Research Scientist at Google DeepMind. Mostly work on ML, NLP, and BioML. Based in Seattle.
http://ptshaw.com
large language modeler (gemini, long context, RL, gemma) @ google deepmind
