I study algorithms/learning/data applied to democracy/markets/society. Asst. professor at Cornell Tech. https://gargnikhil.com/. Helping building personalized Bluesky research feed: https://bsky.app/profile/paper-feed.bsky.social/feed/preprintdigest
#RobotLearning Professor (#MachineLearning #Robotics) at @ias-tudarmstadt.bsky.social of
@tuda.bsky.social @dfki.bsky.social @hessianai.bsky.social
The world's leading venue for collaborative research in theoretical computer science. Follow us at http://YouTube.com/SimonsInstitute.
NeuroAI PhD Candidate at McGill / Mila.
Loves: 🧠 🏕️ 🏔️ 🏊🏻♂️ 🚴🏻♂️ 🏃🏻♂️ 🎨📚☕
https://raymondchua.github.io
Postdoctoral fellow @ University of Oslo (back home in 🏔️🇳🇴🏔️), Bayesian stats (high-dimensional, nonparametric, ML), biostatistics, computation. Previously @ MRC Biostatistics Unit, University of Cambridge 🇬🇧
Neural network interested in statistics, physics, and computing. Mostly network science. Asst prof @ Cambridge
Curious.
Researching #MachineLearning for Scientific Discovery. #ml4science #ai4science
I choose #OpenSource and #OpenScience .
Solving problems in #LifeScience #Genomics #RadioAstronomy
Read Mathematics for Machine Learning at https://mml-book.com
⛷️ 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
Researcher in machine learning
research scientist at google deepmind.
phd in neural nonsense from stanford.
poolio.github.io
Senior Staff Research Scientist @Google DeepMind, former Chair Prof @Oxford Uni
AI, philosophy, spirituality
Head of interpretability research at EleutherAI, but posts are my own views, not Eleuther’s.
how shall we live together?
societal impacts researcher at Anthropic
saffronhuang.com
Senior Principal Researcher @MSRCambridge. Working on reasoning in language models.
Machine learning & statistics researcher @ Flatiron Institute. Posts on probabilistic ML, Bayesian statistics, decision making, and AI/ML for science.
www.dianacai.com
Professor for CS at the Tuebingen AI Center and affiliated Professor at MIT-IBM Watson AI lab - Multimodal learning and video understanding - GC for ICCV 2025 - https://hildekuehne.github.io/
Researcher in Neuroscience & AI
CNRS, Ecole Normale Supérieure, PSL
currently detached to Meta
postdoc @oxfordstatistics.bsky.social working on (robust) LMs for @naturerecovery.bsky.social 🌱
prev PhD student @clopathlab.bsky.social 🧠 & AI resident @ Google X 🤖
Host @ ThursdAI.news pod
AI Evangelist @ Weights & Biases
CEO @ Targum.Video
Opinions my own
Associate Prof. in ML & Statistics at NUS 🇸🇬
MonteCarlo methods, probabilistic models, Inverse Problems, Optimization
https://alexxthiery.github.io/
PhD supervised by Tim Rocktäschel and Ed Grefenstette, part time at Cohere. Language and LLMs. Spent time at FAIR, Google, and NYU (with Brenden Lake). She/her.
Assistant Professor of Machine Learning
Generative AI, Uncertainty Quantification, AI4Science
Amsterdam Machine Learning Lab, University of Amsterdam
https://naesseth.github.io
messing up with gaussians
🎓 CS Prof at UCLA
🧠 Researching reasoning and learning in artificial intelligence: tactable deep generative models, probabilistic circuits, probabilistic programming, neurosymbolic AI
https://web.cs.ucla.edu/~guyvdb/
EEML Organizer, ML researcher
Assistant Professor in Natural Language Processing (NLP) at the University of Warwick, UK.
Personal Webpage: https://warwick.ac.uk/fac/sci/dcs/people/u1898418/
Prof (CS @Stanford), Co-Director @StanfordHAI, Cofounder/CEO @theworldlabs, CoFounder @ai4allorg #AI #computervision #robotics #AI-healthcare
Anthropologist - Bayesian modeling - science reform - cat and cooking content too - Director @ MPI for evolutionary anthropology https://www.eva.mpg.de/ecology/staff/richard-mcelreath/
Lecturer at the University of Bristol.
probabilistic ML, optimisation, interpretability, LLM evals.
Researcher in machine learning and optimization. Open source enthusiast. Parody songwriter (aka PianoHamster). OCD survivor.
Professor at UW; Researcher at Meta. LMs, NLP, ML. PNW life.
At Microsoft Research. Lead of https://aka.ms/game-intelligence - we drive innovation in machine learning with applications in games. https://iclr.cc Board.
AGI safety researcher at Google DeepMind, leading causalincentives.com
Personal website: tomeveritt.se
Machine learning, environmental modeling, sustainability, robotics
Professor @UCL
He/him
Machine Learning Professor
https://cims.nyu.edu/~andrewgw
Associate Professor at MIT EECS, LIDS.
Science at Google DeepMind. AlphaQubit. Ex-BenevolentAI. Opinions are my own.
Assistant Professor at the university of Warwick.
I compute integrals for a living.
https://adriencorenflos.github.io/
Professor of CS and Math @ KAUST. Interested in Optimization for Machine Learning. Federated learning guru. Likes 🏓🏋️♂️🎾🏐⛷️⛸️🧘♂️🤿🎹🎸✈️🏔️📷☀️🐈🍅🥚☕️
MIT PhD Student - ML for biomolecules - https://hannes-stark.com/
PhD researcher, building infrastructure (and pokemon) for Bayesian workflows, simulating everything.
Music, cooking, exercise enthusiast. http://fediscience.org/@scholzmx
Building tools for AI datasets. 😽
Looking in AI datasets. 🙀
Sharing clean open AI datasets. 😻
at https://bsky.app/profile/hf.co
Professor of Natural and Artificial Intelligence @Stanford. Safety and alignment @GoogleDeepMind.
Foundational Research Lead @ Thomson Reuters | Advisor @ UK AISI | ex- Fellow @ Harvard, ex- Senior RS @ GoogleDeepMind | PhD @ UCL / Gatsby Unit 🇬🇧🇩🇪🇺🇲🇭🇰
https://jonathan-schwarz.github.io/
Robotics and Reinforcement Learning tinkerer.
brandonrohrer.com
Wrangler of algorithms for Confluence @ Atlassian.
Eater of bread. Sipper of whisky.
Reports to a Shih Tzu.
Assistant Professor of Statistics & Data Science at UChicago
Topics: data-intensive social science, Bayesian statistics, causal inference, probabilistic ML
Proud “golden retriever” 🦮
Researcher @MSFTResearch; Prof @UWMadison (on leave); learning in context; thinking about reasoning; babas of Inez Lily.
https://papail.io
AI, sociotechnical systems, social purpose. Research director at Google DeepMind. Cofounder and Chair at Deep Learning Indaba. FAccT2025 co-program chair. shakirm.com
Professor, Computer Science, University of British Columbia. CIFAR AI Chair, Vector Institute. Senior Advisor, DeepMind. ML, AI, deep RL, deep learning, AI-Generating Algorithms (AI-GAs), open-endedness.
AI in Bio & Health & Therapeutic Development
Bio: https://linktr.ee/mnarayan
Substack: https://blog.neurostats.org
Peek into my brain: notes.manjarinarayan.org
Previously @dynotx @StanfordMed PhD@RiceU_ECE | BS@ECEILLINOIS
🧪🧮⚕️🧬🧠🖥🤖📈✍️🩺👩📈📉
Distinguished Scientist at Google. Computational Imaging, Machine Learning, and Vision. Posts are personal opinions. May change or disappear over time.
http://milanfar.org
Founding list[float] engineer. Recsys. Personalization. Infra. Systems. Normcore code. Nutella. Vectors. Words. Vibes. Bad puns (soon).
https://vickiboykis.com/what_are_embeddings/
Senior Lecturer in Computer Science, University of Galway, Ireland. I'd rather write programs that write programs than write programs.
AI accountability, audits & eval. Keen on participation & practical outcomes. CS PhDing @UCBerkeley.
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.
https://www.vita-group.space/ 👨🏫 UT Austin ML Professor (on leave)
https://www.xtxmarkets.com/ 🏦 XTX Markets Research Director (NYC AI Lab)
Superpower is trying everything 🪅
Newest focus: training next-generation super intelligence - Preview above 👶
(ML ∪ Bayesian optimization ∪ active learning) ∩ (drug discovery)
Researcher @valenceai.bsky.social
Details: austintripp.ca
Assistant Prof @ImperialCollege. Applied Bayesian inference, spatial stats and deep generative models for epidemiology. Passionate about probabilistic programming: check out my evolving #Numpyro course: https://elizavetasemenova.github.io/prob-epi 🚀
Secular Bayesian.
Professor of Machine Learning at Cambridge Computer Lab
Talent aficionado at http://airetreat.org
Alum of Twitter, Magic Pony and Balderton Capital
Assoc. Prof. of Machine & Human Intelligence | Univ. Helsinki & Finnish Centre for AI (FCAI) | Bayesian ML & probabilistic modeling | https://lacerbi.github.io/
🇮🇹 ProbAI Research Fellow @warwickstats.bsky.social. Previously @ellis.eu Stats PhD @edinunimaths.bsky.social @aalto.fi. 🤔💭 about Monte Carlo, approximate inference, UQ
Senior Research Scientist at Valence Labs. Generative modeling (causal, multimodal) and generalisation for scientific discovery.
PhD in ML from UofEdinburgh and MPI-IS, with time at Google DeepMind, Meta AI and Spotify.
📍London 🔗 cianeastwood.github.io
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
Microsoft Research AI for Science, previously physics @ Cambridge. views my own
Research scientist @NVIDIA | PhD in machine learning @UofT. Previously @Google / @MetaAI. Opinions are my own. 🤖 💻 ☕️
Researching reasoning at OpenAI | Co-created Libratus/Pluribus superhuman poker AIs, CICERO Diplomacy AI, and OpenAI o-series / 🍓
Post-doc @ Harvard. PhD UMich. Spent time at FAIR and MSR. ML/NLP/Interpretability
Mechanistic interpretability
Creator of https://github.com/amakelov/mandala
prev. Harvard/MIT
machine learning, theoretical computer science, competition math.
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?👌…)
Postdoc at the University of Edinburgh working on Machine Learning. Previously in Saarbrücken, Tübingen, and Murcia.
🌐 adrianjav.github.io
Machine Learning researcher at @Xaira_Thera (former @CambridgeEllis and @OxCSML) opinions expressed are my own.
The AI community building the future!
Building robust LLMs @Cohere
I try to put straight lines through things but usually fail. Try to be Bayesian when I can. Views my own. RT/like != endorsement.
Mathematician, writer, Orioles fan, Wisconsinite, cargo shorts dad
human being | assoc prof in #ML #AI #Edinburgh | PI of #APRIL | #reliable #probabilistic #models #tractable #generative #neuro #symbolic | heretical empiricist | he/him
👉 https://april-tools.github.io
Research Engineer at Google DeepMind
A special snowflake existing in 196883 dimensions
#ActuallyAutistic He/Him
Principal scientist @ TII
Visit my research blog at https://alexshtf.github.io
Econ prof at Oxford.
Machine learning, politics, econometrics, inequality, random reading recs.
maxkasy.github.io/home/
Academy Research Fellow at the Dept. of Computer Science, Aalto University, Finland. Affiliated with the Finnish Center for Artificial Intelligence.
Website: http://bharti-ayush.github.io
Señor swesearcher @ Google DeepMind, adjunct prof at Université de Montréal and Mila. Musician. From 🇪🇨 living in 🇨🇦.
https://psc-g.github.io/
Multiplying matrices @Cambridge_Uni & @MSFTResearch | PhD student in Machine Learning | Previously MSc @ucl & BSc @ucddublin
alanjeffares.com
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
Machine learning researcher, working on causal inference and healthcare applications
NO KINGS
“Overly optimistic” 🦮 in Statistics.
Listening in statistics.
Statistics Professor at UW Madison.
theoretical neuro, vision, ml. phding @ uc berkeley. music, muay thai.
neural computation: https://www.dissonances.blog/p/neural-computation
writes citationneeded.news • runs @web3isgoinggreat.com and @followthecrypto.org • tech researcher and cryptocurrency industry critic • software engineer • wikipedian
support my work: citationneeded.news/signup
links: mollywhite.net/linktree
💗💜💙
Human/AI interaction. ML interpretability. Visualization as design, science, art. Professor at Harvard, and part-time at Google DeepMind.
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
We're the Department of Statistics at the University of Oxford (UK). We provide teaching & complete research on computational statistics and statistical methodology, probability, bioinformatics and mathematical genetics.
https://www.stats.ox.ac.uk/
Professor at UT Nuremberg, Germany
I’m 🇫🇷 and I work on RL and lifelong learning. Mostly posting on ML related topics.
Associate professor at U of Toronto. Computer science and math research: (differentially) private data analysis, geometry, discrepancy, optimization.
