Matthew Wicker
Assistant professor (lecture), Imperial College London. I study trustworthiness of machine learning models. Previously: ATI, U. Of Oxford, UGA
@jwvdm.bsky.social
Associate Professor (UHD) at the University of Amsterdam. Probabilistic methods, deep learning, and their applications in science in engineering.
@yaringal.bsky.social
Associate Professor of Machine Learning, University of Oxford; OATML Group Leader; Director of Research at the UK government's AI Safety Institute (formerly UK Taskforce on Frontier AI)
@shakirm.bsky.social
AI, sociotechnical systems, social purpose. Research director at Google DeepMind. Cofounder and Chair at Deep Learning Indaba. FAccT2025 co-program chair. shakirm.com
@avt.im
Decision-making under uncertainty, machine learning theory, artificial intelligence · anti-ideological · Assistant Research Professor, Cornell https://avt.im/ · https://scholar.google.com/citations?user=EGKYdiwAAAAJ&sortby=pubdate
@eringrant.bsky.social
Senior Research Fellow @ ucl.ac.uk/gatsby & sainsburywellcome.org {learning, representations, structure} in 🧠💭🤖 my work 🤓: eringrant.github.io not active: sigmoid.social/@eringrant @[email protected], twitter.com/ermgrant @ermgrant
@betanalpha.bsky.social
Zealous modeler. Annoying statistician. Reluctant geometer. Support my writing at http://patreon.com/betanalpha. He/him.
@blackhc.bsky.social
My opinions only here. 👨🔬 RS DeepMind Past: 👨🔬 R Midjourney 1y 🧑🎓 DPhil AIMS Uni of Oxford 4.5y 🧙♂️ RE DeepMind 1y 📺 SWE Google 3y 🎓 TUM 👤 @nwspk
@maosbot.bsky.social
Parent, spouse, Australian, Professor of Machine Learning in Oxford. Bayesian ML, Long Covid, trans rights, photos of dog, AI must be good for humans, https://www.robots.ox.ac.uk/~mosb
@rmcelreath.bsky.social
Anthropologist - Bayesian modeling - organic modem converting poetry into code - cat and cooking content too - Director @ MPI for evolutionary anthropology https://www.eva.mpg.de/ecology/staff/richard-mcelreath/
@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/
@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?👌…)
@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
@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
@roydanroy.bsky.social
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.
@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/
@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.
@kontoyiannis.bsky.social
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]
@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
@vincefort.bsky.social
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/
@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
@claireve.bsky.social
Group Leader in Tübingen, Germany I’m 🇫🇷 and I work on RL and lifelong learning. Mostly posting on ML related topics.
@gokul.dev
PhD student at @cmurobotics.bsky.social working on interactive learning from implicit human feedback (e.g. imitation/RLHF). no model is an island. https://gokul.dev/.
@kfountou.bsky.social
Associate Professor at CS UWaterloo Machine Learning Lab: opallab.ca
@ftudisco.bsky.social
Machine Learning @ University of Edinburgh | AI4Science | optimization | numerics | networks | co-founder @ MiniML.ai | ftudisco.gitlab.io
@ncollina.bsky.social
Penn CS PhD student and IBM PhD Fellow studying strategic algorithmic interaction. Calibration, commitment, collusion, collaboration. She/her. Nataliecollina.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/
@jrudoler.bsky.social
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)
@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
@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
@ccanonne.github.io
Senior Lecturer #USydCompSci at the University of Sydney. Postdocs IBM Research and Stanford; PhD at Columbia. Converts ☕ into puns: sometimes theorems. He/him.
@thejonullman.bsky.social
Associate Professor of Computer Science at Northeastern University in Boston. Dad. Imposter.
@thesasho.bsky.social
Associate professor at U of Toronto. Computer science and math research: (differentially) private data analysis, geometry, discrepancy, optimization.
@sikatasengupta.bsky.social
cs phd @upenn advised by Michael Kearns, Aaron Roth, and Duncan Watts| previously @stanford | she/her https://psamathe50.github.io/sikatasengupta/
@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
@stein.ke
Computer science, math, machine learning, (differential) privacy Researcher at Google DeepMind Kiwi🇳🇿 in California🇺🇸 http://stein.ke/
@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.
@bsky.app
official Bluesky account (check username👆) Bugs, feature requests, feedback: [email protected]