@cassidylaidlaw.bsky.social
PhD student at UC Berkeley studying RL and AI safety. https://cassidylaidlaw.com
@hellojas.bsky.social
making coffee (to make robots (to make coffee)) @ deepmind nyc find me at your local coffee shop, climbing gym, or music studio. ✨ hellojas.studio
@lukemarris.bsky.social
Research Engineer at Google DeepMind. Interests in game theory, reinforcement learning, and deep learning. Website: https://www.lukemarris.info/ Google Scholar: https://scholar.google.com/citations?user=dvTeSX4AAAAJ
@katjahofmann.bsky.social
At Microsoft Research. Lead of https://aka.ms/game-intelligence - we drive innovation in machine learning with applications in games. https://iclr.cc Board.
@djain.bsky.social
HCI Assistant Professor at UMich researching accessibility, audio AI, sound interaction, XR, and health. Director, Soundability Lab. Previously, Google, Apple, Microsoft, UW, and MIT Media Lab. https://dhruv-jain.com
@lukaschaefer.bsky.social
www.lukaschaefer.com Researcher @msftresearch.bsky.social; working on autonomous agents in video games; PhD Univ of Edinburgh ; Ex Huawei Noah’s Ark Lab, Dematic; Young researcher HLF 2022
@pablogmorato.bsky.social
Postdoctoral Researcher @TUDelft Multi-agent reinforcement learning, probabilistic deep learning, computer vision, wind energy. Opinions are “probably” my own.
@dijiang319.bsky.social
Senior editor @science.org. Molecular biology, #DNA, #RNA, #gene regulation, #epigenetics, nuclear biology, #chromatin biology, 3D #genome, #synbio, #CRISPR and gene editing, other bacterial immune systems, and #AI in all these
@matt.godbolt.org
Sometime verb, real person, lover of 8-bit computers, husband & father, trying to be a kind person. #blacklivesmatter; trans rights are human rights. he/him
@nandofioretto.bsky.social
Assistant Professor of Computer Science at the University of Virginia. I work on Responsible AI (differential privacy & fairness) and machine learning for science and engineering (differentiable optimization) | http://nandofioretto.github.io
@adamsmith.xyz
Professor of computer science at Boston University. Not related to any economists, living or dead, as far as I know.
@ahonkela.bsky.social
Prof of machine learning at University of Helsinki. Interested in (differential) privacy and open source software.
@jubaz.bsky.social
Assistant professor at Georgia Tech in ISyE. I do mechanism design, differential privacy, fairness, and learning theory, mostly. Postdoc @Penn; Ph.D. @Caltech; MSc @Columbia and @Supélec. He/him.
@differentialprivacy.org
🤖 new arXiv preprints mentioning "differential privacy" or "differentially private" in the title/abstract/metadata + updates from https://differentialprivacy.org [Under construction.]
@vsergei.bsky.social
Algorithms, predictions, privacy. https://theory.stanford.edu/~sergei/
@rasmuspagh.net
Professor of computer science at University of Copenhagen. Interested in random things & their application (especially to algorithms and privacy). rasmuspagh.net
@jelaninelson.bsky.social
Professor and Chair of Computer Science Division, UC Berkeley EECS. Research Scientist (part-time) at Google. Founder, AddisCoder. 🇻🇮🇺🇸🇪🇹
@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.
@sikatasengupta.bsky.social
cs phd @upenn advised by Michael Kearns, Aaron Roth, and Duncan Watts| previously @stanford | she/her https://psamathe50.github.io/sikatasengupta/
@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)
@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
@ftudisco.bsky.social
Machine Learning @ University of Edinburgh | AI4Science | optimization | numerics | networks | co-founder @ MiniML.ai | ftudisco.gitlab.io
@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.
@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
@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]
@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.
@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/
@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.
@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/
@kiragoldner.bsky.social
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
@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
@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