@tmlrorg.bsky.social
Transactions on Machine Learning Research (TMLR) is a new venue for dissemination of machine learning research https://jmlr.org/tmlr/
@samuelvaiter.com
CNRS Researcher in maths & computer science. My (current) focus is machine learning and optimization. I live & work in Nice 🇫🇷 website: https://samuelvaiter.com
@xy-han.bsky.social
Assistant Professor @ChicagoBooth | Papers: “Neural Collapse in Deep Nets” & “Survey Descent: Nonsmooth GD” | BSE @Princeton, MS @Stanford, PhD @Cornell | xyhan.me
@damekdavis.bsky.social
Currently an associate professor at Cornell. Working on optimization/ML. Missing California. DamekDavis.com
@esoubies.bsky.social
CNRS researcher at IRIT. Computational Imaging, Microscopy, Optimization, Machine Learning Website: https://www.irit.fr/~Emmanuel.Soubies/
@mathurinmassias.bsky.social
Tenured Researcher @INRIA, Ockham team. Teacher @Polytechnique and @ENSdeLyon Machine Learning, Python and Optimization
@matdag.bsky.social
Postdoc at Inria working on optimization and machine learning. Website: https://matdag.github.io/
@fschaipp.bsky.social
Researcher in Optimization for ML at Inria Paris. Previously at TU Munich. sbatch and apero. https://fabian-sp.github.io/
@alucchi.bsky.social
Researcher in optimization and theoretical machine learning. Assistant professor at the University of Basel. Past: EPFL, ETH Zurich (Switzerland) 🇨🇭
@cevherlions.bsky.social
Associate Professor of Electrical Engineering, EPFL. Amazon Scholar (AGI Foundations). IEEE Fellow. ELLIS Fellow.
@krishnaswamylab.bsky.social
We develop AI methods for science, particularly deep learning methods based on data geometry, topology and dynamics systems.
@twkillian.bsky.social
Senior Research Scientist @MBZUAI. Focused on decision making under uncertainty, guided by practical problems in healthcare, reasoning, and biology.
@pseudomanifold.topology.rocks
Dad · Geometry ∩ Topology ∩ Machine Learning Professor at University of Fribourg While #geometry & #topology may not save the world, they may well save something that is homotopy-equivalent to it. 🏠 https://bastian.rieck.me/ 🏫 https://aidos.group
@aliciacurth.bsky.social
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
@pamattei.bsky.social
Research scientist, Inria. Statistical machine learning.
@guillemsimeon.bsky.social
(He/him) Physicist. Machine learning and atoms @ Microsoft Quantum. 🏳️🌈
@emilevankrieken.com
Post-doc @ University of Edinburgh. Neurosymbolic Machine Learning, Generative Models, NLP https://www.emilevankrieken.com/
@pierrealquier.bsky.social
Professor of Statistics @ ESSEC Business School Asia-Pacific campus Singapore 🇸🇬 https://pierrealquier.github.io/ Previously: RIKEN AIP 🇯🇵 ENSAE Paris 🇫🇷 🇪🇺 UCD Dublin 🇮🇪 🇪🇺 Random posts about stats/maths/ML/AI, poor jokes & birds photo 🌈
@fxbriol.bsky.social
Associate Professor at UCL Statistical Science. Interested in computational statistics, machine learning and applications in the sciences & engineering.
@martinvoegele.bsky.social
Computational Biophysicist, Amateur Photographer, History+Language Nerd. All views my own. Website: https://martinvoegele.github.io/
@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=6Qa-wXMAAAAJ&sortby=pubdate
@marvinschmitt.bsky.social
🇪🇺 AI/ML, Member @ellis.eu 🤖 Generative NNs, ProbML, Uncertainty Quantification, Amortized Inference, Simulation Intelligence 🎓 PhD+MSc CS, MSc Psych 🏡 marvinschmitt.github.io ✨ On the job market, DMs open 📩
@nolovedeeplearning.bsky.social
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
@jwvdm.bsky.social
Associate Professor (UHD) at the University of Amsterdam. Probabilistic methods, deep learning, and their applications in science in engineering.
@neuralnoise.com
Researcher in ML/NLP at the University of Edinburgh (faculty at Informatics and EdinburghNLP), Co-Founder/CTO at www.miniml.ai, ELLIS (@ELLIS.eu) Scholar, Generative AI Lab (GAIL, https://gail.ed.ac.uk/) Fellow -- www.neuralnoise.com, he/they
@clementinedomine.bsky.social
•PhD student @ https://www.ucl.ac.uk/gatsby 🧠💻 •Masters Theoretical Physics UoM|UCLA🪐 •Intern @zuckermanbrain.bsky.social| @SapienzaRoma | @CERN | @EPFL https://linktr.ee/Clementine_Domine
@yoshuabengio.bsky.social
Full professor at UdeM, Founder and Scientific Advisor at Mila - Quebec AI Institute, A.M. Turing Award Recipient. Working towards the safe development of AI for the benefit of all. Website and blog: https://yoshuabengio.org/
@richtarik.bsky.social
Professor of CS and Math @ KAUST. Interested in Optimization for Machine Learning. Federated learning guru. Likes 🏓🏋️♂️🎾🏐⛷️⛸️🧘♂️🤿🎹🎸✈️🏔️📷☀️🐈🍅🥚☕️
@mmbronstein.bsky.social
DeepMind Professor of AI @Oxford Scientific Director @Aithyra Chief Scientist @VantAI ML Lead @ProjectCETI geometric deep learning, graph neural networks, generative models, molecular design, proteins, bio AI, 🐎 🎶
@laurentdinh.bsky.social
Internet pedestrian. ✨Content creator✨ (ML researcher). ᕕ(ツ)ᕗ (he/him/his) https://laurent-dinh.github.io/
@deisenroth.bsky.social
Machine learning, environmental modeling, sustainability, robotics Professor @UCL He/him
@lucamb.bsky.social
Assistant professor in Machine Learning and Theoretical Neuroscience. Generative modeling and memory. Opinionated, often wrong.
@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]
@miniapeur.bsky.social
Gradient surfer at UCL. FR, EN, also trying ES. 🇹🇼🇨🇦🇬🇳🇺🇸🇩🇴🇫🇷🇪🇸🇬🇧🇿🇦. Also on Twitter.
@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
@stein.ke
Computer science, math, machine learning, (differential) privacy Researcher at Google DeepMind Kiwi🇳🇿 in California🇺🇸 http://stein.ke/
@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
@sophie.huiberts.me
linear programming enthusiast. investigator of evil science. haunted by beans. she/her
@mahdi.ch
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.
@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
@anupamg.bsky.social
Professor, Computer Science, New York University. Interested in Algorithms.
@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.
@henryyuen.bsky.social
Complexity, in all its forms. Associate Professor of Computer Science at Columbia University. http://www.henryyuen.net
@thesasho.bsky.social
Associate professor at U of Toronto. Computer science and math research: (differentially) private data analysis, geometry, discrepancy, optimization.
@jasonhartline.bsky.social
Professor at Northwestern CS. Economics, by courtesy. Study mechanism design, economics of algorithms, regulation of algorithms, AI and society. https://sites.northwestern.edu/hartline/
@thejonullman.bsky.social
Associate Professor of Computer Science at Northeastern University in Boston. Dad. Imposter.
@rrwilliams.bsky.social
professor of EECS at MIT. 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)