Prateek Bhustali
PhD student - Multi-Agent Reinforcement Learning for Maintenance Planning @tudelft | Masters in Computational Sciences in Engineering @tuBraunschweig
@matteobettini.bsky.social
PhD Candidate at Cambridge | ex Meta, Amazon | Studying diversity in multi-agent and multi-robot learning https://matteobettini.com/
@idurugkar.bsky.social
Reinforcement learning researcher, dabbled in robotics, and generative techniques that were later made out of date by diffusion. Currently at Sony AI, working on game AI
@ben-eysenbach.bsky.social
Assistant professor at Princeton CS working on reinforcement learning and AI/ML. Site: https://ben-eysenbach.github.io/ Lab: https://princeton-rl.github.io/
@ncklashansen.bsky.social
PhD student at UCSD. NVIDIA fellow. Prev: Meta AI, UC Berkeley, DTU. Interested in reinforcement learning and robots. 🏳️🌈 they/he https://www.nicklashansen.com
@raghuspacerajan.bsky.social
PhD / PostDoc in Reinforcement Learning, AutoRL at the University of Freiburg. First author of MDP Playground. Opinions posted here are my own.
@jvgemert.bsky.social
Head of the Computer Vision lab; TU Delft. - Fundamental empirical Deep Learning research - Visual inductive priors for data efficiency Web: https://jvgemert.github.io/
@daphne-cornelisse.bsky.social
PhD student at NYU | Building human-like agents | https://www.daphne-cornelisse.com/
@stvrb.bsky.social
PhD candidate @UofT @VectorInst. Reliable, safe, trustworthy machine learning.
@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 📩
@paulbuerkner.com
Full Professor of Computational Statistics at TU Dortmund University Scientist | Statistician | Bayesian | Author of brms | Member of the Stan and BayesFlow development teams Website: https://paulbuerkner.com Opinions are my own
@avehtari.bsky.social
Professor in computational Bayesian modeling at Aalto University, Finland. Bayesian Data Analysis 3rd ed, Regression and Other Stories, and Active Statistics co-author. #mcmc_stan and #arviz developer. Also in Mastodon: https://bayes.club/@avehtari
@glouppe.bsky.social
AI for Science, deep generative models, inverse problems. Professor of AI and deep learning @universitedeliege.bsky.social. Previously @CERN, @nyuniversity.
@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
@fxbriol.bsky.social
Associate Professor at UCL Statistical Science. Interested in computational statistics, machine learning and applications in the sciences & engineering.
@upicchini.bsky.social
Full Professor at @deptmathgothenburg.bsky.social | simulation-based inference | Bayes | stochastic dynamical systems | https://umbertopicchini.github.io/
@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)
@canaesseth.bsky.social
Assistant Professor of Machine Learning Generative AI, Uncertainty Quantification, AI4Science Amsterdam Machine Learning Lab, University of Amsterdam https://naesseth.github.io
@lacerbi.bsky.social
Assoc. Prof. of Machine & Human Intelligence | Univ. Helsinki & Finnish Centre for AI (FCAI) | Bayesian ML & probabilistic modeling | https://lacerbi.github.io/
@fragrisoni.bsky.social
Associate Prof | AI for drug discovery | Eindhoven University of Technology | Previously ETH Zurich & UniMiB | she/her 🏳️🌈
@grzegorz.chrupala.me
Speech • Language • Learning https://grzegorz.chrupala.me @ Tilburg University
@madelonhulsebos.bsky.social
Faculty at CWI & ELLIS Amsterdam https://trl-lab.github.io. Previously at UC Berkeley and the University of Amsterdam. Research on neural models for tabular data; table representation learning 💫. https://www.madelonhulsebos.com
@smaglia.bsky.social
Assistant prof in the Amsterdam Machine Learning Lab at the University of Amsterdam | ELLIS scholar | #causality #causalML anything #causal | 🇮🇹🇸🇮 in 🇳🇱 | #UAI2025 program chair https://saramagliacane.github.io/
@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
@edoardo-ponti.bsky.social
Assistant professor in Natural Language Processing at the University of Edinburgh and visiting professor at NVIDIA | A Kleene star shines on the hour of our meeting.
@lenazellinger.bsky.social
ELLIS PhD student at the University of Edinburgh https://lenazellinger.github.io/
@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?👌…)
@papotti.bsky.social
Associate Prof at EURECOM and 3IA Côte d'Azur Chair of Artificial Intelligence. ELLIS member. Data management and NLP/LLMs for information quality. https://www.eurecom.fr/~papotti/
@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
@csprofkgd.bsky.social
#CS Associate Prof York University, #ComputerVision Scientist Samsung #AI, VectorInst Faculty Affiliate, TPAMI AE, ELLIS4Europe Member, #CVPR2025 Publicity Chair on X 📍Toronto 🇨🇦 🔗 csprofkgd.github.io 🗓️ Joined Nov 2024
@wkhuber.bsky.social
Statistician, Computational Biologist R | Bioconductor | Images are data https://www.huber.embl.de Textbook: Modern Statistics for Modern Biology https://www.huber.embl.de/msmb/ (with @sherlockpholmes.bsky.social)
@sanokows.bsky.social
Ellis PhD Student at JKU Linz working on Diffusion Samplers and combinatorial optimization
@dholzmueller.bsky.social
Postdoc in machine learning with Francis Bach & @GaelVaroquaux: neural networks, tabular data, uncertainty, active learning, atomistic ML, learning theory. https://dholzmueller.github.io
@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/
@trackingactions.bsky.social
Scientist 👩🔬 & EPFL Prof 🇨🇭 | DeepLabCut.org , 🦓 cebra.ai | neuroscience & ML 🧠 mackenziemathislab.org | ✨CSO at Kinematik.ai | occasionally 🐦⬛birds/🌱outdoors/🍣food
@desirivanova.bsky.social
Research fellow @OxfordStats @OxCSML, spent time at FAIR and MSR Former quant 📈 (@GoldmanSachs), former former gymnast 🤸♀️ My opinions are my own 🇧🇬-🇬🇧 sh/ssh
@coallaoh.bsky.social
Professor in Scalable Trustworthy AI @ University of Tübingen | Advisor at Parameter Lab & ResearchTrend.AI https://seongjoonoh.com | https://scalabletrustworthyai.github.io/ | https://researchtrend.ai/
@abursuc.bsky.social
Research Scientist at valeo.ai | Teaching at Polytechnique, ENS | Alumni at Mines Paris, Inria, ENS | AI for Autonomous Driving, Computer Vision, Machine Learning | Robotics amateur ⚲ Paris, France 🔗 abursuc.github.io
@krzakalaf.bsky.social
Love Physics, Maths, Machine learning, Computer Science but above all playing 🎸🎵 Happy dad 👧 👧. Also professor @ EPFL. Views are my own.
@alvaro.teje.ro
@niladridutt.bsky.social
PhD @ucl.ac.uk | @ellis.eu | ex-Nvidia, Berkeley | Interested in generative modelling in vision and graphics + reasoning (LLMs) https://niladridutt.com/
@jwvdm.bsky.social
Associate Professor (UHD) at the University of Amsterdam. Probabilistic methods, deep learning, and their applications in science in engineering.
@chatgtp.bsky.social
Machine learning for molecular biology. ELLIS PhD student at Fabian Theis lab. EPFL alumnus.
@dziadzio.bsky.social
ELLIS PhD student in machine learning at IMPRS-IS. Continual learning at scale. sebastiandziadzio.com
@imurray.bsky.social
Professor of Machine Learning and Inference, Edinburgh Informatics, Formally Amazon Scholar. Opinions are my own. Also https://homepages.inf.ed.ac.uk/imurray2/ and https://mastodon.social/@imurray and https://x.com/driainmurray