François-Xavier Briol @fxbriol.bsky.social Professor of Statistics and Machine Learning at UCL Statistical Science. Interested in computational statistics, machine learning and applications in the sciences & engineering.
Nathan Lambert @natolambert.bsky.social A LLN - large language Nathan - (RL, RLHF, society, robotics), athlete, yogi, chef
Writes http://interconnects.ai
Prev Ai2/Olmo, HuggingFace, Berkeley, and normal places
Sebastian Raschka (rasbt) @rasbt.bsky.social ML/AI researcher & former stats professor turned LLM research engineer. Author of "Build a Large Language Model From Scratch" (https://amzn.to/4fqvn0D) & reasoning (https://mng.bz/Nwr7).
Also blogging about AI research at magazine.sebastianraschka.com.
Marc Deisenroth @deisenroth.bsky.social Machine learning, environmental modeling, sustainability, robotics
Research Director @ Google DeepMind, Professor @ UCL
He/him
MC Stan @mc-stan.org Expressive probabilistic programming language for writing statistical models. Fast Bayesian inference. Interfaces for Python, Julia, R, and the Unix shell. A rich ecosystem of tools for validation and visualization.
Home https://mc-stan.org/
ICML Conference @icmlconf.bsky.social Official account of ICML
Alex Immer @aleximmer.bsky.social Research Scientist @Bioptimus. Previously at ETH Zürich, Max Planck Institute for Intelligent Systems, Google Research, EPFL, and RIKEN AIP.
aleximmer.github.io
Richi Paul @erpel.bsky.social phd student working on bayesian methods in bioimage analysis; @fz-juelich.de, @hds_lee & @lmu.de; bsc+msc in comp sci @univie.ac.at; based in karlsruhe; ripaul.github.io
Maike Osborne @maosbot.bsky.social Mother, wife, Australian, Professor of Machine Learning in Oxford. Long Covid, trans rights, music, reggae, AI must be good for humans, https://www.robots.ox.ac.uk/~mosb. She/her 🏳️⚧️🏳️🌈
Desi R Ivanova @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
Martin Trapp @trappmartin.eurosky.social Assistant Prof in Prob ML @ KTH 🇸🇪
WASP Fellow & ELLIS Member
Ex: Aalto Uni 🇫🇮, TU Graz 🇦🇹, originally 🇩🇪.
—
https://trappmartin.github.io/
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Reliable ML | UQ | Bayesian DL | tractability & PCs
Tim G. J. Rudner @timrudner.bsky.social Assistant Professor, University of Toronto.
Junior Research Fellow, Trinity College, Cambridge.
AI Fellow, Georgetown University.
Probabilistic Machine Learning, AI Safety & AI Governance.
Prev: Oxford, Yale, UC Berkeley, NYU.
https://timrudner.com
@rogergrosse.bsky.social @rogergrosse.bsky.social 
Yarin @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)
Thomas Möllenhoff @moellenh.bsky.social researcher
Andreas Kirsch @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
David Holzmüller @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
Emtiyaz Khan @emtiyaz.mastodon.social.ap.brid.gy Team leader (tenured) at RIKEN AIP. Opinions my own. https://emtiyaz.github.io
🌉 bridged from https://mastodon.social/@emtiyaz on the fediverse by https://fed.brid.gy/
Agustinus Kristiadi @agustinus.kristia.de Assistant Professor @westernu.ca, Faculty Affiliate @vectorinstitute.ai. Probabilistic machine learning, decision-making, AI4Science. Bayesian + frequentist, etc!
Gunnar König @gunnark.bsky.social PostDoc @ Uni Tübingen
explainable AI, causality
gunnarkoenig.com
Arik Reuter @arikreuter.bsky.social University of Cambridge and
Max Planck Institute for Intelligent Systems
I'm interested in amortized inference/PFNs/in-context learning for challenging probabilistic and causal problems.
https://arikreuter.github.io/
Julian Rodemann @jurodemann.bsky.social http://www.julian-rodemann.de | PostDoc CISPA Helmholtz | prev. PhD in statistics @LMU_Muenchen | VRS @HarvardStats
Giuseppe Casalicchio @giuseppe88.bsky.social Senior Lecturer and Researcher @LMU_Muenchen working on #ExplainableAI / #interpretableML and #OpenML
Samuel Müller @sammuller.bsky.social (Tab)PFNs, TrivialAugment etc.
Andreas Krause @arkrause.bsky.social Professor at ETH Zurich
Lennart Purucker @lennartpurucker.bsky.social PhD student sup. by Frank Hutter; researching automated machine learning and foundation models for (small) tabular data!
Website: https://ml.informatik.uni-freiburg.de/profile/purucker/
Andrew Gordon Wilson @andrewgwils.bsky.social Machine Learning Professor
https://cims.nyu.edu/~andrewgw
Philipp Hennig @philipphennig.bsky.social Professor for AI/ML Methods in Tübingen. Posts about Probabilistic Numerics, Bayesian ML, AI for Science. Computations are data, Algorithms make assumptions.- S Andrew Gelman et al. @statmodeling.bsky.social Automatically tweets new posts from http://statmodeling.stat.columbia.edu
Please respond in the comment section of the blog.
Old posts spool at https://twitter.com/StatRetro
Marius Lindauer @mlindauer.bsky.social Full Professor of ML & #AutoML at Leibniz University Hannover. #ERC Grant Holder. Interested in: AutoML, ML, RL, iML, LLMs, foundation models and a lot more ;-)
Christoph Molnar @christophmolnar.bsky.social Author of Interpretable Machine Learning and other books
Newsletter: https://mindfulmodeler.substack.com/
Website: https://christophmolnar.com/
André Biedenkapp @abiedenkapp.bsky.social Subgroup Lead at the University of Freiburg researching generalizability of RL and Automated RL
Joaquin Vanschoren @joavanschoren.bsky.social Building AI systems that learn how to learn, grow and adapt continuously, and push humanity forward. Continual learning, meta-learning, open-endedness. Group Lead at TU Eindhoven, Founder of OpenML, NeurIPS D&B Track. 
Francis Bach @bachfrancis.bsky.social Researcher in machine learning
Ravid Shwartz Ziv @shwartzzzivravid.bsky.social Faculty Fellow and Assistant Professor at
NYU's Center of Data Science
Willie Neiswanger @willieneis.bsky.social Assistant Professor in CS + AI at USC. Previously at Stanford, CMU. Machine Learning, Decision Making, AI-for-Science, Generative AI, ML Systems, LLMs.
https://willieneis.github.io
Aki Vehtari @avehtari.bsky.social Professor in computational Bayesian modeling, Aalto University, Finland. Co-author of Bayesian Data Analysis 3rd ed, Regression and Other Stories, Active Statistics and Bayesian Workflow. #mcmc_stan and #arviz developer.
https://users.aalto.fi/ave/
Vincent Fortuin @vincefort.eurosky.social Prof at TU Nuremberg, PI at Helmholtz AI, Fellow at Zuse School for reliable AI, Branco Weiss Fellow, ELLIS Scholar.
Prev: TUM, Cambridge CBL, St John's College, ETH Zürich, Google Brain, Microsoft Research, Disney Research.
https://fortuin.github.io/
AutoML Podcast @automl-podcast.bsky.social Talking about all things AutoML.
Full episode list: https://automlpodcast.com/
Nick Erickson @nickerickson.bsky.social Author of AutoGluon: auto.gluon.ai
Senior Applied Scientist @ AWS AI
#opensource #automl
Leonard Papenmeier @leonard.papenmeier.io Postdoctoral researchers | Bayesian optimization | University of Münster | https://leonard.papenmeier.io/
@klein-aaron.bsky.social @klein-aaron.bsky.social 
Katharina Eggensperger @keggensperger.bsky.social Professor for ML and AI at Lamarr Institute / @tu-dortmund.de. Working on AutoML and Tabular Data. All opinions are my own.
Mina Rezaei @minarezaei.bsky.social Machine Learning Researcher, @LMU Munich, MCML
Interested in probabilistic deep learning, generative models, and trustworthy ML.
minare.github.io
Matthias Feurer @matthiasfeurer.bsky.social Assistant Professor "AutoML and Optimization" @ Lamarr institute and @tu-dortmund.bsky.social. Working on #AutoML, #HPO, #TabularData #OpenML #Benchmarking | https://matthiasfeurer.de | https://automl.cs.tu-dortmund.de
Fiona K. Ewald @fionaewald.bsky.social PhD Student @ LMU Munich
Munich Center for Machine Learning (MCML)
Research in Interpretable ML / Explainable AI
Munich Center for Machine Learning @munichcenterml.bsky.social The MCML is a joint research initiative of LMU München and TU München. It is institutionally funded by the Federal Ministry of Education and Research and the Free State of Bavaria.
Andreas Bender @adibender.bsky.social Senior Lecturer @ LMU Munich
Lead Machine Learning Consulting Unit @ Munich Center for Machine Learning
Matthias Aßenmacher @assenmacher.bsky.social Postdoc | #NLProc researcher | @slds-lmu.bsky.social | @munichcenterml.bsky.social | @berd-nfdi.bsky.social
yawei.li @yaweili-sandylaker.bsky.social PhD candidate at LMU Munich | Munich Center for Machine Learning (MCML) | https://sandylaker.github.io |
Open to work.
Philip Boustani @paboustani.bsky.social MCML PhD student @ LMU Munich
Working on causal & fair ML
Interested in social science and the book of why
He/him
Ludwig Bothmann @ludwig-bothmann.bsky.social PostDoc @ LMU Munich
Group Leader CausalFairML
Munich Center for Machine Learning (MCML)
Thomas Nagler @tnagler.bsky.social Mathematician, Statistician, Programmer. Prof at LMU Munich
Rickmer Schulte @rickmer.bsky.social PhD Student @ LMU Munich
Munich Center for Machine Learning (MCML)
David Rügamer @davidruegamer.bsky.social Associate Prof @ LMU Munich
PI @ Munich Center for Machine Learning
Ellis Member
Associate Fellow @ relAI
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https://davidruegamer.github.io/ | https://www.muniq.ai/
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BNNs, UQ in DL, DL Theory (Overparam, Optim), Sparsity, TabFMs
@jkobialka.bsky.social @jkobialka.bsky.social 
Chair of Statistical Learning and Data Science at the LMU Munich @slds-lmu.bsky.social https://www.slds.stat.uni-muenchen.de