@rosanneliu.com
Founder & executive & community builder & organizer & researcher ML Collective (mlcollective.org) Google DeepMind rosanneliu.com
@patrickkidger.bsky.social
I do SciML + open source! 🧪 ML+proteins @ http://Cradle.bio 📚 Neural ODEs: http://arxiv.org/abs/2202.02435 🤖 JAX ecosystem: http://github.com/patrick-kidger 🧑💻 Prev. Google, Oxford 📍 Zürich, Switzerland
@gabrielpeyre.bsky.social
@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
@jgu32.bsky.social
Machine Learning Researcher @Apple MLR Incoming Assistant Professor @Penn CIS See more details https://jiataogu.me
@kylecranmer.bsky.social
Director Data Science Institute @UWMadison, Professor of Physics, EiC @MLSTjournal. Physics, stats/ML/AI, open science.
@alexlew.bsky.social
Theory & practice of probabilistic programming. Current: MIT Probabilistic Computing Project; Fall '25: Incoming Asst. Prof. at Yale CS
@canaesseth.bsky.social
Assistant Professor of Machine Learning Generative AI, Uncertainty Quantification, AI4Science Amsterdam Machine Learning Lab, University of Amsterdam https://naesseth.github.io
@sejdino.bsky.social
Professor of Statistical Machine Learning at the University of Adelaide. https://sejdino.github.io/
@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
@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 @eringrant@sigmoid.social, twitter.com/ermgrant @ermgrant
@jwvdm.bsky.social
Associate Professor (UHD) at the University of Amsterdam. Probabilistic methods, deep learning, and their applications in science in engineering.
@mvdw.bsky.social
Associate Professor in Machine Learning at the University of Oxford. Interested in automatic inductive bias selection using Bayesian tools.
@mgorinova.bsky.social
ex-@TwitterCortex @Birdwatch 💙 | Now LLMs for innovation & IP 🚀 | PhD in probabilistic machine learning, loyal servant to a cat, collector of random variables, lover of well-placed puns https://mgorinova.github.io/
@maosbot.bsky.social
Parent, spouse, Australian, cyclist, Professor of Machine Learning in Oxford. Bayesian ML, Long Covid, photos of dog, AI must be good for humans, https://www.robots.ox.ac.uk/~mosb
@tychovdo.bsky.social
Postgraduate researcher (PhD) at Imperial College London and visiting researcher at the University of Oxford. Working on probabilistic machine learning.
@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/
@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)
@karen-ullrich.bsky.social
Research scientist at FAIR NY ❤️ Machine Learning + Information Theory. Previously, PhD at UoAmsterdam, intern at DeepMind + MSRC.
@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
@emilevankrieken.com
Post-doc @ University of Edinburgh. Neurosymbolic Machine Learning, Generative Models, NLP https://www.emilevankrieken.com/
@mgollub.bsky.social
🧬💻 | Director of Machine Learning @jura.bsky.social | Probabilistic models, ML, Molecular biology, Immune receptors.
@olegranmo.bsky.social
AI Professor and Founding Director @ https://cair.uia.no | Chair of Technical Steering Committee @ https://www.literal-labs.ai | Book: https://tsetlinmachine.org
@idris1.bsky.social
Johns Hopkins CS PhD student. #MedicalRobotics #ComputerVision #DeepLearning #Guitar
@javaloyml.bsky.social
Postdoc at the University of Edinburgh working on Machine Learning. Previously in Saarbrücken, Tübingen, and Murcia. 🌐 adrianjav.github.io
@lenazellinger.bsky.social
ELLIS PhD student at the University of Edinburgh https://lenazellinger.github.io/
@nicolabranchini.bsky.social
🇮🇹 Stats PhD @ University of Edinburgh 🏴 @ellis.eu PhD - visiting @avehtari.bsky.social 🇫🇮 🤔💭 about uncertainty quantification. Interested in sampling/transport methodologies, applications in climate/science. https://www.branchini.fun/about
@leanderk.bsky.social
ML PhD student @ Uni Edinburgh Interesting in (tractable) probabilistic machine learning, computing niche integrals and whatever you want to tell me about your research!
@loreloc.bsky.social
#probabilistic-ml #circuits #tensor-networks PhD student @ University of Edinburgh https://loreloc.github.io/
@andreasgrv.bsky.social
Postdoc in ML/NLP at the University of Edinburgh. Interested in Bottlenecks in Neural Networks; Unargmaxable Outputs. https://grv.unargmaxable.ai/
@velezbeltran.bsky.social
Machine Learning PhD Student @ Blei Lab & Columbia University. Working on probabilistic ML | uncertainty quantification | LLM interpretability. Excited about everything ML, AI and engineering!
@dianarycai.bsky.social
Machine learning & statistics researcher @ Flatiron Institute. Posts on probabilistic ML, Bayesian statistics, decision making, and AI/ML for science. www.dianacai.com
@trappmartin.bsky.social
ML Researcher @ Aalto University 🇫🇮. Previous: TU Graz 🇦🇹, originally from 🇩🇪. Doing: Reliable ML | uncertainty stuff | Bayesian stats | probabilistic circuits https://trappmartin.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)
@thomas-pinder.bsky.social
Bayesian statistics, Gaussian processes, and all things ML. Senior Applied Scientist at Amazon and developer of GPJax.
@sperez-vieites.bsky.social
Postdoctoral researcher at Aalto University and FCAI, Helsinki 🇫🇮 Previously in Edinburgh, Lille and Madrid. Working on Bayesian inference for state-space models, and Bayesian experimental design. https://sarapv.github.io/
@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.
@guyvdb.bsky.social
🎓 CS Prof at UCLA 🧠 Researching reasoning and learning in artificial intelligence: tactable deep generative models, probabilistic circuits, probabilistic programming, neurosymbolic AI https://web.cs.ucla.edu/~guyvdb/
@siahkoohi.bsky.social
Assistant Professor, CS at UCF | Uncertainty Quantification https://alisiahkoohi.github.io/
@kareemyousrii.bsky.social
Postdoc @ University of California, Irvine | PhD from CS@UCLA Neuro-Symbolic AI, Tractable Probabilistic Reasoning, Generative Models kareemahmed.com
@wordscompute.bsky.social
nlp/ml phding @ usc, interpretability & reasoning & pretraining & emergence 한american, she, iglee.me, likes ??= bookmarks
@glouppe.bsky.social
AI for Science, deep generative models, inverse problems. Professor of AI and deep learning @universitedeliege.bsky.social. Previously @CERN, @nyuniversity.
@swetakar.bsky.social
Machine learning PhD student @ Blei Lab in Columbia University Working in mechanistic interpretability, nlp, causal inference, and probabilistic modeling! Previously at Meta for ~3 years on the Bayesian Modeling & Generative AI teams. 🔗 www.sweta.dev
@flaviucipcigan.bsky.social
Building AIs for scientific discovery at IBM Research & AI Alliance. Discovered antibiotics and materials for carbon capture. Tango dancer. See more at flaviucipcigan.com. Opinions my own.
@sulinliu.bsky.social
Postdoc at MIT. Generative models, inference, AI for science. Prev: Princeton, Meta, NUS. liusulin.github.io