Maxime Robeyns
PhD student in ML. Bayesian deep learning, LLMs for software development, RL and open-endedness.
https://maximerobeyns.com
@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
@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
@chanpyb.bsky.social
PhD student at University of Alberta. Interested in reinforcement learning, imitation learning, machine learning theory, and robotics https://chanb.github.io/
@kfountou.bsky.social
Associate Professor at CS UWaterloo Machine Learning Lab: opallab.ca
@rachel-law.bsky.social
Organic machine turning tea into theorems ☕️ AI @ Microsoft Research ➡️ Goal: Teach models (and humans) to reason better Let’s connect re: AI for social good, graphs & network dynamics, discrete math, logic 🧩, 🥾,🎨 Organizing for democracy.🗽 www.rlaw.me
@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.
@gavin-brown.bsky.social
Postdoc at UW CSE. Differential privacy, memorization in ML, and learning theory.
@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/
@lauraruis.bsky.social
PhD supervised by Tim Rocktäschel and Ed Grefenstette, part time at Cohere. Language and LLMs. Spent time at FAIR, Google, and NYU (with Brenden Lake). She/her.
@afspies.bsky.social
@alexlew.bsky.social
Theory & practice of probabilistic programming. Current: MIT Probabilistic Computing Project; Fall '25: Incoming Asst. Prof. at Yale CS
@cmaddis.bsky.social
Asst. Prof. in Machine Learning at UofT. #LongCOVID patient. https://www.cs.toronto.edu/~cmaddis/
@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
@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/
@tychovdo.bsky.social
Postgraduate researcher (PhD) at Imperial College London and visiting researcher at the University of Oxford. Working on probabilistic machine learning.
@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
@sethaxen.com
Empowering scientists with machine learning @mlcolab.org. Sometimes #Bayesian. Usually #FOSS. Preferably in #JuliaLang. Expat: 🇺🇸 ➡️ 🇩🇪 💼 On the job market (remote/Stuttgart area) sethaxen.com
@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!
@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.
@gdalle.bsky.social
Researcher in machine learning and optimization. Open source enthusiast. Parody songwriter (aka PianoHamster). OCD survivor.
@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/
@mschauer.bsky.social
Statistician, Associate Professor (Lektor) at University of Gothenburg and Chalmers; inference and conditional distributions for anything https://mschauer.github.io http://orcid.org/0000-0003-3310-7915 [ˈmoː/r/ɪts ˈʃaʊ̯ɐ]
@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
@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
@sulinliu.bsky.social
Postdoc at MIT. Generative models, inference, AI for science. Prev: Princeton, Meta, NUS. liusulin.github.io
@ianholmes.org
Berkeley professor (Bioeng, Compbio). Visiting Scientist at Calico. JBrowse genome browser / Apollo annotation editor, ML for gene regulation / molecular evolution / synbio.
@jameshensman.bsky.social
Trying to make all the AIs more efficient. Former Gaussian process connoisseur. Researcher at Microsoft Research.
@jamesallingham.bsky.social
Research Scientist @GoogleDeepMind | Organiser @DeepIndaba | Machine Learning PhD @CambridgeMLG | 🇿🇦
@dan-kowal.bsky.social
Associate Professor of Statistics and Data Science at Cornell University. https://www.danielrkowal.com/
@stepleton.bsky.social
AI research engineer, glider pilot. Apple Lisa power user. @stepleton@oldbytes.space on Mastodon, @tstepleton from the last place. Most of my posts will be about old computers; occasionally I'll mention flying.
@earningmyturns.org
I am an Engineering Fellow at Google DeepMind, creating bridges between AI research and product.