Assistant Professor at Stanford Statistics and Stanford Data Science | Previously postdoc at UW Institute for Protein Design and Columbia. PhD from MIT.
@vincentmallet.bsky.social
Group Leader @ Institut Curie. Working on geometric deep learning for protein and RNA structures representation. Interested in drug design applications.
@karstenkreis.bsky.social
Principal Research Scientist at NVIDIA | Former Physicist | Deep Generative Learning | https://karstenkreis.github.io/ Opinions are my own.
@maom.bsky.social
Assistant Professor at UMich with a focus on computational pharmacology (he/him)
@sarahalamdari.bsky.social
Senior Applied Scientist @ MSR // AI, molecular dynamics, protein design, and some sillyness 🧬 (she/her)
@anton-bushuiev.bsky.social
PhD student at CTU Prague. Working on machine learning for molecule discovery 🤖🧪
@delalamo.xyz
Protein engineering & synthetic biochemistry at GSK Opinions my own https://linktr.ee/ddelalamo
@shriramc.bsky.social
ML Scientist @prescientdesign.bsky.social developing LLM agents for biological discovery. Previously at Stanford and UChicago
@chrmanning.bsky.social
Stanford Linguistics and Computer Science. Director, Stanford AI Lab. Founder of @stanfordnlp.bsky.social . #NLP https://nlp.stanford.edu/~manning/
@yann-lecun.bsky.social
Professor a NYU; Chief AI Scientist at Meta. Researcher in AI, Machine Learning, Robotics, etc. ACM Turing Award Laureate. http://yann.lecun.com
@anshulkundaje.bsky.social
Genomics, Machine Learning, Statistics, Big Data and Football (Soccer, GGMU)
@manoliskellis.bsky.social
@lawrennd.bsky.social
Professor of Machine Learning, University of Cambridge, academic lead of ai@cam, Accelerate Science, author of The Atomic Human, proceedings editor for PMLR.
@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)
@shakirm.bsky.social
AI, sociotechnical systems, social purpose. Research director at Google DeepMind. Cofounder and Chair at Deep Learning Indaba. FAccT2025 co-program chair. shakirm.com
@davidduvenaud.bsky.social
Machine learning prof at U Toronto. Working on evals and AGI governance.
@bleilab.bsky.social
Machine learning lab at Columbia University. Probabilistic modeling and approximate inference, embeddings, Bayesian deep learning, and recommendation systems. 🔗 https://www.cs.columbia.edu/~blei/ 🔗 https://github.com/blei-lab
@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
@jeffdean.bsky.social
Google Chief Scientist, Gemini Lead. Opinions stated here are my own, not those of Google. Gemini, TensorFlow, MapReduce, Bigtable, Spanner, ML things, ...
@carldeboer.bsky.social
Assistant Professor, UBC school of Biomedical Engineering. Trying to enable personalized medicine by solving gene regulatory code.
@arnauddoucet.bsky.social
Senior Staff Research Scientist @Google DeepMind, previously Stats Prof @Oxford Uni - interested in Computational Statistics, Generative Modeling, Monte Carlo methods, Optimal Transport.
@arthurgretton.bsky.social
@davidaknowles.bsky.social
machine learning and functional/statistical genetics. Assistant Prof @Columbia and Core Faculty @nygenome. he/him/his. https://daklab.github.io/
@jesfrellsen.bsky.social
Associate Professor of Machine Learning and Signal Processing, Technical University of Denmark (DTU) https://frellsen.org
@francesarnold.bsky.social
Engineer/scientist, Nobel Prize in Chemistry 2018 I love evolution, enzymes, protein engineering, AI Linus Pauling Professor at Caltech
@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
@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
@keyonv.bsky.social
Postdoctoral fellow at Harvard Data Science Initiative | Former computer science PhD at Columbia University | ML + NLP + social sciences https://keyonvafa.com
@irenetrampoline.bsky.social
ML for healthcare and health equity. Assistant Professor at UC Berkeley and UCSF. https://irenechen.net/
@moberst.bsky.social
Assistant Prof. of CS at Johns Hopkins Visiting Scientist at Abridge AI Causality & Machine Learning in Healthcare Prev: PhD at MIT, Postdoc at CMU
@fxbriol.bsky.social
Associate Professor at UCL Statistical Science. Interested in computational statistics, machine learning and applications in the sciences & engineering.
@spmontecarlo.bsky.social
Lecturer in Maths & Stats at Bristol. Interested in probabilistic + numerical computation, statistical modelling + inference. (he / him). Homepage: https://sites.google.com/view/sp-monte-carlo Seminar: https://sites.google.com/view/monte-carlo-semina
@masakanai.bsky.social
@heyyjudes.bsky.social
CS PhD Student @ Stanford Data, Diversity, and Downstream Impacts https://heyyjudes.github.io
@mvdw.bsky.social
Associate Professor in Machine Learning at the University of Oxford. Interested in automatic inductive bias selection using Bayesian tools.
@lizbwood.bsky.social
Founder & CEO @jura.bsky.social | Full-stack probabilistic machine learning for the development of genetic medicines | NYC & Basel & Boston
@maggiemakar.bsky.social
Assist Prof of computer science @UMichigan CSE & professional email sender. Previously @MIT Machine learning. Causality. Robustness. Healthcare.
@rahulgk.bsky.social
Assistant Professor at the University of Toronto ⚒️ 🏥 Deep learning and causal inference for computational medicine
@kevinkaichuang.bsky.social
Principal Researcher in BioML at Microsoft Research. He/him/他. 🇹🇼 yangkky.github.io
@dmelis.bsky.social
Professoring at Harvard || Researching at MSR || Previously: MIT CSAIL, NYU, IBM Research, ITAM
@dvinnie.bsky.social
Researcher at Google DeepMind in London. Previously PhD at Cambridge University.
@mguindani.bsky.social
Statistician. Bayesian. Professor, Department of Biostatistics, University of California, Los Angeles. Views are my own. He/Him.
@roshanrao.bsky.social
Proteins, evolutionary models, unsupervised learning. Prev: Research Scientist MetaAI, PhD Berkeley. he/him.
@surgebiswas.bsky.social
@uwproteindesign.bsky.social
We create proteins that solve modern challenges in medicine, technology, and sustainability. • 2024 Nobel Prize in Chemistry • University of Washington, Seattle → ipd.uw.edu
@jgreener64.bsky.social
Computational chemist/structural bioinformatician working on improving molecular simulation at MRC Laboratory of Molecular Biology. jgreener64.github.io