Richard Michael
PhD student at University of Copenhagen, @DIKU, @KU_BioML group, DDSA fellow.
@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
@jwenger.bsky.social
Postdoctoral Research Scientist in Statistics at Columbia University
@nathanaelbosch.de
PhD student at the University of Tübingen and the Max Planck Institute for Intelligent Systems. Working on probabilistic numerics, differential equations, filtering and smoothing, and recently automl for time series forecasting. nathanaelbosch.github.io
@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/
@joannasliwa.bsky.social
ELLIS & IMPRS-IS PhD student at University of Tübingen Working on Bayesian Deep Learning in Philipp Hennig's group Website: https://joannasliwa.github.io
@timwei.land
PhD student @ ELLIS, IMPRS-IS. Working on physics-informed ML and probabilistic numerics at Philipp Hennig's group in Tübingen. https://timwei.land
@deshwalaryan.bsky.social
Bayesian Optimization and Gaussian Processes University of Minnesota Web: https://aryandeshwal.github.io/
@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
@pnkraemer.bsky.social
Probabilistic numerics, differentiable linear algebra, and a healthy dose of figure-making. https://pnkraemer.github.io/
@fxbriol.bsky.social
Associate Professor at UCL Statistical Science. Interested in computational statistics, machine learning and applications in the sciences & engineering.
@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.
@maosbot.bsky.social
Parent, spouse, Australian, Professor of Machine Learning in Oxford. Bayesian ML, Long Covid, trans rights, photos of dog, AI must be good for humans, https://www.robots.ox.ac.uk/~mosb
@betanalpha.bsky.social
Zealous modeler. Annoying statistician. Reluctant geometer. Support my writing at http://patreon.com/betanalpha. He/him.
@jeffruffolo.bsky.social
Protein Design / ML @ Profluent Bio | Molecular Biophysics PhD @ Johns Hopkins
@astralcodexten.com.web.brid.gy
P(A|B) = [P(A)*P(B|A)]/P(B), all the rest is commentary. Click to read Astral Codex Ten, by Scott Alexander, a […] [bridged from astralcodexten.com on the web: https://fed.brid.gy/web/astralcodexten.com ]
@alexshauser.bsky.social
Assoc Prof University of Copenhagen - comp. biology, evolutionary bioinformatics, personalised medicin & ML on #GPCRs
@iaugenstein.bsky.social
Professor at the University of Copenhagen. Explainable AI, Natural Language Processing, ML. Head of copenlu.bsky.social lab. #NLProc #NLP #XAI http://isabelleaugenstein.github.io/
@yoshuabengio.bsky.social
Full professor at UdeM, Founder and Scientific Advisor at Mila - Quebec AI Institute, A.M. Turing Award Recipient. Working towards the safe development of AI for the benefit of all. Website and blog: https://yoshuabengio.org/
@khoulahan.bsky.social
Assistant Professor @ McMaster University. Studying the impact of inherited DNA variants on tumour evolution.
@jyim.bsky.social
PhD candidate at MIT CSAIL. Generative models, protein design. Ex: DeepMind, Microsoft, Instagram, Johns Hopkins University. Website: https://people.csail.mit.edu/jyim/ X: https://x.com/json_yim
@ml4science.bsky.social
Cluster of Excellence "Machine Learning: New Perspectives for Science" at University of Tübingen, Germany. Blog: https://www.machinelearningforscience.de/
@mackelab.bsky.social
We build probabilistic #MachineLearning and #AI Tools for scientific discovery, especially in Neuroscience. Probably not posted by @jakhmack.bsky.social. 📍@ml4science.bsky.social, Tübingen, Germany
@jdijkman.bsky.social
Infusing statistical physics with machine learning to describe molecular fluids. PhD Candidate at UvA with Max Welling, Jan-Willem van de Meent and Bernd Ensing.
@rohangorantla.bsky.social
Developing ML methods for Drug Discovery @ Novartis 🧬💻 | prev: PhD student @ University of Edinburgh with Toni Mey
@samblouir.bsky.social
Thanks for coming to “Foundation Models for Biological Discoveries” (FMs4Bio) @ AAAI 2025!
@sulinliu.bsky.social
Postdoc at MIT. Generative models, inference, AI for science. Prev: Princeton, Meta, NUS. liusulin.github.io
@dvinnie.bsky.social
Researcher at Google DeepMind in London. Previously PhD at Cambridge University.
@embl.org
The European Molecular Biology Laboratory drives visionary basic research and technology development in the life sciences. www.embl.org
@sloeschcke.bsky.social
Working on Efficient Training, Low-Rank Methods, and Quantization. PhD at the University of Copenhagen 🇩🇰 Member of @belongielab.org, Danish Data Science Academy, and Pioneer Centre for AI 🤖 🔗 sebulo.github.io/
@iclr-conf.bsky.social
International Conference on Learning Representations https://iclr.cc/
@blog.neurips.cc.web.brid.gy
[bridged from https://blog.neurips.cc/ on the web: https://fed.brid.gy/web/blog.neurips.cc ]
@natureportfolio.nature.com
Nature Portfolio’s high-quality products and services across the life, physical, chemical and applied sciences is dedicated to serving the scientific community.
@jesfrellsen.bsky.social
Associate Professor of Machine Learning and Signal Processing, Technical University of Denmark (DTU) https://frellsen.org
@aaronschein.bsky.social
Assistant Professor of Statistics & Data Science at UChicago Topics: data-intensive social science, Bayesian statistics, causal inference, probabilistic ML Proud “golden retriever” 🦮
@mvdw.bsky.social
Associate Professor in Machine Learning at the University of Oxford. Interested in automatic inductive bias selection using Bayesian tools.
@jeffclune.com
Professor, Computer Science, University of British Columbia. CIFAR AI Chair, Vector Institute. Senior Advisor, DeepMind. ML, AI, deep RL, deep learning, AI-Generating Algorithms (AI-GAs), open-endedness.
@roydanroy.bsky.social
Research Director, Founding Faculty, Canada CIFAR AI Chair @VectorInst. Full Prof @UofT - Statistics and Computer Sci. (x-appt) danroy.org I study assumption-free prediction and decision making under uncertainty, with inference emerging from optimality.
@bayesflow.org
Amortized Bayesian Workflows in Python. 🎲 Post author sampled from a multinomial distribution, choices ⋅ @marvinschmitt.bsky.social ⋅ @paulbuerkner.com ⋅ @stefanradev.bsky.social 🔗GitHub github.com/bayesflow-org/bayesflow 💬Forum discuss.bayesflow.org
@westberglab.com
Assistant Professor at Aarhus University, Denmark | biophysical chemistry PhD | into chembio, synbio, protein design, photochem, microscopy | 2018-2022 at Stanford Bio-X | westberglab.com
@moalquraishi.bsky.social
MLing biomolecules en route to structural systems biology. Asst Prof of Systems Biology @Columbia. Prev. @Harvard SysBio; @Stanford Genetics, Stats.
@francesarnold.bsky.social
Engineer/scientist, Nobel Prize in Chemistry 2018 I love evolution, enzymes, protein engineering, AI Linus Pauling Professor at Caltech
@lindorfflarsen.bsky.social
Protein and coffee lover, father of two, professor of biophysics and sudo scientist at the Linderstrøm-Lang Centre for Protein Science, University of Copenhagen 🇩🇰
@rosettacommons.bsky.social
Rosetta Commons is the central hub for hundreds of developers and scientists from ~100 universities and laboratories to contribute and share the Rosetta source code. Rosetta Commons members develop software improvements to solve their unique queries.
@proteinsociety.bsky.social
A global community of researchers dedicated to the understanding of proteins.
@lkseiling.bsky.social
DE/EN. 📍 Potsdam / Berlin coordination of @dsa40collaboratory.bsky.social, various research at @weizenbauminstitut.bsky.social among other things: http://zusammenfuergleichstellung.de