researching viral pathogen genomics at @lshtm.bsky.social | theo.io / sandersonlab.org
Associate Professor of Statistics and Data Science at Cornell University.
https://www.danielrkowal.com/
Post-doc @ VU Amsterdam, prev University of Edinburgh.
Neurosymbolic Machine Learning, Generative Models, commonsense reasoning
https://www.emilevankrieken.com/
AI Lead at Axiomatic AI. Former Extropic Staff Scientist, MentenAI Quantum Computing Researcher, EPFL QML researcher, ICFO QML PhD candidate.
jax posting
https://lockwo.github.io/
Bayesian and Julia software developer @ PlantingSpace
PhD student @ Univ. Helsinki & FCAI
MSc @ Aalto
Postdoc @univie.ac.at
Researches the Milky Way & star clusters with machine learning
Founded the Astronomy feeds (@astronomy.blue)
🏳️🌈 🏳️⚧️ (she/her), Ⓥ
Website: https://emily.space
GitHub: https://github.com/emilyhunt
Architects of the digital world since 1967 | A leading CS teaching and research unit in the Nordics | #ComputerScience and #DataScience
Theoretical systems neuroscientist. Author of “The Spike: An Epic Journey Through the Brain in 2.1 Seconds”: https://tinyurl.com/ymwy9jrh
Lab: https://humphries-lab.org
Essays on the brain: https://drmdhumphries.medium.com/
Associate Prof. in ML & Statistics at NUS 🇸🇬
MonteCarlo methods, probabilistic models, Inverse Problems, Optimization
https://alexxthiery.github.io/
Research fellow @OxfordStats @OxCSML, spent time at FAIR and MSR
Former quant 📈 (@GoldmanSachs), former former gymnast 🤸♀️
My opinions are my own
🇧🇬-🇬🇧 sh/ssh
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
Assistant professor in Machine Learning and Theoretical Neuroscience. Generative modeling and memory. Opinionated, often wrong.
Posting about the One World Approximate Bayesian Inference (ABI) Seminar, details at https://warwick.ac.uk/fac/sci/statistics/news/upcoming-seminars/abcworldseminar/
Prof at the University of British Columbia. Research in statistics, ML, and AI for science. Views are my own. https://charlesm93.github.io./
ELLIS PhD Student @ JKU supervised by Sepp Hochreiter
Working on Predictive Uncertainty in ML
ML + Cells + Proteins. PI @ AITHYRA https://alextong.net
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/
Tenured Researcher @INRIA, Ockham team. Teacher @Polytechnique
and @ENSdeLyon
Machine Learning, Python and Optimization
ML + Physics + Health at . Exploring the interaction between scientific and ML models.
AI for Science, deep generative models, inverse problems. Professor of AI and deep learning @universitedeliege.bsky.social. Previously @CERN, @nyuniversity. https://glouppe.github.io
#AI4Science #CompNeuro #NeuroAI #SBI
www.mackelab.org @mackelab.bsky.social
· Prof Uni Tuebingen ML4Science BCCN tue.ai
· Adjunct MPI IS · Fellow ellis.eu
· currently hiring postdocs and PhD students
· sometimes goes for a run
Professor of Machine Learning and Inference, Edinburgh Informatics, Formerly Amazon Scholar. Opinions are my own. Also https://homepages.inf.ed.ac.uk/imurray2/ and https://mastodon.social/@imurray and https://x.com/driainmurray
AI + Astro/Physics. Assistant Prof at Cambridge.
astroautomata.com/
Professor for AI/ML Methods in Tübingen. Posts about Probabilistic Numerics, Bayesian ML, AI for Science. Computations are data, Algorithms make assumptions.
Professor of Statistics and Machine Learning at UCL Statistical Science. Interested in computational statistics, machine learning and applications in the sciences & engineering.
Associate Professor in Machine Learning at the University of Oxford.
Interested in automatic inductive bias selection using Bayesian tools.
Academy Professor in computational Bayesian modeling at Aalto University, Finland. Bayesian Data Analysis 3rd ed, Regression and Other Stories, and Active Statistics co-author. #mcmc_stan and #arviz developer.
Web page https://users.aalto.fi/~ave/
VP of AI Research, Principal Scientist @ EIT Oxford | ex-Director @ DeepMind Building models to accelerate fundamental sciences and medicine.
Opinions my own.
https://danilorezende.com/
Academy Research Fellow at the Dept. of Computer Science, Aalto University, Finland. Affiliated with the Finnish Center for Artificial Intelligence.
Website: http://bharti-ayush.github.io
Researcher in machine learning
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.
junior fellow at @Harvard.edu, incoming prof at @HSEAS and @Kempnerinstitute.bsky.social studying machine learning and its applications to nature and the sciences
Secular Bayesian.
Professor of Machine Learning at Cambridge Computer Lab
Talent aficionado at http://airetreat.org
Alum of Twitter, Magic Pony and Balderton Capital
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)
Assistant Prof in Prob ML @ KTH 🇸🇪
WASP Fellow & ELLIS Member
Ex: Aalto Uni 🇫🇮, TU Graz 🇦🇹, originally 🇩🇪.
—
https://trappmartin.github.io/
—
Reliable ML | UQ | Bayesian DL | tractability & PCs
Associate Professor in Machine Learning, Aalto University. ELLIS Scholar.
http://arno.solin.fi
💡 PhD candidate @ Heidelberg University.
🌱 AI for science - simulation-based inference, robust deep learning & cognitive modeling.
Researcher at appliedAI Institute for Europe.
Working on simulation-based inference and responsible ML
Community-maintained simulation-based inference (SBI) toolkit in PyTorch:
• NPE, NLE & NRE
• amortized and sequential inference
• wide range of diagnostics
Posts written by @deismic.bsky.social & @janboelts.bsky.social.
🔗 https://github.com/sbi-dev/sbi
Blog: https://argmin.substack.com/
Webpage: https://people.eecs.berkeley.edu/~brecht/
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
Prof of machine learning at University of Helsinki. Interested in (differential) privacy and open source software.
Assistant Professor at Rensselaer Polytechnic Institute (RPI)
Bayesian | Computational guy | Name dropper | Deep learner | Book lover
Opinions are my own.
Amortized Bayesian Workflows in Python.
🎲 Post author sampled from a multinomial distribution, choices
⋅ @marvin-schmitt.com
⋅ @paulbuerkner.com
⋅ @stefanradev.bsky.social
🔗 GitHub github.com/bayesflow-org/bayesflow
💬 Forum discuss.bayesflow.org
Director Data Science Institute @UWMadison, Professor of Physics,
EiC @MLSTjournal. Physics, stats/ML/AI, open science.
Full Professor of Computational Statistics at TU Dortmund University
Scientist | Statistician | Bayesian | Author of brms | Member of the Stan and BayesFlow development teams
Website: https://paulbuerkner.com
Opinions are my own
PhD student at Aalto University 🇫🇮
Probabilistic ML, amortized inference.
See more at huangdaolang.com
Assoc. Prof. of Machine & Human Intelligence | Univ. Helsinki & Finnish Centre for AI (FCAI) | Bayesian ML & probabilistic modeling | https://lacerbi.github.io/
⛵️ Research Resident @ Midjourney
🇪🇺 Member @ellis.eu
🤖 Generative NNs, Deep Learning, ProbML, Simulation Intelligence
🎓 PhD+MSc Computer Science, MSc Psychology
🏡 https://marvin-schmitt.com
official Bluesky account (check username👆)
Bugs, feature requests, feedback: support@bsky.app
