Parent, spouse, Australian, Professor of Machine Learning in Oxford. Long Covid, trans rights, music, reggae on Fridays, AI must be good for humans, https://www.robots.ox.ac.uk/~mosb
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
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.
Also in Mastodon: https://bayes.club/@avehtari
My opinions only here.
👨🔬 RS DeepMind
Past:
👨🔬 R Midjourney 1y 🧑🎓 DPhil AIMS Uni of Oxford 4.5y
🧙♂️ RE DeepMind 1y 📺 SWE Google 3y 🎓 TUM
👤 @nwspk
Zealous modeler. Annoying statistician. Reluctant geometer. Support my writing at http://patreon.com/betanalpha. He/him.
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
Professor of Statistics and Machine Learning at UCL Statistical Science. Interested in computational statistics, machine learning and applications in the sciences & engineering.
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
Decision-making under uncertainty, machine learning theory, artificial intelligence · anti-ideological · Assistant Research Professor, Cornell
https://avt.im/ · https://scholar.google.com/citations?user=EGKYdiwAAAAJ&sortby=pubdate
AI, sociotechnical systems, social purpose. Research director at Google DeepMind. Cofounder and Chair at Deep Learning Indaba. FAccT2025 co-program chair. shakirm.com
Assistant Professor of Machine Learning
Generative AI, Uncertainty Quantification, AI4Science
Amsterdam Machine Learning Lab, University of Amsterdam
https://naesseth.github.io
Theory & practice of probabilistic programming. Current: MIT Probabilistic Computing Project; Fall '25: Incoming Asst. Prof. at Yale CS
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)
Associate Professor (UHD) at the University of Amsterdam. Probabilistic methods, deep learning, and their applications in science in engineering.
#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
ELLIS PhD student at the University of Edinburgh
https://lenazellinger.github.io/
Assistant Professor & Faculty Fellow, NYU.
AI Fellow, Georgetown University.
Probabilistic methods for robust and transparent ML & AI Governance.
Prev: Oxford, Yale, UC Berkeley.
https://timrudner.com
Machine Learning Researcher
https://alexalemi.com
https://blog.alexalemi.com
