Thomas Nagler

https://www.slds.stat.uni-muenchen.de

Researcher @MSFTResearch; Prof @UWMadison (on leave); learning in context; thinking about reasoning; babas of Inez Lily. https://papail.io

Prof at the University of British Columbia. Research in statistics, ML, and AI for science. Views are my own. https://charlesm93.github.io./

Assistant Professor of Statistics @ ESSEC Business School

AITHYRA is a new dynamic research institute for biomedical AI in Vienna. AITHYRA seeks to build Europe’s premier institute for AI-driven biological and medical research, uniting computer scientists, engineers, and biologists in a collaborative environment.

R, data science, dataviz, maps, experimental design, raytracing. Developer of rayshader, rayrender, and the rayverse | PhD in Physics from Johns Hopkins | Penn

Professor of Statistics, Monash University, Australia. FAA, FASSA. Interested in #forecasting, #rstats, #statistics. he/him http://robjhyndman.com

Associate professor of statistics and data science at the University of St Thomas. Into data visualization and reproducible research, obsessed with R. pronoun.is/she website: amelia.mn mastodon: @vis.social/@amelia

Founding list[float] engineer. Recsys. Personalization. Infra. Systems. Normcore code. Nutella. Vectors. Words. Vibes. Bad puns (soon). https://vickiboykis.com/what_are_embeddings/

programming and exclamation marks blog: jvns.ca zines: wizardzines.com

Software Engineer at Posit, PBC https://fosstodon.org/@gaborcsardi https://github.com/gaborcsardi

Director of Engineering at Heap. #rstats fan. Dad x2. He/him

tada⬢science ⬡⬡ ex(Posit/RStudio, ThinkR, Mango Solutions) ⬡⬡ role(Data Scientist, Software Engineer, R Expert) ⬡⬡

Professor of Statistics and Data Sciences UT Austin | Prev JHUBiostat | R Programming for Data Science | Simply Stats Blog | Not So Standard Deviations | The Effort Report

Code, Data, Analysis, Teaching, Running, Breadmaking ... https://dirk.eddelbuettel.com "God doesn't know, and the devil isn't telling." xkcd.com/2867/

We make free, open-source software for data scientists like the RStudio IDE. We're formerly known as RStudio. You can always download our open-source IDE here. https://posit.co/download/rstudio-desktop/

former 🥑 dev advocate @rstudio, 🏀 hoop head, data-viz lover, gnashgab, blatherskite, #rstats, doggos, and horses

Columnist and chief data reporter the Financial Times | Stories, stats & scatterplots | john.burn-murdoch@ft.com 📝 ft.com/jbm

Professor of Biostatistics Vanderbilt University School of Medicine Expert Biostatistics Advisor FDA Center for Drug Evaluation and Research https://hbiostat.org https://fharrell.com

Em. Prof., UC Davis. Various awards, incl. book, teaching, public service. Many books, latest The Art of Machine Learning (uses qeML pkg). Former Editor in Chief, the R Journal. Views mine. heather.cs.ucdavis.edu/matloff.html

Code hacker, number cruncher, #rstats user, board gamer, road racer, plant eater, bass slapper. I like big bikes and I cannot lie. #cargobike Coming to you from AUS / BNE. https://milesmcbain.com

https://github.com/lionel-

she/her professor at duke university + developer educator at posit cat videos = instant smiles https://mine-cr.com https://fosstodon.org/@minecr

Writing modeling packages at @posit.co (née RStudio). Opinions are my own. https://max-kuhn.org/

$ /usr/bin/kevin: valid on disk $ /usr/bin/kevin: satisfies its Designated Requirement Software engineer at Posit. #rstats abjurations and conjurations.

Building tools for R users, these days mostly in Rust 🦀 https://blog.davisvaughan.com https://github.com/DavisVaughan

Statistics professor, #rstats user and reluctant #python user. I love #quarto, #quilting, #crossstitch, #snark, and #dogs. Research in #forensics, #visualization and #datavis, and #reproduceableresearch.

Biostatistician • Associate Prof @ Wake Forest University • former postdoc @ Hopkins Biostat • PhD @ Vandy Biostat • 🎙 Casual Inference • lucymcgowan.com

Professor. Statistical graphics, EDA, data science, open source and R. Gender equity. she/her

Visualisation and graphics @posit.co Classic Generative Art Weirdo using 🖤 and R: http://thomaslinpedersen.art and http://deca.art/thomasp85 he/him

Software engineer @posit.co, humane #rstats

Looking for my #rstats friends on ALL the platforms...

Building data science tools @posit.co, #rstats, parenthood ✨📊✨

R, data, 🐕, 🍸, 🌈. He/him.

MIT PhD Student - ML for biomolecules - https://hannes-stark.com/

Working towards the safe development of AI for the benefit of all at Université de Montréal, LawZero and Mila. A.M. Turing Award Recipient and most-cited AI researcher. https://lawzero.org/en https://yoshuabengio.org/profile/

Gradient surfer at UCL. FR, EN, also trying ES. 🇹🇼🇨🇦🇬🇳🇺🇸🇩🇴🇫🇷🇪🇸🇬🇧🇿🇦. Also on Twitter.

Researcher trying to shape AI towards positive outcomes. ML & Ethics +birds. Generally trying to do the right thing. TIME 100 | TED speaker | Senate testimony provider | Navigating public life as a recluse. Former: Google, Microsoft; Current: Hugging Face

Host of Lex Fridman Podcast. Interested in robots and humans.

XGBoost maximalist

AI @ OpenAI, Tesla, Stanford

Princeton computer science prof. I write about the societal impact of AI, tech ethics, & social media platforms. https://www.cs.princeton.edu/~arvindn/ BOOK: AI Snake Oil. https://www.aisnakeoil.com/

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

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

Professor of Statistics @ ESSEC Business School Asia-Pacific campus Singapore 🇸🇬 https://pierrealquier.github.io/ Previously: RIKEN AIP 🇯🇵 ENSAE Paris 🇫🇷 🇪🇺 UCD Dublin 🇮🇪 🇪🇺 Random posts about stats/maths/ML/AI, poor jokes & birds photo 🌈

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]

Bayesian statistics, Gaussian processes, and all things ML. Senior Applied Scientist at Amazon and developer of GPJax.

Machine Learning PhD Student @ Blei Lab & Columbia University. Working on probabilistic ML | uncertainty quantification | LLM interpretability. Excited about everything ML, AI and engineering!

⛵️ Research Resident @ Midjourney 🇪🇺 Member @ellis.eu 🤖 Generative NNs, Deep Learning, ProbML, Simulation Intelligence 🎓 PhD+MSc Computer Science, MSc Psychology 🏡 https://marvin-schmitt.com

Research scientist at FAIR NY ❤️ LLMs + Information Theory. Previously, PhD at UoAmsterdam, intern at DeepMind + MSRC.

Theory & practice of probabilistic programming. Current: MIT Probabilistic Computing Project; Fall '25: Incoming Asst. Prof. at Yale CS

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/

Machine Learning Professor https://cims.nyu.edu/~andrewgw

MCML PhD student @ LMU Munich Working on causal & fair ML Interested in social science and the book of why He/him

Assistant Professor "AutoML and Optimization" @ Lamarr institute and @tu-dortmund.bsky.social. Working on #AutoML, #HPO, #TabularData #OpenML #Benchmarking | https://matthiasfeurer.de | https://automl.cs.tu-dortmund.de

Assistant Professor of Statistics at WU Vienna | Before: Postdoc at the University of Copenhagen | PhD from the University of Zurich | Interested in causal inference with complex data structures and statistical software

San Diego Dec 2-7, 25 and Mexico City Nov 30-Dec 5, 25. Comments to this account are not monitored. Please send feedback to townhall@neurips.cc.

statistics, science, software https://www.zeileis.org/

PhD Student @ LMU Munich Munich Center for Machine Learning (MCML) Research in Interpretable ML / Explainable AI

PhD candidate at LMU Munich | Munich Center for Machine Learning (MCML) | https://sandylaker.github.io | Open to work.

http://www.julian-rodemann.de | PhD student in statistics @LMU_Muenchen | currently @HarvardStats

[bridged from https://blog.neurips.cc/ on the web: https://fed.brid.gy/web/blog.neurips.cc ]

University of Cambridge and Max Planck Institute for Intelligent Systems I'm interested in amortized inference/PFNs/in-context learning for challenging probabilistic and causal problems. https://arikreuter.github.io/

PhD Student @ LMU Munich Munich Center for Machine Learning (MCML)

Manchester Centre for AI FUNdamentals | UoM | Alumn UCL, DeepMind, U Alberta, PUCP | Deep Thinker | Posts/reposts might be non-deep | Carpe espresso ☕

Faculty Fellow and Assistant Professor at NYU's Center of Data Science

The MCML is a joint ­research initiative of LMU München and TU München. It is institutionally funded by the Federal Ministry of Education and Research and the Free State of Bavaria.

PhD Candidate at Institute of AI in Management, LMU Munich causal machine learning, causal inference

Machine Learning Researcher, @LMU Munich, MCML Interested in probabilistic deep learning, generative models, and trustworthy ML. minare.github.io

Professor @UCLA, Research Scientist @ByteDance | Recent work: SPIN, SPPO, DPLM 1/2, GPM, MARS | Opinions are my own

Blog: https://argmin.substack.com/ Webpage: https://people.eecs.berkeley.edu/~brecht/

stealth // Gemini RL+inference @ Google DeepMind // Conversational AI @ Meta // RL Agents @ EA // ML+Information Theory @ MIT+Harvard+Duke // Georgia Tech PhD 📍{NYC, SFO, YYZ} 🔗 https://beirami.github.io/

Professor and Head of Machine Learning Department at Carnegie Mellon. Board member OpenAI. Chief Technical Advisor Gray Swan AI. Chief Expert Bosch Research.

I work on AI at OpenAI. Former VP AI and Distinguished Scientist at Microsoft.

Machine learning researcher. Professor in ML department at CMU.

work on theoretical foundations of AI, MLLM reliability/Eval, optimization, high dimensional probability/statistics, AI for science/healthcare; director of center on AIF4S @USC 🚲🏔️🥾🏊‍♂️

Researcher in machine learning

Prof at EPFL AI • Climbing

Researcher in computational mathematics Theory of deep learning, optimal transport, optimization EPFL

Professor at University of Toronto. Research on machine learning, optimization, and statistics.

Sr Research Scientist at Google DeepMind, Toronto. Member, Mila. Adjunct, McGill CS. PhD Machine Learning & MASt Applied Math (Cambridge), BSc Math (Warwick). gkdz.org

Professor of CS and Math @ KAUST. Interested in Optimization for Machine Learning. Federated learning guru. Likes 🏓🏋️‍♂️🎾🏐⛷️⛸️🧘‍♂️🤿🎹🎸✈️🏔️📷☀️🐈🍅🥚☕️

Professor of Applied Mathematics at UCLA. Interested in deep learning and optimization.

Posting about the One World Approximate Bayesian Inference (ABI) Seminar, details at https://warwick.ac.uk/fac/sci/statistics/news/upcoming-seminars/abcworldseminar/

Associate Prof @ LMU Munich PI @ Munich Center for Machine Learning Ellis Member Associate Fellow @ relAI ----- https://davidruegamer.github.io/ | https://www.muniq.ai/ ----- BNNs, UQ in DL, DL Theory (Overparam, Implicit Bias, Optim), Sparsity

Computer science professor at Carnegie Mellon. Researcher in machine learning. Algorithmic foundations of responsible AI (e.g., privacy, uncertainty quantification), interactive learning (e.g., imitation/reinforcement learning). https://zstevenwu.com/

(Tab)PFNs, TrivialAugment etc.

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

AI and cognitive science, Founder and CEO (Geometric Intelligence, acquired by Uber). 8 books including Guitar Zero, Rebooting AI and Taming Silicon Valley. Newsletter (100k subscribers): garymarcus.substack.com

CNRS research director at Sorbonne University in Paris. Interested in black-box optimization (theory, benchmarking, applications, learning,...). ERC project dynaBBO on dynamic black-box optimization algorithms (consolidator grant)

Associate Professor in Machine Learning at the University of Oxford. Interested in automatic inductive bias selection using Bayesian tools.

Safe and robust AI/ML, computational sustainability. Former President AAAI and IMLS. Distinguished Professor Emeritus, Oregon State University. https://web.engr.oregonstate.edu/~tgd/

Research & code: Research director @inria ►Data, Health, & Computer science ►Python coder, (co)founder of scikit-learn, joblib, & @probabl.bsky.social ►Sometimes does art photography ►Physics PhD