Assistant prof at JHU CS. Interested in theory of ML, privacy, cryptography. All cat pictures my own and do not represent the cats of my employer
We rate DAGs.
(If you were hoping for dogs, try here: @weratedogs.com)
Assistant Professor at the Department of Computer Science, University of Liverpool.
https://lutzoe.github.io/
The CISPA Helmholtz Center for Information Security is a German national Big Science Institution within the Helmholtz Association. We research information security in all its facets.
https://cispa.de/en/data-privacy-policy-social-media#Netiquette
Purdue University's Elmore Family School of Electrical and Computer Engineering is dedicated to advancing technology and innovation through world-class education, groundbreaking research, & real-world impact. Learn more: https://engineering.purdue.edu/ECE
America’s first research university. Leading discovery and sharing knowledge to better the world since 1876. With campuses & centers in Baltimore & around the world.
A diverse and collaborative community on the cutting edge of computing and technology within hopkinsengineer.bsky.social at the Johns Hopkins University.
cs.jhu.edu • Baltimore, MD
Applied probabilist. Probability, MCMC, optimization, information theory, TCS.
https://mchchoi.github.io/
CS Prof @ University of Illinois Chicago. Research in causal inference, machine learning, graph mining, privacy.
www.cs.uic.edu/~elena
Math Assoc. Prof. (on leave, Aix-Marseille, France)
Interest: Prob / Stat / ANT. See: https://sites.google.com/view/sebastien-darses/research?authuser=0
Teaching Project (non-profit): https://highcolle.com/
Rollins Assistant Professor of Biostatistics @EmoryRollins, PhD @JHU.edu
Interested in causal inference, missing data, machine learning, algorithmic fairness, non/semiparametrics, graphical models, etc
raziehnabi.com
AI Prof at TU Darmstadt, Founding Co-Director Hessian.AI, DFKI, AAAI/EurAI/AAIA/ELLIS Fellow, AAAI24 Ass. PC CoChair, Fmr. PC CoChair UAI, ECML PKDD, Invest. @Aleph__Alpha, Fmr. AI Column German Newspaper Welt (am Sonntag)
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
Associate professor, Chalmers University of Technology. Machine learning for decision making & healthcare. http://healthyai.se, http://fredjo.com
Machine Learning Prof @UCSanDiego, #Physics-Guided #AI, MIT TR-35 Innovator. Website: roseyu.com
Assistant professor at UIUC iSchool.
Previously at Purdue CS.
Work on Causal Data Science
https://yonghanjung.me/
Ph.D. Student at CausalML Lab, Johns Hopkins University | Causality | Machine Learning | Information Theory
https://ziwei-jiang.github.io/
postdoc @ stanford econ + incoming assistant prof @ oregon state statistics. networks, causal inference, contagion, measurement error, #rstats. he/him
https://www.alexpghayes.com
Professor at IST Austria | Machine learning, information theory | Prev: Stanford, EPFL | opinions my own
PhD student at AIML Lab, TU Darmstadt, Germany.
Teaching AI models 'genuine' (causal) reasoning | https://moritz-willig.de/
www.sites.google.com/view/mian/ | Post Doc @ Institute for Artificial Intelligence in Medicine at Uniklinikum Essen | Previously Ph.D. Student. Causal Inference and Discovery @CISPA Helmholtz Center for Information Security
Dad x 2, husband, son, brother, computational biologist, genome scientist, associate professor at la jolla institute for immunology (LJI) and UCSD https://www.lji.org/labs/ay/
AI in Bio & Health & Therapeutic Development
Bio: https://linktr.ee/mnarayan
Substack: https://blog.neurostats.org
Peek into my brain: notes.manjarinarayan.org
Previously @dynotx @StanfordMed PhD@RiceU_ECE | BS@ECEILLINOIS
🧪🧮⚕️🧬🧠🖥🤖📈✍️🩺👩📈📉
Association for Uncertainty in AI.
Upcoming conference: #uai2026 August 17-21 in Amsterdam, Netherlands! 🇳🇱
https://auai.org/uai2026
⛷️ ML Theorist carving equations and mountain trails | 🚴♂️ Biker, Climber, Adventurer | 🧠 Reinforcement Learning: Always seeking higher peaks, steeper walls and better policies.
https://ualberta.ca/~szepesva
Prof. at TU Dortmund and RC Trust | Chair for Causality | Research on Causality, Machine Learning and Information Theory | Prev. ETH Zürich, ETH AI Center, CISPA and MPI for Informatics | Website: https://www.a-marx.com
Junior professor and Inserm chair | Head of the CIPHOD team | Causal Inference + Causal Discovery + Root Cause Analysis
Assistant Professor, UW-Madison Political Science. http://www.antonstrezhnev.com
Biostatistician • Associate Prof @ Wake Forest University • former postdoc @ Hopkins Biostat • PhD @ Vandy Biostat • 🎙 Casual Inference • lucymcgowan.com
Tea drinking assistant professor of cognitive psychology at Stanford.
https://cicl.stanford.edu
Interested in all things causal modeling. Ongoing projects on causal analyses of discrimination and on causation in dynamical systems.
Econ prof at Seattle University. Book The Effect http://theeffectbook.net out now! Substack https://nickchk.substack.com/ Twitter @nickchk
Parent, spouse, Australian, Professor of Machine Learning in Oxford. Long Covid, trans rights, music, reggae, AI must be good for humans, https://www.robots.ox.ac.uk/~mosb
Postdoc researcher at IDEAL Institute in Chicago, hosted by UIC and TTIC.
My research interests are in machine learning theory, data-driven sequential decision-making, and theoretical computer science.
https://www.idanattias.com/
Associate Professor, Texas A&M University (TAMU).
Areas of interest: Reinforcement Learning, Machine Learning
PhD Student at UiO, Researcher at NIPH, Fulbright Scholar, Statistician, Economist, Industrial Engineer. Web: johandh2o.github.io
Assistant Professor at BU CDS
EconCS | Theory of CS | MD+AI+DS4SG | MD4SG co-founder
Previously Columbia, UW, Oberlin. Views are mine alone.
www.kiragoldner.com
Professor, UW Biology / Santa Fe Institute
I study how information flows in biology, science, and society.
Book: *Calling Bullshit*, http://tinyurl.com/fdcuvd7b
LLM course: https://thebullshitmachines.com
Corvids: https://tinyurl.com/mr2n5ymk
he/him
"The Causal Guy" http://causalpython.io
Author || Advisor || Educator
Host at http://CausalBanditsPodcast.com
Causal ML Tutor @ Uni of Oxford
CausalSky: https://bsky.app/profile/did:plc:imz3rf35poonl7yxt7bogui4/feed/aaamrclcu3tfa
statistics & causal inference
assoc prof of statistics & data science at Carnegie Mellon
https://www.ehkennedy.com/
interested in causality, machine learning, nonparametrics, public policy, etc
Associate Professor of Strategy & Innovation | Co-founder of causalscience.org | Associate Editor at Journal of Causal Inference | Executive Team at Academy of Management TIM Division
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/
https://www.vita-group.space/ 👨🏫 UT Austin ML Professor (on leave)
https://www.xtxmarkets.com/ 🏦 XTX Markets Research Director (NYC AI Lab)
Superpower is trying everything 🪅
Newest focus: training next-generation super intelligence - Preview above 👶
CS Faculty at UCF (SafeRR AI Lab), previous @UMD @ARL@IITK
Interested in Generative AI Alignment, RL, Optimization methods, Robotics, LLMs
Professor at UT Austin. Research in ML & Optimization. Always rethinking how I teach. Amateur accordion player. Committed bike commuter. Online classes in English & Greek. https://caramanis.github.io/
Machine learning researcher, working on causal inference and healthcare applications
🎓 CS Prof at UCLA
🧠 Researching reasoning and learning in artificial intelligence: tactable deep generative models, probabilistic circuits, probabilistic programming, neurosymbolic AI
https://web.cs.ucla.edu/~guyvdb/
Theoretical Computer Science professor @ U. of Michigan-Ann Arbor.
Opinions are mine and may evolve over time.
repost ≠ endorsement.
Policy: I don't interact with anonymous profiles.
Join AAUP.
he/him/his.
Computer science, math, machine learning, (differential) privacy
Researcher at Google DeepMind
Kiwi🇳🇿 in California🇺🇸
http://stein.ke/
Assistant Professor of Biostatistics at Columbia.
I study causal inference, graphical models, machine learning, algorithmic (un)fairness, social + environmental determinants of health, etc. Opinions my own.
http://www.dmalinsky.com
Machine Learner by day, 🦮 Statistician at ❤️
In search of statistical intuition for modern ML & simple explanations for complex things👀
Interested in the mysteries of modern ML, causality & all of stats. Opinions my own.
https://aliciacurth.github.io
Full prof at Saarland University & part of the Amsterdam Machine Learning Lab at the University of Amsterdam | ELLIS scholar | #causality #causalML anything #causal |
🇮🇹🇸🇮 in 🇩🇪🇳🇱
#UAI2026 general chair
https://saramagliacane.github.io/
causal ml; ai+society; social media, comp social science. having fun.. my opinions. he/him. http://hci.social/@emrek
Professor and Head of Machine Learning Department at Carnegie Mellon. Board member OpenAI. Chief Technical Advisor Gray Swan AI. Chief Expert Bosch Research.
CS Prof at Brown University, PI of the GIRAFFE lab, former AI Policy Advisor in the US Senate, co-chair of the ACM Tech Policy Subcommittee on AI and Algorithms.
PhD at MIT CSAIL '23, Harvard '16, former Google APM. Dog mom to Ducki.
Associate Professor in EECS at MIT. Neural nets, generative models, representation learning, computer vision, robotics, cog sci, AI.
https://web.mit.edu/phillipi/
Machine learning researcher. Professor in ML department at CMU.
Assistant Prof at Penn CIS | Postdoc at Microsoft Research | PhD from UT Austin CS | Co-founder LeT-All
Working at microsoft research health futures. Interested in causal representation learning and generative modelling applied to medical data.
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.
assistant prof at USC Data Sciences and Operations and Computer Science; phd Cornell ORIE.
data-driven decision-making, operations research/management, causal inference, algorithmic fairness/equity
bureaucratic justice warrior
angelamzhou.github.io
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/
Research Scientist at GDM. Statistician. Mostly work on Responsible AI. Academia-industry flip-flopper.
machine learning and artificial intelligence | University of Chicago / Google
Assistant Prof. of CS at Johns Hopkins
Visiting Scientist at Abridge AI
Causality & Machine Learning in Healthcare
Prev: PhD at MIT, Postdoc at CMU
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.
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
AI @ OpenAI, Tesla, Stanford
Associate Professor of Electrical Engineering, EPFL.
Amazon Scholar (AGI Foundations). IEEE Fellow. ELLIS Fellow.
Researcher @MSFTResearch; Prof @UWMadison (on leave); learning in context; thinking about reasoning; babas of Inez Lily.
https://papail.io
Distinguished Scientist at Google. Computational Imaging, Machine Learning, and Vision. Posts are personal opinions. May change or disappear over time.
http://milanfar.org
Illuminating math and science. Supported by the Simons Foundation. 2022 Pulitzer Prize in Explanatory Reporting. www.quantamagazine.org
Information theory, probability, statistics. Churchill Professor of Mathematics of Information @UofCambridge: dpmms.cam.ac.uk/person/ik355/ 🧮 #MathSky 🧪 #Science
[used to be @yiannis_entropy at the other place]
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 🌈
full-time ML theory nerd, part-time AI-non enthusiast
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
ML for healthcare and health equity. Assistant Professor at UC Berkeley and UCSF.
https://irenechen.net/
Mathematics professor at Collège de France and fellow of Trinity College Cambridge.
economics and computer science professor at Northwestern
bengolub.net
social and economic networks
originally from Ukraine
So far I have not found the science, but the numbers keep on circling me.
Views my own, unfortunately.
Assistant Professor @PrincetonCS
Research: Theoretical Computer Science, Optimization, Algorithmic Statistics.
Senior Lecturer #USydCompSci at the University of Sydney. Postdocs IBM Research and Stanford; PhD at Columbia. Converts ☕ into puns: sometimes theorems. He/him.
Assistant Prof of CS at the University of Waterloo, Faculty and Canada CIFAR AI Chair at the Vector Institute. Joining NYU Courant in September 2026. Co-EiC of TMLR. My group is The Salon. Privacy, robustness, machine learning.
http://www.gautamkamath.com
AI professor at Caltech. General Chair ICLR 2025.
http://www.yisongyue.com
web: http://maxim.ece.illinois.edu
substack: https://realizable.substack.com
UC Berkeley Professor working on AI. Co-Director: National AI Institute on the Foundations of Machine Learning (IFML). http://BespokeLabs.ai cofounder
EECS Prof @UMich, Research on the Foundations of ML+RL+LLM
https://sota.engin.umich.edu/
Associate Professor at Princeton
Machine Learning Researcher
