Lars van der Laan
Ph.D. Student @uwstat; Research fellowship @Netflix; visiting researcher @UCJointCPH; M.A. @UCBStatistics - machine learning; calibration; semiparametrics; causal inference.
https://larsvanderlaan.github.io
@mfschomaker.bsky.social
Heisenberg Professor for Biostatistics at the Department of Statistics, LMU München | causal inference - missing data - HIV michaelschomaker.github.io
@calebhmiles.bsky.social
Assistant professor of biostatistics at Columbia University Casual inference, statistics, etc Pauca sed Matura
@predict-addict.bsky.social
PhD in machine learning | conformal prediction | time-series | author of bestselling Practical Guide to Applied Conformal-Prediction https://a.co/d/iHRag4i
@nolancole.bsky.social
Biostatistics phd student @University of Washington Interested in non-parametric statistics, causal inference, and science!
@dccsillag.xyz
Applied mathematician working on machine learning, statistics and compilers. Currently doing research at FGV EMAp. dccsillag.xyz
@mcknaus.bsky.social
Assistant Professor of "Data Science in Economics" at Uni Tübingen. Interested in the intersection of causal inference and so-called machine learning. Teaching material: https://github.com/MCKnaus/causalML-teaching Homepage: mcknaus.github.io
@danielawitten.bsky.social
dorothy gilford endowed chair and professor of statistics/biostatistics at university of washington, all views my own
@arxiv-stat-ml.bsky.social
source: https://arxiv.org/rss/stat.ML maintainer: @tmaehara.bsky.social
@nshejazi.bsky.social
assistant professor of biostatistics at harvard — causal inference, machine learning, and semi-parametric estimation, mostly for questions in infectious disease science and climate change avid runner, concertgoer, timezone hopper https://nimahejazi.org
@mcarone.bsky.social
Professor of Biostatistics, University of Washington School of Public Health. Affiliate Investigator, Fred Hutch Vaccine and Infectious Disease Division. Causal inference, ML, survival analysis, statistical epi, viruses and vaccine science. 🇨🇦🇮🇹🇦🇲
@athiya.bsky.social
LTI PhD at CMU on evaluation and trustworthy ML/NLP, prev AI&CS Edinburgh University, Google, YouTube, Apple, Netflix. Views are personal 👩🏻💻🇮🇩 athiyadeviyani.github.io
@moberst.bsky.social
Assistant Prof. of CS at Johns Hopkins Visiting Scientist at Abridge AI Causality & Machine Learning in Healthcare Prev: PhD at MIT, Postdoc at CMU
@amalaa.bsky.social
Assistant Professor at UC Berkeley and UCSF. Machine Learning and AI for Healthcare. https://alaalab.berkeley.edu/
@lucystats.bsky.social
Biostatistician • Assistant Prof @ Wake Forest University • former postdoc @ Hopkins Biostat • PhD @ Vandy Biostat • 🎙 Casual Inference • lucymcgowan.com
@causalscience.org
Fostering a dialogue between industry and academia on causal data science. Causal Data Science Meeting 2024: causalscience.org
@royalstatsoc.bsky.social
We're a membership body for statisticians and data professionals, promoting a world with data at the heart of understanding and decision-making.
@arxiv-stat-me.bsky.social
Statistics -- Methodology (stat.ME) source: export.arxiv.org/rss/stat.ME maintainer: @tmaehara.bsky.social
@bengolub.bsky.social
economics and computer science professor at Northwestern bengolub.net social and economic networks originally from Ukraine
@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.
@ccanonne.bsky.social
Senior Lecturer #USydCompSci at the University of Sydney. Postdocs IBM Research and Stanford; PhD at Columbia. Converts ☕ into puns: sometimes theorems. He/him.
@mattblackwell.bsky.social
data, causal inference, experiments, politics https://mattblackwell.org
@zacharylipton.bsky.social
CTO & Chief Scientific Officer @ Abridge, CMU ML prof, occasional writer, relapsing 🎷, creator of d2l.ai & approximatelycorrect.com
@jaredhuling.bsky.social
Assistant Professor of Biostatistics, University of Minnesota https://jaredhuling.org/
@richarddriley.bsky.social
Professor of Biostatistics • BMJ Deputy Chief Stats Editor • Books: "Prognosis Research in Healthcare: concepts, methods & impact" & "IPD Meta-Analysis: A Handbook for Healthcare Research.." • Websites: www.ipdma.co.uk & www.prognosisresearch.com • Whovian
@ecpolley.bsky.social
Associate Professor and Director of the Biostatistics Laboratory in the Department of Public Health Sciences at the University of Chicago
@causalab.bsky.social
Actionable #causalinference with real-world impact. We use health data to help decision makers make better decisions. We train investigators at Harvard T.H. Chan School of Public Health. Connect with CAUSALab: https://linktr.ee/causalab
@p-hunermund.com
Professor of Technology and Economic Policy | Co-founder of causalscience.org | Associate Editor at Journal of Causal Inference | Executive Team at Academy of Management TIM Division
@paperposterbot.bsky.social
posts updates from arXiv rss feeds for methodology papers in Statistics and Econometrics. Also maintains an arxiv and posts random papers from it. maintainer: @apoorvalal.com source code: https://github.com/apoorvalal/bsky_paperbot
@dennisfrauen.bsky.social
(Ellis) PhD student at LMU Munich. Interested in causal machine learning and reinforcement learning
@beenwrekt.bsky.social
Blog: https://argmin.substack.com/ Webpage: https://people.eecs.berkeley.edu/~brecht/
@aifi.bsky.social
Machine Learning | Stein Fellow @ Stanford Stats (current) | Assistant Prof @ CMU (incoming) | PhD @ MIT (prev) https://andrewilyas.com
@andrea-montanari.bsky.social
Professor, Stanford University, Statistics and Mathematics. Opinions are my own.
@ncollina.bsky.social
Penn CS PhD student and IBM PhD Fellow studying strategic algorithmic interaction. Calibration, commitment, collusion, collaboration. She/her. Nataliecollina.com
@jjcherian.bsky.social
PhD student at Stanford Statistics who dabbles in modeling elections for The Washington Post
@rdpeng.org
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
@f2harrell.bsky.social
Professor of Biostatistics Vanderbilt University School of Medicine Expert Biostatistics Advisor FDA Center for Drug Evaluation and Research https://hbiostat.org https://fharrell.com
@ledell.bsky.social
Chief Scientist @ Distributional.com @dbnlAI.bsky.social #MLSky #StatSky Founder @ datascientific.com Founder wimlds.org & co-founder rladies.org PhD @ UC Berkeley 🏡 🌈 Oakland, California.
@johandh2o.bsky.social
PhD Student at UiO, Researcher at NIPH, Fulbright Scholar, Statistician, Economist, Industrial Engineer. Web: johandh2o.github.io
@omaclaren.bsky.social
I use mathematics, computation, statistics, & machine learning to help think about biology, engineering, & other things. University of Auckland, NZ. Research: http://tinyurl.com/ojmscholar, Teaching: https://tinyurl.com/ojmteaching
@urish.bsky.social
Machine learning researcher, working on causal inference and healthcare applications
@timpmorris.bsky.social
Principal research fellow in statistical methods. Work on simulation studies, non-inferiority, missing data, estimands, covariate adjustment… He/him https://tpmorris.substack.com/ https://profiles.ucl.ac.uk/2059
@alexpghayes.com
incoming postdoc @ stanford + assistant prof @ oregon state. networks, causal inference, contagion, measurement error, #rstats. he/him https://www.alexpghayes.com
@statsepi.bsky.social
Epidemiologist + Statistician | Clinical Research Facility - University College Cork | UCC School of Public Health | #ClinicalTrials #Epidemiology #Statistics #RStats #WBE #IDSurveillance Views mine -> https://statsepi.substack.com/
@noahgreifer.bsky.social
Statistical consultant and programmer at Harvard IQSS. Author/maintainer of the #Rstats packages 'MatchIt', 'WeightIt', and 'cobalt' for causal inference, among many others | He/him ngreifer.github.io
@pwgtennant.bsky.social
Epidemiologist with an interest in causal inference methods at @universityofleeds.bsky.social. Check out my Intro to Causal Inference Course: https://www.causal.training/ #Epidemiology, #EpiSky, #CausalInference, #CausalSky, #AcademicSky