statistician • associate prof • team lead health data science and head methods research program at julius center • director ai methods lab, umc utrecht, netherlands • views and opinions my own

Statistician. Associate prof. at NYU Grossman Department of Population Health. Causal inference, machine learning, and semiparametric estimation. https://idiazst.github.io/website/

https://miguelhernan.org/ Using health data to learn what works. Making #causalinference less casual. Director, @causalab.bsky.social Professor, @hsph.harvard.edu Methods Editor, Annals of Internal Medicine @annalsofim.bsky.social

Biostatistician, London School of Hygiene & Tropical Medicine. Blogging at thestatsgeek.com

biostatistician + biostatistics phd student at the university of washington. learning + writing about better ways to conduct research. #rstats, #dataviz, causal inference. she/her. blog: https://www.khstats.com/

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

Professor of biostatistics at the University of Oslo. Causal inference, survival/event history analysis, jmgran.github.io

Statistician and metascientist. Professor of biometrics at LMU Munich Medical and Mathematical Faculties, committed to open science, member of the Munich Center of Machine Learning. Opinions are mine.

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

Heisenberg Professor for Biostatistics at the Department of Statistics, LMU München | causal inference - missing data - HIV michaelschomaker.github.io

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