Iván Díaz
Statistician. Associate prof. at NYU Grossman Department of Population Health. Causal inference, machine learning, and semiparametric estimation.
https://idiazst.github.io/website/
@jamesheathers.bsky.social
please science correctly if you do i will buy you a small cake and we can be friends the book: forensicmetascience.com
@dingdingpeng.the100.ci
Personality psych & causal inference @UniLeipzig. I like all things science, beer, & puns. Even better when combined! Part of http://the100.ci, http://openscience-leipzig.org
@jlrohmann.bsky.social
PhD | Epidemiology, Applied #CausalInference, #PublicHealth, Stroke research, improving quality, peer review, higher ed & research assessment reform @ Charité in #Berlin Likes: improving science & improv comedy #EpiSky #Epidemiology #HigherEd #AcademicSky
@eurocim.bsky.social
The European Causal Inference Meeting - causal inference in health, economic and social science.
@lesslikely.com
Agnostic statistician (frequentist, bayesian, likelihoodist, fiducial) | Posts about statistics in medicine at http://lesslikely.com | | #StatsTwitter • #EpiTwitter • #RStats
@nickwillyamz.bsky.social
Senior Data Analyst at Columbia University Epidemiology // Incoming Biostatistics PhD student at UC Berkeley
@kararudolph.bsky.social
Associate professor at Columbia University Epidemiology, causal inference, addiction medicine https://kararudolph.github.io/
@kellyvanlancker.bsky.social
Postdoc at Ghent University. Interested in causal inference, clinical and pragmatic trials. Kellyvanlancker.com
@berkeleyctml.bsky.social
CTML, at UC Berkeley, is an interdisciplinary research center for advancing, implementing, and disseminating methodology to address problems arising in public health and clinical medicine. https://linktr.ee/ctml_ucberkeley
@raziehnabi.bsky.social
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
@hanowell.me
Lover of event history analysis, causal inference, Bayesian inference, and their intersection. Also a lover of representative democracy. Posts are my own thoughts. This is a personal account. In medio tuttisimus ibis.
@smaglia.bsky.social
Assistant prof in the Amsterdam Machine Learning Lab at the University of Amsterdam | ELLIS scholar | #causality #causalML anything #causal | 🇮🇹🇸🇮 in 🇳🇱 | #UAI2025 program chair https://saramagliacane.github.io/
@rashellemusci.bsky.social
Passionate about prevention science, lover of latent variables. Associate Professor @JohnsHopkinsSPH, Director of Doctoral Programs @JohnsHopkinsDMH
@katmabu.bsky.social
Running for Congress (IL-09) because we deserve Democrats who actually do something | katforillinois.com
@dagophile.bsky.social
Interested in all things causal modeling. Ongoing projects on causal analyses of discrimination and on causation in dynamical systems.
@calebhmiles.bsky.social
Assistant professor of biostatistics at Columbia University Casual inference, statistics, etc Pauca sed Matura
@frankbretz.bsky.social
Quantitative scientist @ Novartis interested in multiple testing, adaptive designs, dose finding and estimands. https://scholar.google.de/citations?hl=en&user=dDGzYjUAAAAJ
@mandymejia.bsky.social
Associate Professor of Statistics at Indiana University, statistical analysis of functional neuroimaging data, PI of the StatMIND lab
@ariadnerivera.bsky.social
Epi PhD Candidate Interests in causal inference, social epi, policy evaluation, dev economics.
@yann-lecun.bsky.social
Professor a NYU; Chief AI Scientist at Meta. Researcher in AI, Machine Learning, Robotics, etc. ACM Turing Award Laureate. http://yann.lecun.com
@sophieehill.bsky.social
PoliSci PhD student @ Harvard / 🇬🇧🏳️🌈 / Creator of MyLittleCrony.com
@andreaschaffer.bsky.social
Epidemiologist at Bennett Institue for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford https://www.bennett.ox.ac.uk/
@gelovennan.bsky.social
biostatistician * causal inference * causal prediction * time-to-event outcomes * observational data & trials * @LUMC_Leiden
@stablemarkets.bsky.social
Statistician | Assistant professor @ Brown University Dept of Biostatistics | Developing nonparametric Bayesian methods for causal inference. Research site: stablemarkets.netlify.app #statsky
@bonv.bsky.social
Assistant Professor in the Department of Statistics at Rutgers He/him 🏳️🌈
@sylviach.bsky.social
PhD student at UC Berkeley in Epidemiology & Biostatistics. Just an applied stat juggler 🤹🏻♀️
@mfschomaker.bsky.social
Heisenberg Professor for Biostatistics at the Department of Statistics, LMU München | causal inference - missing data - HIV michaelschomaker.github.io
@conjugateprior.org
Señor Research Scientist, an NPC at the Hertie School in Berlin 🇩🇪 via Princeton, Mannheim, Edinburgh and a bunch of other ivory towers that will probably be billiard balls and decorative boxes by the end of the decade.
@alecmcclean.bsky.social
Postdoc @ NYU Grossman; stats / ML + causal inference https://alecmcclean.github.io/
@christopherjarvis.bsky.social
Operations Lead Humanitarian Epidemiologist Researcher https://www.linkedin.com/in/c-jarvis/ https://github.com/jarvisc1 Trustee @Mapaction @AppliedEpi #Rstats #Statssky #Episky
@michaelplanknz.bsky.social
Professor of Applied Mathematics at the University of Canterbury, NZ. Fellow @royalsocietynz.bsky.social. Math modelling in biology and epidemiology. Bicycles make the world a better place. He/him https://www.math.canterbury.ac.nz/~m.plank/
@jonathan-bartlett.bsky.social
Biostatistician, London School of Hygiene & Tropical Medicine. Blogging at thestatsgeek.com
@jeremypb.bsky.social
Postdoctoral Research Fellow @causalab.bsky.social @hsph.harvard.edu
@cristianmeli.bsky.social
Population health scientist · Senior lecturer at the University of Fribourg, Switzerland · Cyclist and theater lover · Papà. Social & life course epidemiology Monitoring of chronic diseases & mortality Causal inference from observational data Data science
@alexmill.io
dissociating professor (marketing, USC), scientist, constrained optimizer California 🌴 https://alexmiller.phd
@awlevis.bsky.social
Postdoc @ CMU Statistics & Data Science www.awlevis.com interests: causal inference, distribution shift, machine learning, non/semiparametrics, w/ applications in EHR data & beyond
@jeremylabrecque.bsky.social
Canadian epidemiologist and causal inference person at Erasmus Medical Center. Big fan of Northern Expsoure and Car Talk. jeremylabrecque.org
@davidlaursen.bsky.social
Clinical research methodology, placebo, blinding Repost/like ≠ endorse
@thenewstats.bsky.social
Open science, estimation statistics, and random thoughts from Bob Calin-Jageman and Geoff Cumming. https://thenewstatistics.com/itns/
@jiafengkevinchen.bsky.social
postdoc at siepr | assistant professor (‘25) of economics at stanford jiafengkevinchen.github.io
@ang-yu.bsky.social
PhD Candidate in Sociology at UW-Madison. Studying causal inference. https://ang-yu.github.io/