Causal Sky Chart
People working on causal inference, broadly defined.
Created by
@jrgant.bsky.social
@andershuitfeldt.net
Aspiring rationalist. Medical doctor (PGY 4, addiction medicine). In a past life, I was an epidemiologist. MB BCh BAO (Royal College of Surgeons in Ireland, 2008). ScD (Harvard School of Public Health, 2015).
@whitneyepi.bsky.social
Epidemiologist * Bringing light to gynecologic health and health care * I also love TV Views expressed are personal
@pausalz.bsky.social
Paul Zivich, Assistant (to the Regional) Professor Computational epidemiologist, causal inference researcher, amateur mycologist, and open-source enthusiast. https://github.com/pzivich #epidemiology #statistics #python #episky #causalsky
@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
@mattpfox.bsky.social
Professor of Epidemiology/Global Health. Caring about kindness in academia. @busph Free Associations podcast co-host pophealthex.org/fa
@lizstuart.bsky.social
Statistician; Professor and Chair @JHUBiostat @JohnsHopkinsSPH, w/links to @SREESociety, @AmericanHealth. Oh, & spouse, mom, runner, traveler.
@lisabodnar.bsky.social
shiny epi people podcast host | epidemiologist studying nutrition and perinatal health | mom of 3 | drinker of wine (see previous) | she/her
@malcolmbarrett.malco.io
Ph.D., epidemiology. research software engineer @ Stanford Health Policy. living in Ann Arbor. open-source data science. causal inference. doing poems on aircrafts. approximately Bayesian. formerly Posit, Apple, AmeriCorps. ๅฟใ็ใใใsic semper tyrannis.
@neurostats.org
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 ๐งช๐งฎโ๏ธ๐งฌ๐ง ๐ฅ๐ค๐โ๏ธ๐ฉบ๐ฉโ๐๐
@miguelhernan.org
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
@lucystats.bsky.social
Biostatistician โข Assistant Prof @ Wake Forest University โข former postdoc @ Hopkins Biostat โข PhD @ Vandy Biostat โข ๐ Casual Inference โข lucymcgowan.com
@sherrirose.bsky.social
Stanford Professor | Computational Health Economics & Outcomes | Fair Machine Learning | Causality | Statistics | Health Policy | Health Equity drsherrirose.org Lab manual: stanfordhpds.github.io/lab_manual Personal account
@statmodeling.bsky.social
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
@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
@cdsamii.bsky.social
NYU Politics prof. Methods to inform policy. Governance, conflict, institutions. cyrussamii.com
@rmcelreath.bsky.social
Anthropologist - Bayesian modeling - organic modem converting poetry into code - cat and cooking content too - Director @ MPI for evolutionary anthropology https://www.eva.mpg.de/ecology/staff/richard-mcelreath/
@mariaglymour.bsky.social
Professor and Chair of the Department of Epidemiology at Boston University School of Public Health
@epidbydesign.bsky.social
Epidemiologist, writer, bon vivant. Professor @UNC (opinions my own); co-PI of STAR Cohort; "Morpheus of the Table 2 Fallacy.โ He/him.
@epiellie.bsky.social
Epidemiologist and science communicator | newsletter: epiellie.substack.com | cohost @casualinfer podcast | Causal inference for public health #epitwitter | Canadian in US ๐จ๐ฆ | she/her/Dr
@jrgant.bsky.social
Research Scientist + Asst Prof (Practice) @ Brown SPH. Interested in epidemiology, stats, modeling, ID, complexity, causality. Know just enough to be dangerous. Current quest: never leave Emacs. (Personal account. Opinions not even my own.)