@cdsamii.bsky.social
NYU Politics prof. Methods to inform policy. Governance, conflict, institutions. cyrussamii.com
@azjacobs.bsky.social
Asst Prof of Information @ UMich thinking about assumptions built into AI
@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
@lucystats.bsky.social
Biostatistician • Assistant Prof @ Wake Forest University • former postdoc @ Hopkins Biostat • PhD @ Vandy Biostat • 🎙 Casual Inference • lucymcgowan.com
@danlarremore.bsky.social
Prof | CU Boulder BioFrontiers Institute + Computer Science | Santa Fe Institute LarremoreLab.github.io
@jugander.bsky.social
Associate Professor, Stanford MS&E. Visiting Yale FDS '24-'25. Social networks, social and behavioral data, causal inference, mountains. www.stanford.edu/~jugander/
@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 🧪🧮⚕️🧬🧠🖥🤖📈✍️🩺👩📈📉
@aliceschwarze.bsky.social
Head of Research @ Utah AI Policy Office // math, networks, complex systems, machine learning, and all things AI // mom & cat lady
@mraginsky.bsky.social
web: http://maxim.ece.illinois.edu substack: https://realizable.substack.com
@maibennett.com
Asst Professor at @UTAustin working on causal inference. The Anna Wintour of slide decks. If you have something to say, say it with a nice plot #rstats
@edwardhkennedy.bsky.social
assoc prof of statistics & data science at Carnegie Mellon https://www.ehkennedy.com/ interested in causality, machine learning, nonparametrics, public policy, etc
@statstas.datascience.blue
Social data scientist AMA about survey statistics, sampling weights, small area estimation, multilevel models, latent class analysis, structural equation models, #rstats, #Stata. Scraping contents of this account is not permitted.
@bechhof.bsky.social
statistics obsessor, economics enjoyer, occasional engineer, founder at TrovBase
@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
@linstonwin.bsky.social
senior lecturer in statistics, penn NYC & Philadelphia https://www.stat.berkeley.edu/~winston
@jgyou.bsky.social
Assistant professor of Statistics and Complex systems at UVM. Lab: https://joint-lab.github.io
@jiafengkevinchen.bsky.social
postdoc at siepr | assistant professor (‘25) of economics at stanford jiafengkevinchen.github.io
@joft.bsky.social
Prof. of #Statistics, #machinelearning / ethics for #datascience @LSE. Unschooled to community college to PhD @Stanford Technology, institutions, and ideas should serve people, but much of humanity is stuck with this upside-down.
@rohanalexander.bsky.social
I spend too much money on books. And too much time writing them. 🇦🇺🇨🇦. https://rohanalexander.com http://tellingstorieswithdata.com https://rohanalexander.substack.com
@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
@ericjpedersen.bsky.social
Associate prof of biology prof Concordia University. Lost in the wilds between ecology, statistics, and dynamic systems. Always interested in chatting all things GAM- and and nonlinear-system related
@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
@jake-westfall.bsky.social
Software engineer (MLOps), previously data scientist, previously research psychologist. Teetotal vegan YIMBY cyclist in Austin, TX, USA.
@jamesuanhoro.bsky.social
Nigerian. Assistant professor in the Research, Measurement & Statistics program at University of North Texas. Uses Stan a lot. Member @CWA6186 / TSEU
@modrakm.bsky.social
Biostatistics/bioinformatics at Charles University, 2nd faculty of Medicine. Bayesian in practice, but not a fan of Bayesianepistemology. Main on fedi: https://bayes.club/@modrak_m Blog: https://martinmodrak.cz
@gemoran.bsky.social
Assistant Prof of Statistics at Rutgers Previously: postdoc in the Blei Lab at Columbia. PhD in Statistics from University of Pennsylvania. https://www.gemma-moran.com Aussie 🦘| NYC-based 🗽
@skdeshpande91.bsky.social
Assistant professor in Statistics at UW–Madison. Interested in #Bayesian statistics, sports analytics, causal inference. Also cocktails and Dallas sports. #mffl
@emcfowland.bsky.social
HBS Professor interested in the development and deployment of Data Science tools (e.g., Anomaly Detection, Causal Inference, Networks) for better decision-making.
@erictleung.bsky.social
marketing data scientist, generalist, math and library enthusiast, data scientist of the third kind, loves good stationary and pens, low tech enthusiast, open source tinkerer, opinions = mine #rstats
@statstipton.bsky.social
Professor of Statistics at NorthwesternU, Faculty Fellow at IPRatNU. meta-analysis, causal generalization, education, psychology.
@epiellie.bsky.social
Epidemiologist and science communicator | newsletter: epiellie.substack.com | cohost @casualinfer podcast | Causal inference for public health #epitwitter | Canadian in US 🇨🇦 | she/her/Dr
@rnishimura.bsky.social
Survey methodologist and statistician at the Survey Research Center, Institute for Social Research, University of Michigan #survey | #sampling | #statistics | #RStats
@aeadata.bsky.social
Data editor for the American Economic Association - for official guidance, always go to http://aeaweb.org and https://aeadataeditor.github.io. Does not follow persons (sorry)
@angelamczhou.bsky.social
assistant prof at USC Data Sciences and Operations; phd Cornell ORIE. data-driven decision-making, operations research/management, causal inference, algorithmic fairness/equity angelamzhou.github.io
@stephenjwild.bsky.social
I try to put straight lines through things but usually fail. Try to be Bayesian when I can. Views my own. RT/like != endorsement.
@datavisfriendly.bsky.social
ASA Fellow; #rstats developer of graphical methods for categorical and multivariate data; #datavis history of data visualization; #historicaldatavis; Milestones project Web: www.datavis.ca GitHub: github.com/friendly
@joshpasek.com
Prof of Comm & Media and Polisci @Umich studying how people get and use political information and social measurement. Skills/competencies: data sci, DIY solar, election analytics, carpooling, #polcom, #polpsych, survey methods, AI (views are my own)
@leonievogelsmeier.bsky.social
Assistant Professor improving (assessment of) measurement in intensive longitudinal data Department of Methodology and Statistics, Tilburg University, The Netherlands Ambassador for the Tilburg Experience Sampling Center: https://experiencesampling.nl/
@nathanielforde.bsky.social
https://nathanielf.github.io/ Statistics, Probability previously Logic and Philosophy
@jburnmurdoch.ft.com
Columnist and chief data reporter the Financial Times | Stories, stats & scatterplots | [email protected] — On 👨👶 leave until July — 📝 ft.com/jbm
@data.ft.com
The FT’s team of reporters, statisticians, illustrators, cartographers, designers, and developers work with colleagues across our newsrooms, using graphics and data to find, investigate and explain stories. https://www.ft.com/visual-and-data-journalism
@dataandme.bsky.social
former 🥑 dev advocate @rstudio, 🏀 hoop head, data-viz lover, gnashgab, blatherskite, #rstats, doggos, and horses