Matteo Courthoud
@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
@patrickdoupe.bsky.social
Principal Economist doing Ads, Pricing, Auctions, experiments; Parenting; Cycling Shutup and np.linalg.inv(X.T @ X) @ X.T @ y. Then get some rest
@vincentab.bsky.social
Prof. Most tweets about R. “Polisci, it’s all about what’s going on.” http://arelbundock.com
@causalscience.org
Fostering a dialogue between industry and academia on causal data science. Causal Data Science Meeting 2024: causalscience.org
@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
@dlmillimet.bsky.social
Robert H. & Nancy Dedman Trustee Prof of Econ at @SMU, husband, son, proud papa, baseball junkie, animal enthusiast, proudly woke. http://people.smu.edu/dmillimet/ https://dlm-econometrics.blogspot.com/
@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/
@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 🧪🧮⚕️🧬🧠🖥🤖📈✍️🩺👩📈📉
@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
@chelseaparlett.bsky.social
Ph.D, stats lover/writer✍🏼, #statistics #scicomm #datascience #statstiktok 👩🏻💻 she/her
@bradross.bsky.social
economics PhD student @ Stanford GSB | public, urban, econometrics | he/him https://brad-ross.github.io
@lauretig.bsky.social
Data Scientist. Poli sci PhD. Cyclist (Gravel, MTB, road). Bayes, causal inference, etc. Also: cats, food opinions. Views & opinions my own. Not investment advice. He/him
@linstonwin.bsky.social
senior lecturer in statistics, penn NYC & Philadelphia https://www.stat.berkeley.edu/~winston
@chrisaitken.bsky.social
Economics PhD student. Interested in political economy, the media, and the use of ML for causal inference. Trying to do interesting things with interesting data 🏴🇬🇧
@profgrimmer.bsky.social
Assistant Professor @JohnsHopkinsAMS, Works in Mathematical Optimization, Mostly here to share pretty maths/3D prints, sometimes sharing my research
@naimurashid.bsky.social
Associate Prof @uncbiostat, @UNCpublichealth, and @UNC_Lineberger #Genomics #statisticalcomputing #clinicaltrials #cancer https://sph.unc.edu/adv_profile/naim-rashid-phd/
@melodyyhuang.bsky.social
Currently @ Yale, working on causal inference & cutting down on caffeine. Website: melodyyhuang.com
@louisahsmith.com
Assistant professor at Northeastern (Health Sciences) & the Roux Institute in Portland, ME. Epidemiologic methods, causal inference, biostats, reproductive and perinatal epi, #rstats, teaching & learning. she/her 🐶🚴♀️🏔️🎗️
@jonhuang.bsky.social
Epidemiology, Biostatistics, & Causal Inference for Health and Social Equity, Academic (but in the Good Way), Bringing Community Data to Communities, Dad, Motorcycle Enthusiast, R&B, Soul, Brass Band, Blues, Jazz, etc. jonhuang.org
@coussens.bsky.social
Data science and health economics at Abett. Previously prof @Columbia.
@mcuellar.bsky.social
Asst. Prof. of Criminology, Statistics & Data Science @Penn. Research in statistics+law, causal inference, and forensic science.
@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 🗽
@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.
@etchin.bsky.social
Assistant Professor of Biostatistics at Johns Hopkins • health equity • data science • studying mass incarceration and algorithm bias
@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
@tracysweet.bsky.social
She/Her ~ Statistician/Quant Methodologist at UMD ~ CMU Stats Alum ~ Researches racial equity, social networks, machine learning, Bayesian things ~ Mom of 3 kids, 2 dogs, 1 cat
@ellaudet.bsky.social
Political Scientist | Associate Professor @Suffolk | Harvard PhD | Co-author of Data Analysis for Social Science (with Kosuke Imai): bit.ly/dss_textbook
@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
@hspter.bsky.social
Data Science advising / consulting. Formerly startup CTO, Data Science Biden 2020, Stitch Fix, Etsy. PhD JHU Biostar. Co-host Not So Standard Deviations podcast. 🥳😴🧘🐈⬛
@economeager.bsky.social
Aspiring wastrel, applied econometrician. At http://rachaelmeager.com for bayes, dev econ and meta science. Also at http://rottenandgood.substack.com for writing, art, death and emotions. Gay academic nonbinary weirdo, cursed to be serious in life.
@seanjtaylor.com
Data Science, Causal Inference, Economics, Statistics and Machine Learning Two joys in life: [1] Learning something interesting about the world [2] Telling people about it Data Science @OpenAI
@ddimmery.com
social science methods: experiments, stats, ML. has read over a dozen books
@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.
@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/
@elenadata.bsky.social
CS Prof @ University of Illinois Chicago. Research in causal inference, machine learning, graph mining, privacy. www.cs.uic.edu/~elena
@karlrohe.bsky.social
“Overly optimistic” 🦮 in Statistics. Listening in statistics. Statistics Professor at UW Madison.
@pedrosantanna.bsky.social
Associate Professor at Emory University. Causal Inference | Difference-in-Differences | Econometrics. Dad x4
@guilhermeduarte.bsky.social
PhD candidate (OID - @Wharton - @Penn). interests: causality, politics, ML duarteguilherme.github.io
@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.
@drjwolfson.bsky.social
Professor, UMN Biostatistics & Health Data Science. Co-founder, Daynamica (www.daynamica.com). Canadian still pronouncing Z the right way, usually.
@skdeshpande91.bsky.social
Assistant professor in Statistics at UW–Madison. Interested in #Bayesian statistics, sports analytics, causal inference. Also cocktails and Dallas sports. #mffl
@aschuler.bsky.social
Assistant Professor of Biostatistics UC Berkeley semiparametric statistics, machine learning, causal inference, stats/ML pedagogy, social justice Modern Causal Inference Book: alejandroschuler.github.io/mci/