Brian Lookabaugh
Brian-Lookabaugh
Research analyst doing federal elections research work. I also like doing quantitative conflict research and NFL analytics on the side.
Fors Marsh Athens, Texas
Ke Sun
datake
My research interest is statistical reinforcement learning.
University of Alberta Edmonton, Alberta
Momenul Haque Mondol
momenulhaque
Graduate Research Assistant, SPPH, UBC, Canada.
Assistant Professor of Statistics, University of Barishal, Barishal, Bangladesh.
The van der Laan Group
vanderLaan-Group
The research group of Mark van der Laan at UC Berkeley
Berkeley, CA, USA
STA 679 - Spring 2022
sta-679-s22
From Correlation to Causation. The goal of this course is to give students the skills needed to conduct analyses and communicate results
Causal AI
CausalAI
Judea Pearl 是 Causal AI 的奠基人，Bernhard Scholkopf 推进了 Causality for Machine Learning，Yoshua Bengio 提出了 System 2 deep learning 作为 Causal AI 的一个范式。
Wang Qing
Vincent-wq
Postdoc fellow who is inter
estd in neuro data science📈 and a photographer📸
MNI, McGill University Montreal, Canada
Riccardo Cadei
riccardocadei
Researcher in Causal Machine Learning
Institute of Science and Technology Austria Vienna
Kevin Lin
Oxlord-Lin
A junior in School of Data Science, Fudan Univeristy. Current interest includes biostatistics, linguisitics and econometrics.
Fudan University Shanghai, China
Gabe Loewinger
gloewing
Biostatistics PhD, Harvard University
Machine Learning Research Scientist, NIMH.
NIMH
Ian Lundberg
ilundberg
Assistant Professor, Information Science, Cornell
Cornell University Ithaca, NY
Daniel Csillag
dccsillag
Applied mathematician working on machine learning, compilers, and automatic theorem proving.
Lina Montoya
lmmontoya
Asst. Professor | UNC-Chapel Hill | School of Data Science & Society | Dept. of Biostatistics
University of North Carolina at Chapel Hill
Anna Guo
annaguo-bios
I am a Ph.D. student in Biostatistics at Emory University working with Dr. Razieh Nabi. My research focuses on causal inference and semiparametric statistics.
Emory University Atlanta, GA
nima hejazi
nhejazi
Assistant Professor of Biostatistics at the Harvard School of Public Health
Harvard School of Public Health Boston, Massachusetts
Chris Kennedy
ck37
Psychiatry faculty; biostatistics PhD. {Targeted, deep, machine} learning, NLP, IRT, computer vision, exposure mixtures, EHRs.
Harvard Medical School, Mass General Hospital Boston, MA
Kat Hoffman
kathoffman
Biostatistician and 2nd year Biostatistics PhD student at the University of Washington
University of Washington Seattle, WA
tlverse
tlverse
An extensible ecosystem of R packages for targeted causal machine learning
Berkeley, CA, USA
Targeted Learning in Biomedical Big Data (Spring 2018)
tlbbd-sp2018
A course in Targeted Learning, offered as Public Health 290 in Spring 2018, with Prof. Mark van der Laan
Berkeley, CA
Ivana Malenica
imalenica
Wojcicki and Troper HDSI Fellow at the Harvard Department of Statistics
Harvard University Cambridge, MA
Jiaqi Zhang
JqVicky
- PhD @ MIT. LIDS, EECS Dept.
- Undergrad @ PKU. Stats, Math Dept.
- Interests: causality x sequential decision making in bio.
Cambridge
Causal Inference with Longitudinal Data
Causal-LDA
An academic-industry collaboration developing statistical software for causal longitudinal data analysis
Bryan S. Graham
bryangraham
Professor of Economics / Econometrician
University of California - Berkeley Berkeley, CA
Ruocheng Guo
rguo12
ML Researcher @ ByteDance Research (UK). RL for LLMs, Causal ML, Conformal Prediction, Recommendation Systems, and GNNs.
London
Kirigaya Kazuto
LSTM-Kirigaya
Deep Learning Architecture & CV Algorithm & DRL & Web & Design & Music
USTC Jiangsu, China
Charlie Gauthier
Velythyl
Charlie Gauthier, master's student at Mila/UdeM.
ML/RL, robotics and functional programming (Scala ❤️) are my main interests.
Montreal, QC, Canada
Edgar Dobriban
dobriban
Associate Professor of Statistics & Computer and Information Science. Interested in stats and ML. Course notes, software, and code to reproduce papers.
The Wharton School, University of Pennsylvania Philadelphia, PA
Christina Heinze-Deml
christinaheinze
I am a Research Scientist at Apple Health AI. My research interests include causality, distributional robustness and deep representation learning.
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