People
Researchers and Heroes in Causality
Papers of Judea Pearl
Pear 2019 seven tools of causal inference过于经典，需要背诵论文中所有的内容。
Pearl 2018 Causal and Counterfactual Inference 因果推断框架一个简要的数学介绍。
An message to AI people by Pearl(2019) at ACM
2019AAAI-why 最新报告
Interviewed by Hernan
2011 Turing Price Interview 最囧的采访记者, 完全不懂对方在说什么.
The requirements to be a good researcher in the area:
Have a PhD in Applied Mathematics, Computational Statistics, Computer Science or a related discipline.
Experience and background of computer science and data science, computer vision, machine learning.
Skills in Python and Linux are required.
Strong communication skills in written and verbal English
Highly self-motivated and possess the ability to work independently as well as in multidisciplinary collaborative environment.
英国高校
Jonathan Barrett
Quatumn Causal Models
Vanessa Didelez
Causal Concepts and Graphical Mo dels - Handbook of graphical models
At Christ Church College, Oxford
Nature 因果论文的作者
Remodelling machine learning: An AI that thinks like a scientist
Deep Learning and causal inference
Christina Heinze-Deml Postdoc of ETH (Marloes助教)
Causal Structure Learning
Marloes Maathuis
Professor of Statistics(ETH)
Handbook of Graphical Models
Professor of Statistics, ETH
Emre Kiciman
Harvard Univ.
哈佛大学生物统计.
Tyler J. VanderWeele
Migual Hernan
James Robins
其他高校
University of Washington
University of Copenhagen
University of Califolia, Berkeley
Mathias Drton 图模型专家
Steffen Lauritzen 图理论
chain graphs. Bayesian
Martin Wainwright 伯克利机器学习
PhDs in Causal inference
Ruocheng Guo http://www.public.asu.edu/~rguo12/
AAAI-WHY 2019 https://why19.causalai.net/index.html#
Director of Max Planck Institute for Intelligent Systems
Facebook AI Research
PhD student in Université Paris-Saclay