معرفی
Linbo Wang is an Associate Professor at the Department of Statistical Sciences, University of Toronto, with cross-appointments to the Department of Computer and Mathematical Sciences at U of T Scarborough and the Department of Computer Science at U of T. He is also an Adjunct Associate Professor at the University of Washington and a Canada Research Chair in Causal Machine Learning.
- B.Stat. from Peking University (2011)
- PhD in Biostatistics from the University of Washington (2016)
- Postdoctoral Fellowship at Harvard T.H. Chan School of Public Health
His research focuses on causal inference, machine learning, and biostatistics, particularly causal modeling, graphical models, and robust inference for high-stakes domains like healthcare and justice. Recent work includes causal mediation analysis, instrumental variable methods, and trustworthy AI frameworks emphasizing fairness, explainability, and stability.
His publications span causal inference for longitudinal studies, missing data, high-dimensional models, and biomedical applications. Awards include the NSERC Discovery Accelerator Supplement, Ontario Early Researcher Award, and recognition as a Canada Research Chair.
He is affiliated with the Vector Institute and the Data Sciences Institute, co-organizing conferences like the 23rd Meeting of New Researchers in Statistics and Probability and serving as tutorial co-chair for the 39th Conference on Uncertainty in Artificial Intelligence. Currently, he is accepting students and postdocs for research in causal inference and machine learning.
