Department of Statistics and the College
Victor Veitch’s recent work revolves around the intersection of machine learning and causal inference, as well as the design and evaluation of safe and credible artificial intelligence systems. Other notable areas of interest include network data and the foundations of learning and statistical inference.
His research has been published in arXiv, The Annals of Probability, and The Annals of Statistics. Among his honors are the Statistical Society of Canada’s Pierre Robillard Award, which recognizes the best PhD thesis defended at a Canadian university in a given year and written in the fields covered by The Canadian Journal of Statistics.
Veitch earned a bachelor of science degree in mathematical physics from the University of Waterloo and later a master of mathematics degree from the same institution, working in quantum computation. He then completed his PhD in statistics at the University of Toronto. Most recently, he was a distinguished postdoctoral researcher in the Department of Statistics at Columbia University. Veitch, who joins the University of Chicago in January 2021, is also a research scientist at Google Cambridge.