News from University of Toronto
The Department of Statistical Sciences at the University of Toronto has recently advertised its rapid expansion in (research) depth and (expertise) width (for a brief warm-up, see Growing pains and Gains in Statistics - the Toronto Way, Liaison 32.4, 2018). After “talking a good game”, we are extremely pleased to welcome six outstanding new colleagues who will help us play one too!
Monica Alexander (Assistant Professor in the Department of Statistical Sciences and the Department of Sociology, University of Toronto) received her PhD in Demography at the University of California, Berkeley, in 2018. Her research interests include statistical demography, mortality and health inequalities, and small-area population issues. Monica has worked on research projects with the World Health Organization, UNICEF, the Bill and Melinda Gates Foundation, and the Human Mortality Database. She has also been a Fellow at Data Science for Social Good and a research officer at the ANU’s Centre for Aboriginal Economic Policy Research.
Murat Erdogdu (Assistant Professor in the Department of Statistical Sciences and the Department of Computer Science, University of Toronto; Faculty Member of the Vector Institute) has been a postdoctoral researcher at Microsoft Research - New England lab. In 2017 he earned his PhD from the Department of Statistics at Stanford University. Murat has an MS degree in Computer Science from Stanford, and BS degrees in Electrical Engineering and Mathematics, both from Bogazici University. His research interests include optimization, machine learning, statistics, applied probability, and connections among these fields.
Nathalie Moon (Assistant Professor, Teaching Stream, in the Department of Statistical Sciences, University of Toronto) obtained her PhD in Biostatistics from the University of Waterloo earlier this year. She also holds an MMath in Biostatistics from the University of Waterloo (2013) and a BScH in Statistics from Queen’s University (2011). Nathalie’s research focuses on the design of life history studies, with particular interest in studying the progression of chronic diseases using multi-state modeling approaches.
Linbo Wang (Assistant Professor in the Department of Statistical Sciences, University of Toronto, and the Department of Computer and Mathematical Sciences, University of Toronto Scarborough) received a PhD in Biostatistics from the University of Washington in 2016, and a postdoctoral fellowship in the Department of Biostatistics at Harvard University. Linbo’s research interests include causal modeling, missing data, graphical models and robust inference in infinite-dimensional models. He is currently interested in discovering the causal structures underlying complex statistical dependencies. His methodological contributions have found useful applications in public health and social sciences.
Ting-Kam Leonard Wong (Assistant Professor in the Department of Statistical Sciences, University of Toronto, and the Department of Computer and Mathematical Sciences, University of Toronto Scarborough) completed his PhD in Mathematics at the University of Washington in 2016 after which he was a non-tenure track Assistant Professor at the University of Southern California. His research interests include probability, mathematical finance, as well as the geometry of information. In particular, he is trying to apply optimal transport and geometry to design robust investment algorithms.
Yuchong Zhang (Assistant Professor in the Department of Statistical Sciences, University of Toronto) has received her BSc in Mathematics from the Chinese University of Hong Kong in 2010, and her PhD in Applied and Interdisciplinary Mathematics from the University of Michigan in 2015. Before joining U of T in 2018 she worked at Columbia University as a Term Assistant Professor. Her main research interests include stochastic optimal control, mathematical finance, game theory and applied probability. Yuchong has published several papers on fundamental theorem of asset pricing and optimal investment problems under model uncertainty and/or transaction costs, and more recently, on mean field games and its interaction with economics. She was the winner of the 2016 SIAG/FME Conference Paper Prize.
Radu Craiu, Chair of the Department of Statistical Sciences at the University of Toronto