Five DoSS Graduate Students Receive Ontario Graduate Scholarship (OGS) Awards

July 16, 2020 by Negin Neghabat

In recognition of their outstanding academic achievement, five DoSS graduate students have been named awardees of Ontario Graduate Scholarships (OGS) for the academic year 2020-2021. 
The OGS program encourages excellence in graduate studies at publicly-assisted universities in Ontario by providing merit-based scholarships to Ontario’s best graduate students in all disciplines of academic study. 
The Department of Statistical Sciences congratulates these five talented students on this achievement and looks forward to following their academic paths and future accomplishments.


Alex Yuxiang Gao

Alex is a third year PhD student. His research interests are in Bayesian methodology, causal inference and spatiotemporal modelling. In particular, he is currently researching ways to generalize treatment effect estimates to target populations. He has previously been awarded the OGS award for the 2018-2019 academic year.

Emma Holmes

Emma is starting her PhD studies this Fall in the Department of Statistical Sciences. Her research will be in the area of financial and actuarial math. She currently plans to focus her research in the area of sensitivity measures with applications in finance. Emma is also the recipient of an Arts and Science Doctoral Recruitment Award.

Michaël Lalancette

Michaël is a PhD candidate. His current research interests lie in multivariate extreme value theory, particularly in the asymptotic independence/dependence dichotomy, as well as in the field of computational statistics. In 2019-2020, he was awarded the Ruth E. and Harry E. Carter Memorial Ontario Graduate Scholarship.

Mufan Li

Mufan is a third year PhD candidate working on applied probability theory, stochastic analysis, and partial differential equations with applications in statistical learning theory. He has previously been awarded an OGS (2019-2020), and he won the MITACS Accelerate Fellowship with Borealis AI (2018).

Arvind Shrivats

Arvind is a PhD candidate studying market-based schemes for emissions generation and renewable energy incentives. His research applies techniques from stochastic control, mean field games, and principal agent games to better understand these schemes. He was previously the recipient of an OGS award in 2019, and won the Department of Statistical Sciences' Early Research award in 2020.