The Department of Statistical Sciences (DOSS) has established an enviable tradition of garnering Discovery Accelerator Supplement (DAS) awards in recent years. For instance, this is the fourth consecutive year in which a DOSS member receives a DAS. This year, Daniel Roy has won with his proposal, A Fresh Look at our Understanding of Machine Learning. Dan's leading-edge research spans both Statistics and Machine Learning. He has made seminal contributions in numerous areas, including statistical network analysis and random graphs; theoretical machine learning; statistical decision theory; Bayesian nonparametric statistics; and probabilistic programming.
The NSERC's Discovery Accelerator Supplement (DAS) provides additional resources to fast-track researchers with strong potential to become international leaders within their research disciplines. There is no application process, the selection being made in conjunction with the review of Discovery Grant applications each year. Each award is valued at $120,000, and these funds directly support Canadian researchers in their quest to compete with global leaders in their respective fields. Each year, NSERC gives up to 130 awards across all disciplines it funds. Given that currently NSERC funds every year in excess of 25K researchers, the DAS is indeed a very prestigious award.
In 2017 Dehan Kong won a DAS for his proposal Novel Statistical Methods with Application to Imaging Genetics. Dehan has contributed extensively to statistical learning methods for high-dimensional complex data, motivated by his interdisciplinary work in neuroscience, genetics and Alzheimer’s research.
In 2018, two DOSS faculty members received the DAS award. Lei Sun’s proposal, Robust allele-based association analyses of complex genetic data, continues her long-term research interests in developing new statistical methods for genetic studies of complex traits. Sebastian Jaimungal's DAS for his proposal, Stochastic Control and Games in Intraday Markets, recognizes the impact of his diverse research program that gravitates around problems in mathematical finance, including seminal contributions to algorithmic trading, mean-field games, stochastic control, and, more recently, reinforcement learning.
Last year in 2019, Linbo Wang has been awarded a DAS for his proposal Causal Inference with Massive and Complex data: High-Dimensionality and Network Interference. Linbo's research brings fundamental developments to learning from complex data patterns by recognizing causation in these patterns and is central to many important applications in a wide variety of areas including public health and genetics.
Reading through the projects described above as well as the research interests of the DAS recipients, one is struck not only by the depth inherently rewarded by the NSERC adjudication committee, but also the breadth of the research conducted within the Department of Statistical Sciences. This makes the Department an exciting place to build collaborations within and outside statistics, among theorists, methodologists and practitioners.
We congratulate all the recipients of DAS and look forward to many more successes!
Radu V. Craiu
Professor and Chair
Department of Statistical Sciences
University of Toronto