Department of Statistics and Actuarial Science professor Marius Hofert and David R. Cheriton School of Computer Science professors Sergey Gorbonuv, Gautum Kamath and Jian Zhao have each been awarded a Natural Sciences and Engineering Council of Canada (NSERC) Discovery Accelerator Supplement (DAS).
“I am proud to hear that four of our exceptional young researchers have been recognized for their research projects in such important areas,” said Mark Giesbrecht, Dean of the Faculty of Mathematics. “Congratulations to Marius, Sergey, Gautum and Jian on being awarded the Discovery Accelerator Supplements.”
Hofert’s research focuses on the intersection of copula modeling and computational statistics with applications in quantitative risk management (QRM). His research project, Copula modeling with generative neural networks, has practical applications in addressing and eliminating some of the long-standing challenges of simulation-based applications of copulas and make it easier for practitioners to check if a fitted model is adequate for the available data.
For untrusted, distributed and highly adversarial environments, such as in cloud computing and blockchains, Gorbonuv builds systems and protocols to protect data and information. His research project, Enabling New Applications via Cryptographic Tools for Data In-Use, will entail the design of new security models, methods and algorithms for secure computation over encrypted data; construct new algorithms for secure processing of machine learning, artificial intelligence and natural language processing applications; and build systems and new applications that enable secure data and program processing in untrusted environments.
Kamath interests lie in principled methods for statistics and machine learning, specifically with a focus on settings that are common in modern data analysis. His project, Theoretical Foundations of Differentially Private Statistics, will develop methods and tools for private statistics and, for a given task, answer the central question: how much more data do we need to ensure that our solution to the task does not violate the privacy of the users?
Developing advanced interaction and visualization techniques that promote the interplay between humans, machines and data, Zhao’s research focus is information visualization, human-computer interaction and data science. His research project, Visualization Techniques for Collaborative Data Analysis, will result in new visualization techniques, systems and methods that allow us to better understand human behaviour during collaboration and improve the efficiency of analysts in collaborative data analysis.
The DAS Program aims to provide substantial and timely additional resources to accelerate progress and maximize the impact of outstanding research programs. In 2020, NSERC awarded $15.24 million to 127 applications in the DAS competition. These supplements are valued at $120,000 over three years.