We’re delighted to announce two winners of the department’s 2020 Marshall Prize. This year, the Marshall Prize co-winners are PhD students Anthony Christidis and Saifuddin (Saif) Syed.
In honour of our Professor Emeritus Albert Marshall, the Marshall Prize is awarded annually to a statistics graduate student who has achieved great distinction according to the professional and academic criteria by which members of our discipline are judged.
Anthony and Saif are worthy recipients of this award, having each been praised by their nominators for demonstrating outstanding contributions that go beyond what’s expected of a PhD student.
Anthony has extensive knowledge of numerical optimization, modern statistical learning, and robustness theory. He's described by his collaborators as an “extremely talented researcher” whose “research output and expertise in statistical theory and applications have been outstanding.”
In his research, Anthony focuses on providing a theoretical framework for learning optimal ensembles of models. Through this research, Anthony has solved novel theoretical as well as computational problems. His research has also taken him to KU Leuven, through a MITACS Globalink Research Award.
Notably, Anthony has collaborated widely beyond his thesis work with Professor Ruben Zamar. For example, he has worked with our Professor Matías Salibián-Barrera on initial estimators for robust regression in high-dimensional settings. He’s also worked with Professor Doug Martin (University of Washington) on influence functions and their applications to the analysis of financial time series.
While playing a central role in a collaborative project on gene-expression datasets, Anthony developed efficient algorithms to solve multi-convex optimization problems. Now, Anthony is also collaborating with an international team of medical researchers on a project that aims to find non-invasive tools to diagnose ovarian and prostate cancer.
Anthony has a joint paper published in the Journal of Mathematical Finance and one published in Technometrics. He also has several other papers in the works, including a joint paper with Dr. Stefan Van Aelst (KU Leuven) on the application of his optimal ensemble learning research to high-dimensional microarray data.
Anthony has also contributed to the statistical community by serving as a reviewer for reputable statistics journals (Journal of the American Statistical Association and Computational Statistics and Data Analysis). In the department, he’s served as a TA and a lecturer.
Saifuddin (Saif) Syed
Saif is described by his nominator as having outstanding creativity and technical ability.
Saif was nominated for the Marshall Prize for his range of excellent research, including his collaborative work with our Associate Professor Alex Bouchard-Côté and others on parallel tempering, which is a class of methods used to approximate difficult posterior distribution in Bayesian statistics. This work requires a breadth of skills, including advanced Monte Carlo theory, stochastic analysis, statistical physics, and differential geometry.
Saif has made impressive contributions to this work, which has attracted much international attention in the field of computational statistics and will appear in the Journal of the Royal Statistical Society Series B. Notably, methodology developed through this work has been taken up by researchers in other disciplines. For example, it has been recently applied by the Event Horizon Telescope collaboration to discover magnetic polarization in the image of the supermassive black hole M87.
Along with Dr. Bouchard-Côté, our Assistant Professor Trevor Campbell, and fellow PhD student Vittorio Romaniello, Saif has also been working on a generalization of the notion of annealing paths where paths of distributions interpolate between simple and complex distributions. This work has been accepted to the Thirty-eighth International Conference on Machine Learning.
Additionally, Saif is working with Dr. Campbell on their new, less restrictive, concept of exchangeability; that is, local exchangeability. One of Saif’s results from this project has become a key one in the line of research.
Saif has given several invited talks on his work. Outside his research, Saif has served as a TA and a guest lecturer in our department. He’s also been an instructor in math courses for UBC Vantage College and for the UBC Department of Mathematics.