"This is well deserved recognition for a brilliant scientist," said Martha Crago, Vice-Principal, Research and Innovation. "Professor Paquette’s work is an important component in the evolution of Artificial Intelligence, and augments McGill’s strong reputation in this field. I salute her contributions and applaud her achievement."
A Sloan Research Fellowship is one of the most prestigious awards available to young researchers, in part because so many past Fellows have gone on to become distinguished figures in science. Renowned physicists Richard Feynman and James Cronin were Sloan Research Fellows, as was mathematician John Nash, one of the fathers of modern game theory. A database of current and former Sloan Research Fellows can be found at https://sloan.org/fellows-database.
Fellows from the 2024 cohort are drawn from a diverse range of 53 institutions across the U.S. and Canada, including large public university systems, Ivy League institutions, and small liberal arts colleges. "We thank all the outstanding and forward-thinking institutions that nominated faculty for the Sloan Research Fellowship," says Daniel L. Goroff, director of the Sloan Research Fellowship Program. "We are proud to partner with them in recognizing, supporting, and uplifting the next generation of scientific leaders."
Courtney Y. Paquette is an Assistant Professor in the Department of Mathematics and Statistics and a Canada CIFAR AI Chair. Her research brings together several areas of mathematics in a new way, in particular applying the theory of stochastic processes, advanced random matrix theory, and high-dimensional statistics to the analysis of optimization algorithms: for this reason, she has received a Canada-CIFAR AI Chair and has become a core member of Mila, the prestigious Quebec AI Institute. Paquette’s research interests lie at the frontier of large-scale continuous optimization and deep learning theory, with an eye toward immediate practical implications for artificial intelligence and machine learning. Her main research program is concerned with developing stochastic learning algorithms in high dimensions and using the dynamics of these algorithms to gain insights into why neural networks work.
Since the first Sloan Research Fellowships were awarded in 1955, 31 faculty from McGill University have received a Sloan Research Fellowship, including this year’s winner.