Toronto’s AI-focused Vector Institute has announced five new faculty members from across Canada.
The new faculty brings the Vector Institute expertise in machine learning, computational biology, computer vision, computer graphics, neural networks, clustering, computer security, privacy and statistical and computational machine learning.
“Vector has become a beacon for top AI talent seeking opportunities to collaborate with peers, to have the flexibility to conduct pure or applied research, teach students, or work with industry, as well as launch a new startup company,” said Garth Gibson, president and CEO of the Vector Institute. “Vector offers a unique structure that bridges academia, industry, and institutions and presents researchers with opportunities to work with existing data sets to solve real-world challenges. The new Vector Faculty Members announced today will join a highly-accomplished team of world-class researchers currently at Vector Institute, and we are excited to see what they will accomplish together.”
The new faculty members include:
Dr. Shai Ben-David, University of Waterloo: Ben-David earned his PhD in mathematics from the Hebrew University in Jerusalem and was a professor at Technion (Israel Institute of Technology). He has also held visiting faculty positions around the world, and has been a professor at the David R. Cheriton School of Computer Science at University of Waterloo since 2004. His research interests include a range of topics in computational statistics, machine learning theory, and unsupervised learning and clustering.
Dr. Sara Mostafavi, University of British Columbia: Mostafavi is an assistant professor at the Department of Statistics and the Department of Medical Genetics, and an affiliate member of the Department of Computer Science, at the University of British Columbia (UBC). She received her PhD in computer science from the University of Toronto in 2011, working with Quaid Morris, a Vector Faculty Member, and completed her postdoctoral fellowship at Stanford University. Mostafavi’s research interests are in the development and application of machine learning and statistical methods to study the genomics of complex diseases, particularly psychiatric disorders.
Dr. Nicolas Papernot, University of Toronto: Papernot will be joining the Department of Electrical & Computer Engineering (ECE) at the University of Toronto as an assistant professor in Fall 2019. He is currently a research scientist at Google Brain working on the security and privacy of machine learning in Úlfar Erlingsson’s group. Papernot’s research interests span the areas of computer security, privacy, and machine learning.
Dr. Leonid Sigal, University of British Columbia, and Borealis AI: Leonid moved from Carnegie Mellon University and Disney Research in Pittsburgh to Vancouver in 2017, joining UBC as an associate professor in the Department of Computer Science. His research interests are in machine learning and computer vision with a focus on object recognition, scene understanding, action recognition, multi-modal learning, and neural networks.
Dr. Bo Wang, Peter Munk Cardiac Centre (PMCC) and the Techna Institute at the University Health Network (UHN), and Faculty of Medicine at University of Toronto: Having recently completed his PhD at Stanford, Bo will serve as the Lead Artificial Intelligence Scientist co-hired by PMCC and the Vector Institute. Wang will lead the development and integration of new machine-learning approaches into the care of patients with heart and vascular diseases.
Since its launch in 2017, the Vector Institute has grown into a community of more than 240 researchers, including faculty, postdocs, students and affiliates. Over the last year, the Institute has published over 100 papers.