Justin W.L. Wan

  • Studentship in 1992 at Chinese University of Hong Kong

Dr. Justin W.L. Wan is a professor and faculty member of the Scientific Computing group at the David R. Cheriton School of Computer Science, University of Waterloo.

He received his PhD degree from the Applied Math Program in the Department of Mathematics, UCLA. After graduation, he started his career at Stanford University as a Forsythe Fellow (acting assistant professor) before he joined the University of Waterloo. In 2010-2015, Dr. Wan was the Director of the Centre for Computational Mathematics in Industry and Commerce. He was appointed as the Associate Director (Vice Director) for the Cheriton School of Computer Science in 2015-2018. After a year of sabbatical, he was appointed as the Director of Graduate Studies in Computer Science from 2019-2021. Since 2019, Dr. Wan is the Co-Director of Computing and Financial Management, University of Waterloo.

Dr. Wan has also been active in service for his research community. He was elected and served as the Secretary for the Canadian Applied and Industrial Mathematics Society (CAIMS) from 2015-2020. He has been organizers of workshops and international conferences such as the CAIMS Annual Meeting in 2021. He has also served as editors for journals and members of a number of program committees. Currently, Dr. Wan is on the editorial boards as Associate Editor for the Springer journal, Computational and Applied Mathematics, and CAIMS Journal of Mathematics in Science and Industry.

Awards & Honors

Dr. Wan was awarded the Alfred P. Sloan Foundation Doctoral Dissertation Fellowship, 1996-97. He was the Canada Research Chair in Scientific Computing from 2006-2016. He received an Outstanding Performance Award by the University of Waterloo in 2016. Recently, he received the Arthur Beaumont Distinguished Service Award from the Canadian Applied and Industrial Mathematics Society.

Research Interests

Dr. Wan's research is in the general area of scientific computing. Combining ideas and theories from mathematical modelling and numerical computation, his research team develop advanced, robust and efficient numerical techniques to solve complex application problems arising in science, engineering, finance and economics. Applications of his research include medical image processing (image restoration, segmentation, registration), machine learning and neural network model for financial applications (option pricing, algorithmic trading), and computer graphics simulation of physical phenomenon. Some of his recent projects include image enhancements of CT scans, computation of American options with many assets and hedging parameters, and fast fluid simulation with deformable solid objects.