Andrew Heunis

Andrew Heunis is a Professor at the University of Waterloo, cross-appointed with the Department of Statistics and Actuarial Sciences. He holds a BSc from the University of the Witwatersrand (Johannesburg) and an MSc from Imperial College, London.

His research focuses on stochastic algorithms, system identification, nonlinear filtering, and stochastic differential equations. His work integrates advanced probability theory with applications in control systems, financial mathematics, and signal processing. Recent research emphasizes theoretical foundations of nonlinear filtering and stochastic optimization, with contributions to portfolio optimization and convergence analysis of stochastic algorithms.

He has supervised numerous PhD and MASc theses, including studies on mean-variance portfolio optimization, stochastic control, and quantum annealing. Current students include Dian Zhu (PhD), Pradeep Ramchandani (PhD), and Alisa Tazhitdinova (MASc).

Teaching responsibilities include courses on stochastic processes, linear systems, and probability theory at both undergraduate and graduate levels. Technical reports include work on convex duality in constrained portfolio optimization, extending his research into financial applications.

No scientific awards are listed in the provided information.