Angus Lewis

Dr. Angus Lewis is a Lecturer in applied probability within the School of Computer and Mathematical Sciences at the University of Adelaide, part of the Faculty of Sciences, Engineering and Technology. His research focuses on stochastic processes, matrix-analytic methods, and their applications in tracking, optimization, and data science. He explores theoretical and applied aspects of matrix-exponential distributions, Markov-modulated processes, and hidden Markov models, with applications in signal processing and ecological time-series analysis (sclerochronology). His work also involves stochastic filtering, parameter estimation for continuous-time Markov chains, and Markov decision processes.

Research interests include the probabilistic interpretation of stochastic systems, near-real-time tracking using diverse data sources, and approximations of complex stochastic processes (e.g., multi-type branching processes, fluid queues). Dr. Lewis’s methods bridge theory and practice, aiming to solve optimization and modeling challenges in dynamic environments.

No specific articles, awards, or grants are listed in the provided text. He is eligible to supervise postgraduate research given his academic role.