Jeffrey Kwan is an Associate Lecturer in Statistics at the School of Mathematics and Statistics. His research interest is in probability theory and stochastic processes. In particular, he is interested in self-exciting point processes (Hawkes processes) and their asymptotic behaviour. Jeffrey's Ph.D. was on proving and the application of ergodicity for non-stationary and non-exponential Hawkes processes. He received his Ph.D. in 2023. Jeffrey has also taught undergraduate and postgraduate courses on statistics, probability, and stochastic processes.
Professional affiliations and service positions
Conferences and talks
Professional Teaching Development Programs
Kwan J; Chen F; Dunsmuir W, 2023, 'Alternative asymptotic inference theory for a non-stationary Hawkes process', Journal of Statistical Planning and Inference, http://dx.doi.org/10.1016/j.jspi.2023.03.004, ROS ID: 2011353
Kwan J; Chen F; Dunsmuir W, 'Ergodicity of Hawkes process with a general excitation kernel' (under review)
Daniel Ghezelbash, Mia Bridle, Keyvan Dorostkar, Tsz-Kit Jeffrey Kwan, 'Decoding justice: A data-driven approach evaluation and improving the administrative review of refugee casesin Australia' (under review)
Kwan J; Chen F; Dunsmuir W, 'Ergodicity of Hawkes processes with time-varying baseline intensities and general excitation kernels, and applications in asymptotic inference' (in preparation)