Teaching and Supervision
Supervision
Current Students
Taylor Woodward (PhD Candidate, jointly supervised with Prof Michael Stumpf)
Yujing Liu (PhD Candidate, jointly supervised with Prof Michael Stumpf)
Research Associates
Tom Cummings
Yang Zhao
Co-mentored research associates on the project Clone wars: predicting clonal diversity in resistance to CAR-T cell immunotherapy
Past Students
Dr. Megan Coomer (2019-2023)
Co-supervised to completion (with Prof Michael P.H. Stumpf). Megan is now co-founder of the venture capital-backed deep tech company Cell Bauhaus.
Current Teaching
Mathematics and Statistics for Biomedicine (MAST10024) Semester 1, 2025 - The University of Melbourne
I coordinate and lecture this large service subject for biomedicine students. The course covers mechanistic modeling (ODEs and mass-action kinetics), epidemics (compartmental models), and statistical/data analysis techniques (hypothesis testing and linear regression).
Recent Workshops
The Fundamentals of Whole Cell Modelling: Stochastic Simulation in Julia AMSI BioInfoSummer Workshop, 2024 - The University of Melbourne
In conjunction with Dr. Kaan Öcal and Dr. Augustinas Šukys, I developed and delivered interactive materials on stochastic modelling of biochemical systems using the Julia programming language, introducing participants to practical implementation of stochastic algorithms for cellular simulations.
Previous Teaching Experience
Thinking Scientifically (SCIE20001) 2023 - The University of Melbourne
I managed student queries for the data science module serving over 800 students on the Ed Discussion platform, and led the overhaul of learning exercises, Minitab worksheets, and datasets.
Tutor and Mathematics Support 2013-2018 - La Trobe University
Mathematics
Discrete Mathematics (Level 1)
Calculus and Differential Equations (Level 1)
Number Systems (Level 1)
Mathematics for Biology (Level 1)
Applied Algebra (Level 2)
Vector Calculus (Level 3)
Complex Analysis (Level 3)
Model Theory (Level 4)
Statistics
Applied Statistics (Level 2)
Probability Models (Level 2)
Biostatistics (Level 3)