Mr David Wu
Research | Current
My current research is investigating efficient ways of performing parameter and state estimation for epidemiological models. This area has recently become a hot topic, as interdisciplinary researchers are rediscovering the difficulties of fitting simple, but flexible, models to sparse, poorly curated datasets. I am trying to tackle problems of computational cost in standard methods of fitting these models by using approximate solution methods. These include the use of collocation to avoid solving the forward problem explicitly, and using surrogate models to reduce highly complex models to tractable problems.
I have also been working with epidemic models on networks. This has involved implementing an efficient stochastic simulation of the spread and control of a contagion spreading over a large, realistic network.
Teaching | Current
- ENGSCI 233 - Computationla Techniques and Computer Systems (S1 2019, S1 2020)
- ENGSCI 263 - Engineering Science Design I (S2 2020)
- ENGSCI 331 - Computational Techniques 2 (S2 2019)