Modeling of complex systems can take many forms, and a career in this field may start in one place yet end up somewhere very different. I will discuss computationally-focused research I have conducted in two very different areas, namely planetary astrophysics and biomathematics. The former centers on the processes by which a young protostar's disk transforms itself into a planetary system, how these processes lead to the huge diversity of discovered exoplanets, and how our own Solar System fits into the picture. The latter involves inferring the burden and past history of infectious diseases from surveillance and health system data, and using this to make predictions about the future, including the effect that future interventions (e.g. new vaccines) might have. Although on the face of it these two areas have little in common, in some cases similar computational methods and approaches can be applied to both. In other cases, however, they absolutely cannot. I will provide examples of both.

Bio:

Edward Thommes is part of the Modeling, Epidemiology and Data Science group at Sanofi Pasteur Global, adjunct professor in the Department of Mathematics and Statistics at University of Guelph as well as York University, and an affiliate member of the Waterloo Institute for Complexity and Innovation (WICI). He starting working in industry in 2012, previously at GlaxoSmithKline Canada and Takeda Canada. He holds a BSc in physics from the University of Alberta (1994), and a PhD in astrophysics from Queen’s University (2000). Subsequently, he was a postdoc at UC Berkeley, NASA Ames, the University of Toronto and Northwestern University. His research interests include biomathematics, epidemiology, health economics, the conduct of real-world evidence studies, AI and machine learning.

Links:

• Research page: https://sites.google.com/view/ewthommes/home

• I’m a part of the Dynamics Training Lab at University of Guelph (PI Monica Cojocaru) at University of Guelph: https://sites.google.com/site/mgcojocarumath/networks-and-dynamics-lab

• My LinkedIn page: https://www.linkedin.com/in/edward-thommes-6455a371/

• Google Scholar profile: https://scholar.google.com/citations?user=v5niLjcAAAAJ

Some relevant publications:

Thommes EW, Matsumura S, Rasio FA. Gas disks to gas giants: Simulating the birth of planetary systems. Science. 2008 Aug 8;321(5890):814-7.

Thommes, E.W., Duncan, M.J. and Levison, H.F., 1999. The formation of Uranus and Neptune in the Jupiter–Saturn region of the Solar System. Nature, 402(6762), pp.635-638.

Thommes, E.W., Mahmud, S.M., Young‐Xu, Y., Snider, J.T., van Aalst, R., Lee, J.K., Halchenko, Y., Russo, E. and Chit, A., 2020. Assessing the prior event rate ratio method via probabilistic bias analysis on a Bayesian network. Statistics in medicine, 39(5), pp.639-659.

Humphrey, L., Thommes, E.W., Fields, R., Coudeville, L., Hakim, N., Chit, A., Wu, J. and Cojocaru, M.G., 2021. Large-scale frequent testing and tracing to supplement control of Covid-19 and vaccination rollout constrained by supply. Infectious Disease Modelling, 6, pp.955-974.

Mahmud, S.M., Xu, L., Hall, L.L., Puckrein, G., Thommes, E., Loiacono, M.M. and Chit, A., 2021. Effect of race and ethnicity on influenza vaccine uptake among older US Medicare beneficiaries: a record-linkage cohort study. The Lancet Healthy Longevity, 2(3), pp.e143-e153.