Madeline was a proud Pittsburgher and Torontonian with training in mathematical and computational biology, particularly the ecology and evolution of malaria. Madeline’s research interests focused on developing our quantitative understanding of basic biological processes that underlay within-host infection dynamics. She was working toward a new approach for developing compact, predictive models of within-host infection dynamics that incorporated time series from infected animals and machine learning methods for model discovery. Such an approach not only provided interpretable models of within-host dynamics but also helped design more efficient and informative experiments. Broadly, Madeline enjoyed learning and implementing new mathematical and computational methods, and she saw machine learning as an exciting new area for skill development. For her ideal dinner party, Madeline would have invited Kurt Vonnegut, Stanley Kubrick, and Jeff Lynne.
- Science Mentor: Aaron A. King, Ecology and Evolutionary Biology; Mathematics, LSA
- AI Mentor: Kayvan Najarian, Computational Medicine and Bioinformatics; Electrical Engineering and Computer Science, College of Engineering