Abstract: Nirvana Nursimulu's (University of Toronto, Expected 2021) research focuses on methods for computationally analyzing metabolic networks, with applications towards understanding pathogen growth in pursuit of drug development. Nirvana has examined the enzyme annotation problem, specifically focusing on producing methods that yield lower false positives than traditional similarity search metrics while considering full sequence diversity within enzyme classes. In addition, Nirvana has developed an automated pipeline for enzyme annotation and reconstruction of a metabolic model, focusing on increasing model coverage in order to yield more realistic simulations. In other work, Nirvana has also investigated more traditional microbiology across various pathogens.