DrLeonid Chindelevitch

Dr. Chindelevitch’s research programme focuses on the mathematical and computational modeling of antimicrobial resistance in infectious disease, both on the molecular level (using computational and systems biology) as well as on the population level (using epidemiology and population genetics). He is also interested in the application of science to policy towards the goal of improving patient outcomes, especially in low-income or low-resource settings. His methodological research interests focus on computational biology, algorithm development, discrete optimisation, machine learning and artificial intelligence.

Background
Dr. Chindelevitch holds a PhD in Applied Mathematics from MIT (supervised by Bonnie Berger) and a BSc in Mathematics and Computer Science from McGill University. His doctoral work focussed on metabolic models of tuberculosis (TB). Dr. Chindelevitch completed a postdoctoral fellowship in Ted Cohen's group from 2012 to 2015 and was a faculty member at the School of Computing Science at Simon Fraser University from 2015 to 2020, where he received an Alfred P. Sloan Research Fellowship in Computational and Evolutionary Molecular Biology. He joined the Department of Infectious Disease Epidemiology and the MRC Centre for Global Infectious Disease Analysis at Imperial College in 2020.

Dr. Chindelevitch also has experience of working in industry and non-profit organisations. Between his PhD and his postdoctoral fellowship he worked as a computational biologist at Pfizer, where he developed methods for interpreting gene expression, genetic, and metabolomic data using a large network of known biological relationships. He has also worked at the Massachusetts General Hospital and the Clinton Health Access Initiative, and is currently consulting the Foundation for Innovative New Diagnostics on M. tuberculosis, where he co-led the recent effort to catalogue the genomic determinants of drug resistance.