معرفی
Leonid Chindelevitch is an Assistant Professor in Infectious Disease Epidemiology at the School of Public Health, part of the Faculty of Medicine at Imperial College London. He is affiliated with the Artificial Intelligence Network, the Centre for eXplainable Artificial Intelligence (XAI), and the MRC Centre for Global Infectious Disease Analysis. His research focuses on mathematical and computational modeling of antimicrobial resistance in infectious diseases, combining molecular-level analyses (computational biology, systems biology) with population-level approaches (epidemiology, population genetics). He also applies science to policy to improve healthcare outcomes, particularly in low-resource settings.
Education:
- PhD in Applied Mathematics from MIT (supervised by Bonnie Berger)
- BSc in Mathematics and Computer Science from McGill University
Research Interests: Dr. Chindelevitch’s work spans computational biology, algorithm development, discrete optimization, machine learning, and artificial intelligence. He investigates genomic determinants of drug resistance in pathogens like M. tuberculosis and B. burgdorferi, leveraging methods such as exact optimization and deep neural networks. His team integrates MLST typing and tandem repeat copy number analysis to understand resistance mechanisms.
Awards:
- Alfred P. Sloan Research Fellowship (2015)
Advising & Grants: Previously a faculty member at Simon Fraser University (2015–2020), he transitioned to Imperial College in 2020. He consults for the Foundation for Innovative New Diagnostics on M. tuberculosis drug resistance and co-led a global genomics catalog project. His industry experience includes computational roles at Pfizer and the Massachusetts General Hospital.
Labs & Teams: Active in the MRC Centre for Global Infectious Disease Analysis and collaborates with the Imperial College’s AI Network to advance explainable AI in healthcare.
