معرفی
Ehsan Karim is a researcher affiliated with the Department of Statistics at the University of British Columbia (UBC), within the Faculty of Science. His work focuses on advancing statistical methodologies in epidemiology, biostatistics, and healthcare analytics. He has contributed to studies addressing causal inference, high-dimensional data modeling, and the application of machine learning in health research.
Key research interests include: causal inference in observational studies, bias correction techniques (e.g., immortal time bias, residual confounding), predictive modeling for healthcare outcomes (e.g., tuberculosis mortality, multiple sclerosis prodrome), and the evaluation of clinical interventions (e.g., direct-acting antivirals for hepatitis C). His work often integrates large administrative datasets and population-based cohort studies.
Recent articles highlight innovations in Bayesian adaptive trial designs, the role of machine learning in reducing residual confounding, and longitudinal analyses of healthcare costs among high-need patients. Karim’s methodologies are applied to critical public health issues such as opioid use disorder, maternal health, and chronic pain management.
His research bridges statistical theory and practical healthcare challenges, emphasizing rigorous data-driven approaches to improve clinical decision-making and public health policy.
