Minjie Cao is a Master’s student in Computer Science at the University of Ottawa. He is passionate about exploring diverse areas within Machine Learning. His collaboration with fellow team members across various projects has been a rich source of inspiration. He is dedicated to developing scalable machine learning models to address real-world challenges. He is being working on the ModEx project
Krishna Roy Chowdhury is a doctoral student with interests in health economic evaluation, decision sciences methods, cost effectiveness analysis and bladder cancer. She is currently conducting research on bladder cancer risk, prevention, and treatment strategies at the population level. She completed her MSc in epidemiology at McGill University, where her thesis examined the effectiveness and safety of apixaban vs rivaroxaban in patients with atrial fibrillation and type 2 diabetes mellitus. Prior to this, she obtained her BSS and MSS in Health Economics from the University of Dhaka.
Michael Pham is a Biomedical Science Graduate with a Biostatistics specialization from the University of Ottawa. Under the mentorship of Dr. Hawre Jalal, his undergraduate honor thesis examines race and gender disparities in life expectancy computation, revealing biases impacting policies. Michael’s research interests extend to Public Health Policy and Decision Science. He is currently dedicated to advancing his expertise with a Master’s in Statistics.
David Garibay holds a bachelor’s degree in economics and a master’s degree in methods for public policy analysis. He supports evidence-based decision-making and is a very passionate R user. He is currently a Data Analyst and Modeler at PADeCI. David has developed decision-analytic models to assess public policies, particularly for bladder and colorectal cancer. He is part of the Bladder modeling group at CISNET, a member of the Society for Medical Decision Making, and a member of Stanford’s Data Science x Decision Science (DS^2) groups.
Linke Li is a PhD candidate in Biostatistics at the University of Toronto. He is passionate about leveraging machine learning methods and Bayesian decision theory to determine the most effective clinical trial design strategies from a health economics perspective. He completed a bachelor of computing degree and a master of science degree in statistics at Queen’s University. Outside of research, he is a big fan of anime and detective novels. He is currently working on the Value of Information component of the ModEx project.
Mohamed Adam Saib is an undergraduate student majoring in Computer Engineering at the University of Ottawa with interest in software development, machine learning, and artificial intelligence. His enthusiasm for tackling multifaceted challenges in these domains made a valuable addition to develop several efficient software solutions to the ModEx project that focuses on building an analysis pattern to a specific population and its behaviors.
Praveen Kumar, PhD earned his Ph.D. in Health Services Research and Policy with a focus in Decision Sciences from the School of Public Health, University of Pittsburgh. He is an Assistant Professor in the Department of Health Policy and Management at the University of Pittsburgh, where his ongoing research focuses on opioid use disorder and bladder cancer. His research interests lie in assessing the value of public health interventions and policies using decision modeling and cost-effectiveness analysis.
Kyu Lee, PhD is an endowed assistant professor of health decision science at the The Comparative Health Outcomes, Policy, and Economics (CHOICE) Institute, School of Pharmacy, University of Washington. Her research interest is to use disease simulation models to leverage scarce data in forecasting the future burden of disease and in evaluating the value of innovative health technology, primarily for infectious diseases. Her recent research project examined the impact of COVID-19 non-pharmaceutical interventions on the population immunity and future influenza epidemics in the United States. Dr.Lee currently develops projects on estimating the impact of new vaccine production technologies on the future burden of respiratory infectious diseases such as influenza and respiratory syncytial virus.
David Sinclair, PhD was previously a Postdoctoral Research Associate in the Public Health Dynamics Laboratory, University of Pittsburgh, where he developed simulations of infectious disease spread, drug use and mortality. David is currently a Senior Research Associate in the Population Health Sciences Institute, Newcastle University, UK, where he specialises in computational and statistical modelling. He is a member of the Healthy Ageing Policy Research Unit, working closely with the UK Government’s Department for Health and Social Care to inform policy decisions.