Associate Professor, Cumming School of Medicine, University of Calgary

Dr. Darren Brenner is a cancer epidemiologist and an Associate Professor in the Departments of Oncology and Community Health Sciences at the University of Calgary. He holds the Armstrong Investigatorship in Molecular Cancer Epidemiology at the Cumming School of Medicine. He is the Director of Research at the Forzani & MacPhail Colon Cancer Screening Centre. He is the current co-chair for the Canadian Cancer Statistics Advisory Committee and Advisor for the OncoSim All-Cancers Microsimulation Model. Dr. Brenner leads a research program at the University of Calgary focused on improving cancer screening and cancer risk reduction.

Senior Research Associate, Cumming School of Medicine, University of Calgary

Dr. Tamer N. Jarada, Ph.D., is a Data Scientist with over 15 years of academic and professional experience. Dr. Jarada’s current research is focused on using Big Data, Advanced Analytics and Machine Learning to understand and improve the quality of health systems and inform initiatives aimed at reducing the incidence, prolonging survival and enhancing outcomes of cancer. Dr. Jarada earned his Ph.D. in Computer Science from the University of Calgary. In his Ph.D. research, he addressed the demand for integrating various biological and biomedical datasets for data-driven insights in the Computational Drug Repositioning field. Dr. Jarada’s primary work and research interests are Health Informatics & Analytics, Big Data Analytics, Data Visualization, Bioinformatics, Biomedicine, Computational Biology, Machine Learning, Natural Language Processing and Network Analysis.

Research Assistant/Computer Science Intern, Cumming School of Medicine, University of Calgary

Yanbo (Ned) Liu is a research assistant and data/computer science intern interested in natural language processing and machine learning. He is pursuing a bachelor’s degree at the University of Calgary with a Data Science Minor. He joined the team in 2021 and his current responsibility includes assisting with research projects as well as building and maintaining dashboards and web applications.

Research Associate, Cumming School of Medicine, University of Calgary

Eliya Farah, received his BSc. in Biology and Math from the University of Ottawa in 2019. Followed by a MSc. in Public Health from McGill University in 2021. Eliya has extensive research experience in the field of cancer epidemiology. He has co-authored over 10 peer-reviewed articles and is a former lead member of the COVID-19 and Cancer Task Force.

Data Management Specialist, Cumming School of Medicine, University of Calgary

John Hutchinson is a Data Management specialist and has primarily worked with Bioinformatics cancer research and development of statistics dashboards. He has recently graduated with a Bachelor of Health Sciences at the University of Calgary, where he completed his thesis on the prediction of colorectal cancer using machine learning.

Postdoctoral Associate, Cumming School of Medicine, University of Calgary

Dr. Matt Warkentin, PhD, is a molecular epidemiologist with over 10 years of experience in the areas of cancer epidemiology, biostatistics, and machine learning. His research is at the intersection of molecular epidemiology, quantitative imaging, and big data, as it relates to cancer. This includes analysis of genomics, biomarkers, and image data across several cancer sites to: (i) enhance our understanding of cancer biology and etiology, (ii) improve methods for risk-stratification and early cancer detection, and (iii) translate research into clinical settings to support decision-making and precision medicine initiatives. He has significant expertise in the application of machine learning and leading-edge artificial intelligence to medical images (e.g., CT) to improve cancer screening. Dr. Warkentin is an avid proponent of transparent, reproducible, and open-source science, and is the author and maintainer of several packages for the R programming language, and co-author/contributor to several more packages for the R and Python languages.