Φ Lab

The Predictive Health Informatics Lab is led by Dr. Dan Lizotte at the University of Western Ontario. (The guy on the right.) Dr. Lizotte is jointly appointed to the Department of Computer Science in the Faculty of Science and the Department of Epidemiology & Biostatistics in the Schulich School of Medicine & Dentistry.

We develop and apply machine learning and biostatistical methodology, broadly defined, to health research problems. Methods range from classification and regression to unsupervised representation learning to reinforcement learning, and problems range from public health to primary, secondary, and tertiary healthcare. A key component of our approach is to have all analyses be interpretable and explainable, with the goal of providing decision support for challenging problems. We strive for meaningful multidisciplinary collaboration with health researchers and stakeholders on projects that lead to new knowledge both in data science methodology and in health research.

Brent Davis

Brent is a PhD Candidate in the Department of Computer Science and a member of the Φ Lab and Insight Lab. He was previously the instructor for MMASc 9251A: Professional Computing for Applied Scientists and presently the Teaching Assistant for Unstructured Data. As of March 1st 2019, Brent will also be a Mitacs Accelerate Intern. This work is with the Parkwood Institute and IBM with the target of improving mental health resources for Canadian Veterans. His research interests are two-fold. The first is in applying machine learning to search techniques for social media datasets, with a focus on public health applications. The second is in creating visual analytics systems which allow for interactive exploration of the information spaces these techniques exist in.

Ethan Jackson

Ethan is a PhD Candidate in the Department of Computer Science and the Brain and Mind Institute, Postgraduate Affiliate of the Vector Institute, and a Research Associate of the Φ Lab.  His research interests are in deep learning framework development and predictive time series modelling in health informatics and biological systems.

Jaky Kueper

Jaky (Jacqueline) is piloting a combined PhD program in Epidemiology and Computer Science and is a recent graduate of the pan-Canadian Transdisciplinary Understanding and Training on Research in Primary Health Care (TUTOR-PHC) program. Her research integrates epidemiology and computer science to develop, apply, and evaluate methods for supporting care decisions within Primary Health Care settings. She is supported by a Frederick Banting and Charles Best Canada Graduate Scholarship – Doctoral Award from the Canadian Institutes of Health Research (2018-2021). 

Demetri Pananos

Demetri is currently a PhD student in the department of Epidemiology & Biostatistics.  His research concerns Bayesian methods for drug dosing regimes.  Demetri is a firm believer in open science, reproducibility, and interdisciplinary collaboration.

Nathan Phelps

Nathan is a Master’s student in the Department of Computer Science. Through a partnership with Parkwood Hospital, his research will involve using reinforcement learning techniques to work towards optimizing the treatments chosen for people with spinal cord injuries. This past summer, Nathan worked under Dr. Douglas Woolford of the Department of Statistical and Actuarial Sciences, using statistical and machine learning techniques to model forest fire occurrences in a region of Alberta. He is currently continuing this research on a part time basis.

Maede Sadat Nouri

Maede is currently a Master’s student in the Department of Computer Science, and a member of both Φ Lab and Insight Lab.  Her previous Master’s degree in Applied Statistics provided her with a broad knowledge of statistical analysis, and applies it to her current research in the area of machine learning and interactive visualization.

Alliance for Healthier Communities (https://www.aohc.org)

Patrick Kim

Patrick graduated with his MSc in Epidemiology in 2018, co-supervised by Drs. Dan Lizotte and Amanda Terry. His thesis is titled “Chronic Disease Risk Prediction Models and their Impacts on Behavioural and Health Outcomes: A Systematic Review and Meta-analysis.” Patrick is currently working for York Region Public Health.

Lavanya Uruthiramoorthy

Lavanya graduated with her MSc in Epidemiology in 2017, co-supervised by Drs. Monali Malvankar and Dan Lizotte. Her thesis is titled “Predicting Important Patient-Reported Outcomes for Glaucoma Management: Cross-Sectional Study.” Lavanya is currently working as a health research coordinator at the University of Toronto.