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 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 (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 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 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.