This profile is built from public research funding records (CIHR, NSERC and SSHRC). We have not imported them from a University of Toronto directory, so their publications, courses and email address may be missing. Find their university profile.
Research
Latest funding
- $100,000
Older Adults' Hospital Admissions for Unmet Community Support Needs
CIHR · 2025 · Co-investigator
- $20,000
Workshop on connection and understanding around national data, AI modelling and public Health
CIHR · 2023 · Co-investigator
- $99,972
ARtificial intelligence to Enable Automated REspiratory illness Surveillance through Primary care (AREA-RESP)
CIHR · 2022 · Co-investigator
Older Adults' Hospital Admissions for Unmet Community Support Needs
Principal investigators: Lapointe-Shaw, Lauren; Gopalkrishnan, Rahul; Jones, Aaron T; Razak, Fahad; Roberts, Surain B; Verma, Amol
Keywords: Ageing; Alternative Level Of Care; Home And Community Care; Hospital Crowding; Older Adults; Social Admissions; Transitions Of Care
Workshop on connection and understanding around national data, AI modelling and public Health
Principal investigators: Rosella, Laura C
Keywords: Artificial Intelligence; Data; Data Governance; Public Health
ARtificial intelligence to Enable Automated REspiratory illness Surveillance through Primary care (AREA-RESP)
Principal investigators: Pinto, Andrew D; Price, David J
Keywords: Artificial Intelligence; Covid-19; Influenza; Machine Learning; Natural Language Processing; Primary Health Care; Public Health; Respiratory Illness; Sars-Cov-2; Surveillance
Artificial Intelligence for Public Health (AI4PH) Training Platform
Principal investigators: Rosella, Laura C; Anderson, Maureen; Buckeridge, David L; Fan, Lisa; Lee, Joon; Lix, Lisa M; Osgood, Nathaniel D
Keywords: Artificial Intelligence; Big Data; Decision Making; Health Equity; Machine Learning; Public Health; Social Determinants Of Health; Training
COVID-19 Variant Supplement - Evaluating the differential impact of what we have done, as we prioritize what to do next: a multi-provincial intervention modeling study using population-based data
Principal investigators: Mishra, Sharmistha; Baral, Stefan D; Janjua, Naveed Z; Katz, Alan; Kwong, Jeffrey C; Maheu-Giroux, Mathieu; Sander, Beate H; Williamson, Tyler
Keywords: Health Administrative Data; Intervention Impact; Population Health; Transmission Dynamics
COVID-19 Variant Network - Evaluating the differential impact of what we have done, as we prioritize what to do next: a multi-provincial intervention modeling study using population-based data
Principal investigators: Mishra, Sharmistha; Baral, Stefan D; Janjua, Naveed Z; Katz, Alan; Kwong, Jeffrey C; Maheu-Giroux, Mathieu; Sander, Beate H; Williamson, Tyler
Keywords: Health Administrative Data; Intervention Impact; Population Health; Transmission Dynamics
Evaluating the differential impact of what we have done, as we prioritize what to do next: a multi-provincial intervention modeling study using population-based data
Principal investigators: Mishra, Sharmistha; Janjua, Naveed Z; Katz, Alan; Kwong, Jeffrey C; Maheu-Giroux, Mathieu; Williamson, Tyler
Keywords: Health Administrative Data; Intervention Impact; Population Health; Transmission Dynamics
Identifying and mitigating bias in machine learning models used in population health
Principal investigators: Pinto, Andrew D
Keywords: Artificial Intelligence; Bias; Equity; Guideline Development; Health Inequities; Machine Learning; Model Development; Population Health; Public Health
Wintertime Seasonality of Influenza and Invasive Bacterial Disease: Influence of Environment, Pathogen Interactions, Time Scales, and Geography
Principal investigators: Fisman, David N
Keywords: Epidemiology; Infectious Diseases; Mathematical Modeling And Simulation; Public Health Surveillance
From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.
A short, specific email works best. This draft uses one of their recent papers; replace the parts in brackets with your own details before sending.