Featured Speakers
Ali Etemad
Presentation: “Toward AI-driven Understanding of Health and Emotions Everywhere”
Dr. Etemad is an Associate Professor in the Department of Electrical and Computer Engineering at Queen's University. He holds the endowed professorship of Mitchell Professor in AI for Human Sensing & Understanding and leads the Human-Centered AI and Interactive Machines (Aiim) lab.
His main area of research is human-centered machine learning and deep learning.
Dr. Etemad received his M.A.Sc. and Ph.D. degrees in Electrical and Computer Engineering from Carleton University, Ottawa, Canada, in 2009 and 2014, respectively. Prior to joining Queen’s, he held several industry positions as a lead scientist. He has published over 180 papers in top conferences (e.g., NeurIPS, ICLR, AAAI, CVPR, ECCV, ICCV, ICASSP, etc.) and journals (e.g., TMLR, T-PAMI, T-AFFC, T-IP, T-IFS, T-ITS, IoT J., JBHI, T-NSRE, T-ASLP, etc.), is a co-inventor of 10 patents, and has given over 30 invited talks. Dr. Etemad is an Associate Editor for IEEE Transactions on Affective Computing and IEEE Transactions on Artificial Intelligence. He has served as an AC/PC member and organizer for various conferences and workshops. He has received a number of awards, including the Queen's Prize for Excellence in Research, the Queen's Supervisor of the Year Award, the Queen's Instructor of the Year Award, and several Best Paper Awards (e.g., at ACM ICMI'23). Dr. Etemad’s lab and research program have been funded by the Natural Sciences and Engineering Research Council (NSERC) of Canada, Ontario Centres of Excellence (OCE), the Canadian Foundation for Innovation (CFI), Mitacs, and other organizations, as well as the private sector. He has previously held Visiting Faculty positions at the University of Cambridge and Google Research.
Samira Abbasgholizadeh-Rahimi
Presentation: “The Role of AI in Enhancing Older Adults’ Lives”
Samira Abbasgholizadeh-Rahimi, BEng, PhD, is the Canada Research Chair in AI and Advanced Digital Primary Health Care and an Assistant Professor at McGill University and Mila-Quebec AI Institute. Prof. Rahimi is affiliated scientist at Lady Davis Institute for Medical Research of the Jewish General Hospital, past elected President of Canadian Operational Research Society, and Co-Director of McGill’s Collaborative for Artificial Intelligence and Society (McCAIS).
With an interdisciplinary background, her research is about the development and implementation of advanced digital health technologies such as AI-enabled decision support tools in primary health care. Her research is dedicated to enhancing the prevention and management of diseases with a particular emphasis on vulnerable populations (e.g., older adults, those with chronic diseases).
Her work as Principal Investigator has been funded by the Fonds de recherche du Québec – Santé (FRQS), Natural Sciences and Engineering Research Council (NSERC), Roche Canada, Brocher Foundation (Switzerland), and Canadian Institutes of Health Research (CIHR).
She is the recipient of numerous awards, including the 2022 New Investigator Primary Care Research Award of North American Primary Care Research Group (NAPCRG), an award that recognizes exceptional contributions by emerging investigators in the field of primary care research.
Dimitrios Kollias
Presentation: “Affective Computing and Healthcare: Models of Affect and Approaches with a view on Fairness and Explainability”
Dr. Kollias is an Assistant Professor in AI at Queen Mary University of London, UK. He has worked as Research Scientist at Deep Render Ltd, as Consultant at Toyota Motor Europe, FaceSoft Ltd and Cogitat Ltd. He obtained the Ph.D. from Imperial College London, where he was a member of the iBUG group and recipient of the prestigious Teaching Fellowship of Imperial College London.
His research interests span the areas of multimodal machine and deep learning, trustworthy AI, computer vision, affective computing, behavior analysis & generation, digital humans, HCI, medical imaging, mental health & healthcare.
He has co-authored more than 50 publications in the top journals and conferences (e.g., IJCV, CVPR, ICCV, ECCV, AAAI, TAFFC, ECAI, Neurocomputing). He is inventor of the 'Facial Behaviour Analysis' (2021) patent in collaboration with Huawei. His research has been funded and used by many top international companies (e.g. Affectiva, Realeyes, Soul Machines, Hume AI, Gentex Technologies). He was awarded the 'Sullivan Thesis Prize' (best UK thesis award) in 2023 by BMVA. He has h-index 35, with over 4900 citations.
He has been: i) General Chair of the ABAW series of Workshops and Competitions in CVPR 2024, 2023 & 2022, ECCV 2024 & 2022, ICCV 2021 and IEEE FG 2020; ii) co-Organizer & Chair of the DEF-MIA-COV19D series of Competitions and Workshops in CVPR 2024, IEEE ICASSP 2023, ECCV 2022 and ICCV 2021; iii) co-Organizer of MRAC and REACT Workshops in ACM-MM 2024 & 2023; iv) Co-organizer of Deepfakes Detection Grand Challenge at ACM-MM 2024.
He is reviewer in most top journals and conferences in his fields. He is reviewer for evaluation of grant proposals (e.g. EU, UK, Canada, Qatar).
Michael Businelle
Presentation: “Using the Insight mHealth Platform to Rapidly Develop and Deploy Smartphone-Based Assessments and Interventions”
Dr. Michael Businelle is the Peggy and Charles Stephenson Endowed Chair in Cancer and a tenured Professor in the Department of Family and Preventive Medicine at the University of Oklahoma Health Sciences Center (OUHSC) and a member of the NCI Designated Stephenson Cancer Center (SCC).
He also co-directs the Health Promotion Research Center at OUHSC which is staffed by over 100 employees (including 28 faculty). He was recruited to the OUHSC in October 2015 to develop and direct the SCC Mobile Health (mHealth) Shared Resource. The mHealth resource is currently staffed by 9.5 employees including 6 computer scientists /engineers.
In the past 9 years, his team has developed the InsightTM mHealth platform which enables researchers to rapidly create mobile apps that can use ecological momentary assessments (EMA) and sensor data (i.e., activity monitor, mobile carbon monoxide monitor) to identify environmental, cognitive, affective, physiological, and behavioral antecedents of cancer risk behaviors (e.g., smoking, heavy alcohol use, poor diet / inactivity / obesity) and deliver context-specific adaptive interventions in real-time. To date, the mHealth resource has supported over 95 studies including 48 that were funded by the NIH, and 5 that collect data outside the US (i.e., Cambodia, Scotland, Laos).
Since 2011, Dr. Businelle has been the PI, Co-I, consultant, or mentor on 61 studies that have used smartphones to collect data and/or intervene in real-time. During this time, he has been PI on 20 studies that have been funded by the NIH, ACS, and internal funds (e.g., R34AA024584; R01MD010733; R01CA221819, P30CA225520 COVID-19 Supplement, U54MD015946 Core Study; R01MH126586), and he has a strong publication record (i.e., >200 peer reviewed publications) in the areas of health behavior change, health disparities, and mHealth.
Presenting Labs
Behavioural Health Innovations (BHI) Lab
Led by Dr. Nicole Alberts at Concordia University, BIH Lab works to improve behavioural health across the lifespan with a focus on those diagnosed with childhood cancer. It uses digital health approaches to answer key research questions and develop and test innovative interventions targeting pain and psychological outcomes.
Applied Perception Lab
The AP Lab works on developing methods to enhance perception of computer generated images. We focus on developing novel visualization techniques, display devices and interaction paradigms to enrich the users experience in clinical and health scenarios and workflows.
MuSAE lab
The MuSAE Lab conducts research in human-computer interaction (HCI) and its applications. Using our expertise in signal processing and machine learning, we develop tools to optimize human, mechanical, and interactive aspects of HCI, focusing on immersive multisensory experiences, affective computing, brain-computer interfaces, and neuroergonomics.
Ubisoft La Forge
La Forge is Ubisoft’s research and development group that brings together experts from the industry and academic sector to prototype technological innovations and improve the game-making process. With this focus on applied research, La Forge aims to fill the gap between theory and practice, while contributing to solving real-world problems through scientific publications.
Data Science Group
The McGill University Health Centre’s Data Science Group conducts informatics and machine learning research and development to advance hospital operations.
Computational Health Informatics Laboratory
CHIL is an interdisciplinary laboratory at the University of Waterloo's School of Computer Science. Led by Dr. Jesse Hoey, its focus is on enabling more efficient and easy-to-use healthcare delivery through computational mechanisms. CHIL studies large-scale data analytics problems in healthcare. Current projects include assistive technologies for the care of dementia, health tracking and interventions for the management of diabetes, computational modeling of addiction, and automated analysis of medical imaging. Dr. Hoey is the Editor-in-Chief of the IEEE Transactions on Affective Computing.
IVADO
IVADO is an interdisciplinary, cross-sectoral research and knowledge mobilization consortium whose mission is to develop and promote a robust, reasoning and responsible AI. Led by Université de Montréal with four university partners (Polytechnique Montréal, HEC Montréal, Université Laval and McGill University), IVADO brings together research centers, government bodies and industry members to co-build ambitious cross-sectoral initiatives with the goal of fostering a paradigm shift for AI and its adoption.
RahimisLab
Dr. Rahimi's research lab leverages her interdisciplinary expertise to focus on developing and implementing cutting-edge digital health technologies, particularly AI-enabled decision support tools for primary health care. The lab is committed to advancing the prevention and management of chronic diseases, including cardiovascular conditions, in primary health care with a strong emphasis on addressing the needs of vulnerable populations and older adults.
Aging Team at the Kite Research Institute
Kite Aging Team consists of more than 35 PIs and their respective labs. Together, they focus on devising solutions to help manage demographic change that will place great demands on the continuum of care, ease pressure on the healthcare system, provide additional services and supports, and assist independent living and aging in place.
KAPTICS
KAPTICS is a Montreal-based startup focused on improving the understanding of user experiences in immersive virtual environments. We provide reliable tools and expertise to accurately measure user experience by integrating advanced biosensors into AR/VR headsets. Our plug-and-play solution delivers high-quality, real-time physiological data, making research in human-computer interaction (HCI) and extended reality (XR) easier and more efficient.
The Surveillance Lab
The McGill University Surveillance Lab conducts research and development of computational methods and software that has immediate impact on improving population health through biosurveillance and population health monitoring.
Dr. Nitika Pant Pai’s Laboratory
Dr. Nitika Pant Pai leads her own laboratory from the Medicine Division of Clinical Epidemiology at the McGill University Health Centre. Its research develops and implements point-of-care diagnostics for HIV and co-infections and integrates innovation, artificial intelligence, and implementation science to address health service delivery gaps and inform global and national policies.
CoCo Lab
The research goals of the Université de Montréal’s Cognitive and Computational Neuroscience Lab is to probe the role of large-scale brain dynamics in higher-order cognition, and to investigate brain network alterations in brain disorders. To this end electrophysiological brain data (mainly MEG and EEG) is used combined with advanced methods and data analytics including complexity science and machine learning. Recent projects examine large-scale brain network dynamics in a range of cognitive processes (e.g. decision-making, creative behavior) and across different states of consciousness (resting wakefulness, sleep, dreaming, anesthesia, hypnosis, meditation and psychedelic states).
Innovation, Technology, and Cognition Laboratory (INTECOG)
INTECOG is led by Dr. Alexander Moreno, PhD, from the Centre de recherche de l’institut universitaire de gériatrie de Montréal (CRIUGM). Its research focuses on the co-construction and co-development of gerontechnologies ranging from home support to end-of-life care, such as virtual reality, social robotics, and electronic home assistants.