Réseau de l’ARC

Stephen Czarnuch

Membre de :

Comité consultatif du réseau d'universitaires, de chercheurs et de cliniciens (ARCNAC) et sous-comités Réseau de l’ARC

Province : Terre-Neuve-et-Labrador

Affiliation : Memorial University

Institution: Memorial University of Newfoundland

Membre de :

Comité consultatif du réseau d'universitaires, de chercheurs et de cliniciens (ARCNAC) et sous-comités Réseau de l’ARC

Province : Terre-Neuve-et-Labrador

Affiliation : Memorial University

Institution: Memorial University of Newfoundland

Dr. Stephen Czarnuch, Ph.D., is an Associate Professor of Biomedical Engineering, joint-appointed to the Faculty of Engineering and Applied Science and the Faculty of Medicine, and director of the Centre for Artificial Intelligence at Memorial University. He is also currently serving as the co-chair of the joint Masters of Applied Science in Software Engineering and Masters of Artificial Intelligence, co-hosted by the Department of Electrical and Computer Engineering and Department of Computer Science, and is the program coordinator for the Centre for Artificial Intelligence. Dr. Czarnuch obtained his Ph.D. from the University of Toronto in Biomedical Engineering, focusing on human motion and activity detection using computer vision and machine learning. He has extensive experience developing technologies for vulnerable populations, implementing a holistic, user-centered design philosophy centered on identifying user needs and evaluating health outcomes. His public safety research focuses on public safety communicators (e.g, 911, call-takers, dispatchers), with a particular interest in next-generation 911. His research is inherently interdisciplinary, lying at the intersection of engineering, computer science, medicine, gerontology, rehabilitation, psychology, and sociology. Specifically, he seeks to develop relevant, accessible, acceptable and adoptable patient-oriented technological interventions based on autonomously tracking human motion using computer vision. Further, he emphasizes the evaluation of technology efficacy by connecting academic research with healthcare providers and patients in a real-world context. His technical focus is on machine learning, deep learning, and computer vision.

Chercheur

Projets en cours

  • Analyse du programme de formation en corrections de Service correctionnel Canada

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