AI @ York


With its interdisciplinary network of scientific, engineering, societal, ethical and legal researchers, York University is building AI solutions for the many important challenges facing our society today.


AI@YorkU aligns with York’s emphasis upon creativity, innovation and global citizenship, and its reputation as a leader in research that crosses disciplinary boundaries. York will continue to build bridges linking breakthroughs in the science and technology of AI to application domains addressing critical societal needs, while advancing our understanding of the ethical, legal and governance dimensions of this transformative technology.



AI research at York is broadly distributed across faculties and departments. Research ranges from the development of new brain-inspired AI systems, through application to smart cities, disaster management, emergency planning and disease transmission models, to novel legal and governance frameworks. A key focus is the research and development of next generation intelligent and interactive AI systems that can work closely and adaptively with humans.

Teaching & Learning

York offers more than 80 AI-related courses that range from the mathematical and computational foundations of machine learning, data mining, computer vision and robotics through to applications relating to gaming and the performing arts, business management of AI systems and the underlying philosophy, law and ethics of AI.


AI research at York is intensely collaborative, involving many industry partners from start-ups to multinationals, as well as public sector agencies and hospitals, particularly in the GTHA.
VISTA (2016-2023)
BRAIN (2016-2021)
ISSUM (2017-2022)
DAV (2015-2021)
DITA (2018-2024)


York University has a thriving AI start-up culture supported by the commercialization experts at Innovation York, IP Osgoode, the Innovation Clinic and the Bergeron Entrepreneurs in Science and Technology (BEST) labs. Application areas include attentive vision systems for sports and security, mobility assessment technologies, construction and real-estate.


York maintains more than 125 international AI partnerships with institutions in China, India, Singapore, South Korea, Finland, France, Germany, Sweden, the UK and the US. For example, York University’s Vision: Science to Applications program has partnered with ten international research institutions in China, Germany, the Netherlands, the UK, the US and Austria. York is a co-sponsor, with Xi’an Jiatong University, of the international journal Big Data and Information Analytics.

Faculty Positions

New AI Faculty Hires:
LA&PS: Ian Stedman
Lassonde: Gene Cheung
Science: Joel Zylberberg
Health: Ingo Fruend
LA&PS: Regina Rini

Student Opportunities


Schulich School of Business
Master of Business Analytics


Schulich School of Business 
Master of Management in Artificial Intelligence

AI in Action

AI research at York is broadly distributed across faculties and departments.

James Elder - Computer Vision, Computational Neuroscience
Regina Rini - Ethics of Technology
Richard Wildes - Computer Vision
Kristin Andrews - Animal and Machine Intelligence
Michael Jenkin - Autonomous Systems
Petros Faloutsos - Virtual Human Modeling, Crowd Simulation
Muhammad Ali Khalidi - Philosophy of Artificial Intelligence
John K. Tsotsos - Computer Vision, Computational Neuroscience, Human Vision, Robotics
Shayna Rosenbaum - Cognitive Neuroscience, Spatial Navigation, Memory and Aging
Ian Stedman – Public Policy & Governance of AI
Dan Zhang - Intelligent Manufacturing and Robotics; Intelligent Engineering Equipment; Individualized Design and Manufacturing
Mark-David Hosale - Computational Arts, Digital Performance, Cybernetics, Installation Art, Interaction Design
Manos Papagelis - Big Data Analytics, Data Mining, Graph Mining, Machine Learning
Christo El Morr - Health Virtual Communities, eHealth, Hospital Readmission
Huaiping Zhu - Infectious Diseases Modeling; Climate Change
Usman Khan - Water Resources Engineering
Aijun An - Data mining, Machine Learning
Gunho Sohn - Computer Vision, Photogrammetry
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Verena Gottschling - Cognitive Skills and Digitalization, Learning, Affect and Emotion, Pain
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Gene Cheung - Graph Signal Processing, Image Representation & Processing, Graph Spectral Machine Learning
Hui Jiang - Machine learning
Joel Zyleberg - Vision, computational neuroscience, brain-driven deep learning
Vassilios Tzerpos - Deep Learning and Audio
Hjalmar Turesson - Unsupervised representation learning
Marcus Brubaker - Computer Vision and Machine Learning
Ikjyot Singh Kohli - Understanding the mathematical structure of neural networks
Steven Wang - Machine Learning and Big Data with application to health care
Ali Sadeghi-Naini - Precision Medicine


get in touch

Are you an academic looking to collaborate on research, current/prospective student looking for study opportunities, or are interested in becoming involved with AI@YorkU?