Morteza Zihayat

Associate Professor

Morteza Zihayat received his Ph.D. in Computer Science from York University, Canada (2016). He then held positions as a Postdoctoral Fellow at the University of Toronto’s Faculty of Information and as a Research Fellow at IBM Canada, working on high-performance computing and data analytics projects with a focus on social networks and AI-driven tools for mental health. In 2017, he joined the Ted Rogers School of Management at Toronto Metropolitan University as an Assistant Professor, later becoming an Associate Professor, where he advanced the application layer of artificial intelligence (AI) through extensive industry collaborations. In 2025, he was appointed Canada Research Chair in Human-Centred Artificial Intelligence and is currently a faculty member in the Department of Electrical, Computer, and Biomedical Engineering at TMU's Faculty of Engineering and Architectural Science.

Dr. Zihayat's research lies at the intersection of AI, security, and society, with a focus on building fair and transparent AI systems. His expertise spans human-centered AI, fair information retrieval systems, and blockchain-enabled AI infrastructures. He has collaborated with organizations including the Toronto Transit Commission, The Globe and Mail, AT&T, and IBM's Centre for Advanced Studies, applying AI in sectors such as healthcare, digital media, and social networks.

He has published extensively in leading journals and conferences, including IEEE TKDE, Machine Learning Journal, Information Processing & Management, SIGIR, SIGKDD, ECIR, and SIAM SDM, among others. His research has attracted over $1.7 million in external funding from agencies such as NSERC, Mitacs, and multiple industry partners. Dr. Zihayat serves as Associate Editor of the Computational Intelligence Journal and is an active reviewer for top-tier venues. His work is unified by a singular mission: advancing AI systems that are transparent, accountable, and designed to serve the public good.

RESEARCH INTERESTS

• Data Analytics
• Human-centered AI
• Decentralized AI
• Information Retrieval
• Graph mining

AWARDS AND RECOGNITION

• Canada Research Chair (Tier 2) in Human-Centered AI, 2024
• Dean's Outstanding Scholarly, Research, and Creative (SRC) Activity Award, 2023
• Best Short Paper Award - European Conference on Informatio Retrieval (ECIR), 2023
• IBM CAS Faculty Fellow, 2021

SELECTED PAPERS

• R. Etemadi, M. Zihayat, K. Feng, J. Adelman, F. Zarrinkalam, E. Bagheri, "Jointly Learning Content-Network Representations for Collaborative Expert Discovery," Machine Learning Journal, 2025.
• S. Salamat, N. Arabzadeh, Sh. Seyedsalehi, A. Bigdeli, M. Zihayat, E. Bagheri, "A Contrastive Neural Disentanglement Approach for Query Performance Prediction," Machine Learning Journal, 2025.
• Sh. Seyedsalehi, S. Salamat, N. Arabzadeh, S. Ebrahimi, M. Zihayat, E. Bagheri, "Gender Disentangled Representation Learning in Neural Rankers," Machine Learning Journal, 2024.
• X. Yang, A. Joukova, M. Zihayat, A. Ayanso, "Social Influence-based Contrast Language Analysis Framework for Clinical Decision Support Systems," Decision Support Systems, 2022.
• H. Davoudi, Z. Rashidi, M. Zihayat, A. An, G, Edall, "Paywall Policy Learning in Digital News Media," IEEE Transactions on knowledge and Data Engineering, 202