Sadaf Salehkalaibar is an Assistant Professor in the Department of Computer Science at the University of Manitoba, Winnipeg, Canada. She holds an office in the EITC building (E2-416) and has previously held academic positions at the University of Tehran, University of Toronto as a research associate, and visiting roles at McMaster University, Telecom Paristech, and National University of Singapore. Her research focuses on explainable artificial intelligence, generative models, and information theory with an emphasis on rate-distortion-perception tradeoffs in video and image processing. Her educational background includes teaching courses such as Signals and Systems, Digital Signal Processing, and Network Security at the University of Tehran. She currently teaches COMP4190 (Artificial Intelligence) at the University of Manitoba. Research interests revolve around developing efficient algorithms for AI systems, with key contributions in learned video compression, federated learning, and privacy-preserving techniques. Notable work includes the M22 algorithm for communication-efficient federated learning and the NSERC Discovery Grant-funded project on data-driven learning efficiency. Recent publications highlight advancements in perception loss functions, Gaussian vector source analysis, and secure distributed hypothesis testing. She actively serves on editorial boards (e.g., IEEE Transactions on Communications) and conferences (ISIT, ITW). Awards include the prestigious NSERC Discovery Grant (2025). Supervision highlights 13 MSc students at the University of Tehran, focusing on topics like privacy-preserving systems and distributed learning. Labs/teams: Leads research group at University of Manitoba focusing on AI and information theory applications in multimedia systems.
