成人VR视频 Professors Jackie Chi Kit Cheung and Lijun Sun have received funding for their research projects on reasoning and responsible artificial intelligence (AI) from the Canadian Institutes of Health Research (CIHR), Natural Sciences and Engineering Research Council of Canada (NSERC), and Social Sciences and Humanities Research Council (SSHRC), .
The funding comes from the Canada-France call for proposals on AI, a joint research initiative launched in 2024 by the Agence nationale de la recherche (ANR) in France and Canada鈥檚 Tri-agencey partners鈥擭SERC, SSHRC, and CIHR鈥攚ith support from the Institut de valorisation des donn茅es (IVADO).
The program supports collaborative, multidisciplinary projects from within the Canadian and French research ecosystems focused on generative AI and the security and safety of embedded AI. Ten projects have received a total of $3,292,500 in funding in this competition.
Recipients:
, Associate Professor, School of Computer Science
Project: REGARD - Robust Evaluation of Generative AI in Real-World Environments
Collaborators: Edith Law (Waterloo University), Pablo Piantanida (Centrale Sup茅lec), Fr茅d茅ric B茅chet (Universit茅 Aix-Marseille), and Geraldine Damnati (Orange Labs).
Funder: SSHRC ($300,000) and IVADO ($60,000)
The REGARD project aims to advance the evaluation of language generation systems by understanding their behaviour, measuring performance, generalization, and robustness, and assessing their societal impacts. By integrating social, algorithmic, and theoretical perspectives, Cheung will develop frameworks, protocols, evaluation methods, and case studies to analyze benefits and harms, assess limitations, and ensure models are reliable, value-aligned, and applicable in real-world settings.
Lijun Sun, Associate Professor, Department of Civil Engineering
Project: MobAgent - Large Language Model Agent for Mobility Reasoning and Synthesis
Collaborator: Latifa Oukhellou (Universit茅 Gustave Eiffel)
Funder: NSERC ($300,000)
MobAgent will create realistic, high-resolution human mobility data from diverse and sparse sources like transit cards, call records, and social media鈥攕ources that current AI methods struggle to integrate, thereby limiting their application in transportation planning and urban management. Leveraging large language models to enhance deep generative models, MobAgent will produce privacy-preserving data that can capture complex travel patterns. These methods will provide reproducible, adaptable mobility data to support sustainable transportation, equitable urban access, and evidence-based planning, while fostering international France-Canada collaboration.
Photograph: 成人VR视频 Professors Jackie Chi Kit Cheung and Lijun Sun