Scholar
Bang Liu
Google Scholar ID: lmfAnP4AAAAJ
Associate Professor at the University of Montreal, Canada CIFAR AI Chair at Mila
Citations & Impact
Citations
2,485
H-index
27
i10-index
55
Publications
20
Co-authors
24
list available
Contact
Publications
Resume (English only)
Academic Achievements
- - Publications: Multiple papers accepted at ACL 2025, PAKDD 2025, ICLR 2025, NAACL 2025, EMNLP 2024, IJCAI 2024, ACM Multimedia 2024, ECCV 2024, etc.
- - Awards: WAIC Yunfan Award (Rising Star) 2024
- - Projects: Open-sourced AEIVA: An Evolving Intelligent Virtual Assistant
- - Positions: Area Chair for NeurIPS 2025, IVADO Researcher
Research Experience
- - June 2025 - Current: Associate Professor at Université de Montréal, Canada
- - August 2020 - May 2025: Assistant Professor at Université de Montréal, Canada
- - Affiliations: Université de Montréal, Mila - Quebec AI Institute, Institut Courtois
Education
- - Ph.D. Degree: January 2020 from the Dept. of Electrical and Computer Engineering, University of Alberta (UA), Canada
- - M.Sc. Degree: September 2015 from the Dept. of Electrical and Computer Engineering, University of Alberta (UA), Canada
- - B.Eng. Degree: June 2013 from the Dept. of Electronic Engineering and Information Science, University of Science and Technology of China (USTC), China
Background
- - Research Interests: natural language processing, multimodal & embodied learning, theory and techniques for AGI (e.g., understanding and improving large language models), and AI for science (e.g., health, material science, XR)
- - Professional Field: Computer Science and Operations Research
- - Introduction: Bang Liu is an Associate Professor in the Department of Computer Science and Operations Research (DIRO) at the University of Montreal (UdeM). He is a member of the RALI laboratory (Applied Research in Computer Linguistics) of DIRO, a member of Institut Courtois of UdeM, an associate member of Mila – Quebec Artificial Intelligence Institute, and a Canada CIFAR AI (CCAI) Chair.
Miscellany
- - Looking for highly-motivated students to work on natural language processing, data mining, machine learning, and a broad range of topics related to artificial intelligence
