Date
16 September 2024 (Monday)
Time
9:30 am to 4:00 pm
Location
Conference Centre (E-P/F-01), Tai Po Campus, The Education University of Hong Kong
Organised by
Rundown
09:30 AM – 10:00 AM |
Registration |
10:00 AM – 11:10 AM |
Launching Ceremony of Artificial Intelligence Research and Education Alliance |
Welcoming Address
Prof. John LEE
President,
Chair Professor of Curriculum and Instruction,
The Education University of Hong Kong
Opening Remarks
Prof. May CHENG
Vice President (Academic),
Chair Professor of Teacher Education,
The Education University of Hong Kong
Prof. Guandong XU
Chair Professor of Artificial Intelligence,
Director of Centre for Learning, Teaching and Technology (LTTC),
Director of University Research Facility of Data Science & Artificial Intelligence (UDSAI),
The Education University of Hong Kong
Invited Talk 1
Topic: From Visible to Invisible: Exploration of AI for Education at HKUST(GZ)
Prof. Lionel Ming-Shuan NI
Founding President of HKUST (Guangzhou),
Chair Professor, Department of Computer Science and Engineering,
The Hong Kong University of Science and Technology
Abstract
The increasing utilization of Artificial Intelligence (AI) in education is poised to revolutionize the learning and teaching landscape. This presentation will demonstrate how faculty members at HKUST(GZ) are leveraging AI tools in their teaching to introduce innovative and diverse instructional approaches on campus, with a focus on fostering a student-centered, personalised and effective learning environment. The goal of integrating AI into education at HKUST(GZ) is to explore how teachers can naturally incorporate AI tools into their educational activities, moving from using AI intentionally to using it as easily as they use PowerPoint or Excel or Words. This shift from deliberate AI use to natural integration aims to make AI a seamless part of the educational experience, making teaching more effective and innovative, signifying a promising and forward-thinking direction for the future of education.
Biography of Prof. Lionel Ming-Shuan NI
Professor Lionel M. Ni is the Founding President of the Hong Kong University of Science and Technology (Guangzhou) (HKUST(GZ)). Professor Ni earned his PhD degree in Electrical Engineering from Purdue University in 1980. He served as Vice Rector (Academic Affairs) and Chair Professor in the Department of Computer and Information Science at the University of Macau; Chair Professor and Head of Department of Computer Science and Engineering, Dean of HKUST Fok Ying Tung Graduate School and Special Assistant to the President; Professor in Computer Science and Engineering at Michigan State University (1981 to 2002), the Microelectronic Systems Architecture program director at US National Science Foundation (1995-1996) co-founder and CEO of CC&T Technologies, Inc., Michigan (1998-2001), and the Chief Scientist of the China’s National 973 Program on Wireless Sensor Networks (2006 to 2011).
Professor Ni’s research interests include high-performance computing, internet technologies, mobile computing, wireless networking, big data, and intelligent computing. He has published three books and over 360 refereed journal and conference articles with over 37,000 citations on Google Scholar. The winner of eight best paper awards, he has multiple achievements including ownership of 28 US/China patents and having supervised 73 well-placed PhD students.
11:10 AM – 11:25 AM |
Tea Break |
11:25 AM – 12:10 PM |
Invited Talk |
Invited Talk 2
Topic: User-Centric Evaluation of Large Language Models
Prof. Min ZHANG
Professor,
Department of Computer Science and Technology,
Tsinghua University
Abstract
Large language models (LLMs) are emerging tools increasingly used across various domains, making user-centric performance assessment crucial for guiding service selection. Existing benchmarks often overlook user-specific needs, focusing on predefined general model capabilities, such as world knowledge and reasoning. This talk aims to study user experiences, understand users’ needs and expectations, and evaluate LLM performance in real-world scenarios from a user-centric perspective. A benchmark is introduced, along with a new User Reported Scenarios (URS) dataset, comprising 1846 real-world cases from 712 participants across 23 countries/regions, categorized by the user intents taxonomy. It aligns well with human preferences, validating it as an effective, user-centric evaluation of LLMs.
Biography of Prof. Min ZHANG
Dr. Min Zhang is a full professor in the Dept. of Computer Sci. & Tech., Tsinghua University. She is the chief director of the AI Lab. She specializes in Web search, personalized recommendation, and user modeling. She has been the Editor-in-Chief of ACM Transaction on Information Systems (TOIS) since 2020, and also serves as the General Chair of ACM MM’25, and PC Chair of CHIIR’24, RecSys’23, CIKM’23, ICTIR’20, WSDM’17, etc. She won the “Test-of-Time” award at SIGIR’24.
12:10 PM – 02:00 PM |
Lunch Break |
02:00 PM – 02:45 PM |
Invited Talk |
Invited Talk 3
Topic: Generative Neighbor Augmentation for Robust Graph Learning
Prof. Zhiguo GONG
Professor of the State Key Laboratory of Internet of Things for Smart City,
Head of Department of Computer and Information Science,
University of Macau
Abstract
Generally speaking, the performance of graph learning technologies depends on the balance of data distribution, such as a uniform distribution of node labels and node degrees. However, the graph data in the real world is usually unbalanced because the data is often gradually established over time, and the nodes of new categories are generally sparse with quite few neighbors. In this talk, we introduce our generative algorithms for automatic neighbor augmentations.
Biography of Prof. Zhiguo GONG
Gong Zhiguo is currently a professor at the State Key Laboratory of Internet of Things for Smart Cities, University of Macau, and a professor and the associate dean of Faculty of Science. He received his Ph.D. from the Chinese Academy of Sciences in 1998. He is currently engaged in research on machine learning and data mining. His main results have been published in international conferences and journals such as SIGIR, CIKM, IJCAI, ICDE, VLDB, SIGMOD, KDD, AAAI, TODS, TIST, TKDE, TKDD, VLDBJ, etc. He is the conference chair of IEEE/WIC/ACM WI/IAT 2012, WAIM2014, and Apweb-WAIM2018, the local chair of ICDE2019 and IJCAI2019, IJCAI2023, and the program committee chair of PAKDD2019 and IEEE ICBK2021.
02:45 PM – 03:45 PM |
Panel Discussion |
Panel Discussion
Topic: Navigating AI in Education: Opportunities and Challenges
Moderator
Prof. Guandong XU
Chair Professor of Artificial Intelligence,
Director of Centre for Learning, Teaching and Technology (LTTC),
Director of University Research Facility of Data Science & Artificial Intelligence (UDSAI),
The Education University of Hong Kong
Panellist
Prof. Lionel Ming-Shuan NI
Founding President of HKUST (Guangzhou),
Chair Professor, Department of Computer Science and Engineering,
The Hong Kong University of Science and Technology (Guangzhou)
Panellist
Prof. Min ZHANG
Professor,
Department of Computer Science and Technology,
Tsinghua University
Panellist
Prof. Zhiguo GONG
Professor of the State Key Laboratory of Internet of Things for Smart City,
Head of Department of Computer and Information Science,
University of Macau
Panellist
Prof. Chee Kit LOOI
Research Chair Professor of Learning Sciences,
Department of Curriculum and Instruction,
The Education University of Hong Kong
03:45 PM – 04:00 PM |
Closing Remark |