Speakers

Prof. Xinguo Yu

Central China Normal University, 

China

BIO: Prof. Yu Xinguo is the Dean of the CCNU Wollongong Joint Institute and a Professor at the National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, China. He also holds an adjunct professorship at the University of Wollongong, Australia. He is the Chair of the Hubei Society of Artificial Intelligence in Research and Education. Prof. Yu's research primarily focuses on intelligent educational technology, intelligent research, educational robotics, multimedia analysis, computer vision, and machine learning. With over 170 published research papers, he is a recognized leader in his field. Prof. Yu serves as an Associate Editor and Guest Editor for several international journals and has contributed significantly to the global academic community by serving as General Chair, Keynote Speaker, and Program Chair for more than 30 international conferences. Since 2021, he has pioneered and led the annual International Conference on Intelligent Education and Intelligent Research.

Title: The Transformative Impact of Artificial Intelligence on Modern Life

Abstract: Artificial Intelligence (AI) is swiftly becoming a transformative force across diverse industries, reshaping how we live and work. This keynote speech delves into several pioneering areas of AI, beginning with its role in advancing research and showcasing key principles and recent breakthroughs. The discussion then turns to its profound impact on education, demonstrating its potential to revolutionize learning experiences. Finally, the talk explores the development of smart vehicles and autonomous driving technologies. By offering a forward-looking perspective, this speech underscores AI's immense potential to enhance and reshape our future way of life. 

Prof. Wanyang Dai

Nanjing University, China

BIO: Wanyang Dai is a Distinguished Professor at Nanjing University and Chief Scientist at Su Xia Control Technology. He is the current President and CEO of the U.S.-based (blockchain and quantum computing) SIR Forum, President of the Jiangsu Probability and Statistical Society, and Chairman of the Jiangsu BigData-Blockchain and Smart Information Special Committee. He received his Ph.D. in mathematics, systems, and industrial engineering from the Georgia Institute of Technology in the USA. He was an MTS and principal investigator at U.S.-based AT&T Bell Labs (currently Nokia Bell Labs) with a project called “Technology Transfer,” now called a cloud system. He was the Chief Scientist at the DepthsData Digital Economic Research Institute. He published numerous influential papers in big-name journals, including Quantum Information Processing, Operations Research, Operational Research, Queueing Systems, Computers and Mathematics with Applications, Communications in Mathematical Sciences, and the Journal of Computational and Applied Mathematics. He has received various academic awards and has presented over 50 keynote and plenary speeches at IEEE/ACM, big data and cloud computing, quantum computing and communication technology, computational and applied mathematics, biomedical engineering, mathematics and statistics, and other international conferences. He has been serving as IEEE/ACM conference chairs, editors-in-chief, and editorial board members for various international journals ranging from artificial intelligence, machine learning, data science, wireless communication, pure mathematics, and statistics to their applications.

Title: Quantum transformer with quantum cloud computing for robot routing and IoV based vector decision-making 

Abstract: We develop a unified quantum transformer (called Q-Transformer) including quantum encode-decode coupling processes, which has the prediction and adaptive feedback control capability. This newly designed Q-Transformer is integrated into our quantum cloud computing platform as its smart federated learning engine, which is supported by our recently designed and justified neutral atom quantum computer. The main advantage to develop such an integrated big model platform system is to conduct high-dimensional vector decision-making appeared in real-world systems ranging from smart agents (e.g., multi-task man-shaped robots) to wireless networks such as semantic communication and generative metaverse over quantum 6G, IoT, and IoV. Specific applications such as multiple objective based robot routing, resource allocation, and dynamic pricing will be given. Related optimization and equilibrium policies will be trained with numerical simulations. 

Prof. Hon Wai Leong

National University of Singapore

BIO: Prof. Hon Wai Leong (梁汉槐) is with the Department of Computer Science at the National University of Singapore. He received the B.Sc. (Hon) degree in Mathematics from the University of Malaya and the Ph.D. degree in Computer Science from the University of Illinois at Urbana-Champaign. He also had visiting appointments at UIUC, UCSD, and also in Shanghai Institute of Biological Sciences, CAS.

His research interest is in the design and analysis of algorithms for optimization problems from diverse application domains including VLSI-CAD, transportation logistics, multimedia systems, and computational biology. 

As a teacher, he specializes in finding simple ways to explain complicated subject matters and loves to integrate CT (computational thinking) and growth mindset in his classes. Recently, he was involved in teaching two innovative courses: "GEQ1000: Asking Questions", and "GET1031: Computational Thinking (no coding)". Both courses are general education courses for all students (esp for non-majors).

He is passionate about fostering the love for Computing and Mathematics to all, and especially to young students. He works with high school students and teachers via outreach talks and fun workshops on creative problem solving, CT, matheMAGIC. He also mentors high school students’ research projects. He gives general talks on "Computational Thinking (CT) for anyone and everyone", especially to teachers and parents. He also teaches Polya Problem Solving Process and how to apply it to creative problem solving.

In 1992, he founded the Singapore training program for the International Olympiad in Informatics (IOI). In 2008, he (together with others) started an annual coding competition for primary school students (code::XtremeApps competition: Junior category). He is also an advisor to a coding academy, LccL (Learn to Code and Code to Learn) meant for children from 5 to 18.

Recently, Prof Leong took up a part-time visiting appointment with the CCNU-UOW-JI (Central China Normal University, University of Wollongong Joint Institute). He is a member of ACM, IEEE, ISCB, and a Fellow of the Singapore Computer Society.

Title: Leveraging ChatGPT and PPSP (Polya Problem Solving Process) for MetaCognition: Is it possible?

Abstract: In recent years, there is increasing use of ChatGPT and IOT to build intelligent AI Assistants for many domains. However, in the domain of creative problem solving, especially in mathematics, there appear to be still a gap. This is especially true in the realm of AI Assistants that can give customized prompt to students who are facing difficulties when solving some complicated math problems. 

For this challenge, the Polya (4-steps) Problem Solving Process may have potential to help. In the 1940s, the late Professor Polya has proposed a process that breaks down the problem by offering a list of possible simpler questions to try out (in modern AI language, these will be called short prompts). 

In this talk, I propose a project (not carried out yet) to have ChatGPT and IOT leverage on PPSP to potentially build an AI Assistant that can progressively learn MetaCognition, first for solving mathematical problem, such as those in high school mathematics. Then the resulting PPSP-AI-Assistant can give customized intelligent prompts to students when students are stuck in problem solving, and can assist the students to reflect on their solutions. This may even help the students to progressively learn metacognitive skills.