Invited Speakers

Invited Speakers 邀请报告人




Prof. Xiwen Zhang
Beijing Language and Culture University, China


Xiwen Zhang is currently a Professor of Digital Media Department, School of Information Science, in the Beijing Language and Culture University. He worked as an associated professor from 2002 to 2007 at the Human-computer interaction Laboratory, Institute of Software, Chinese Academy of Sciences. From 2005 to 2006 he was a Postdoctor advised by Prof. Michael R. Lyu in the Department of Computer Science and Engineering, the Chinese University of Hong Kong. From February to April in 2001 he was a Research Assistant by Dr. KeZhang Chen in the Department of Mechanical Engineering, the University of Hong Kong. From 2000 to 2002 he was a Postdoctor advised by Prof. Shijie Cai in the Computer Science and Technology Department, Nanjing University.
Prof. Zhang 's research interests include pattern recognition, computer vision, and human-computer interaction, as well as their applications in digital image, digital video, and digital ink. Prof. Zhang has published over 60 refereed journal and conference papers in his research areas. His SCI paper are published in Pattern Recognition, IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics, Computer-Aided Design. He has published more than twenty EI papers.
Prof. Zhang received his B.E. in Chemical equipment and machinery from Fushun Petroleum Institute (became Liaoning Shihua University since 2002) in 1995, and his Ph.D. advised by Prof. ZongYing Ou in Mechanical manufacturing and automation from Dalian University of Technology in 2000.


Title: Intelligently Extracting Information from Digital Ink Chinese Text by Junior International Students ​


Abstract: Chinese characters have complex structures. Their writing plays an import role in learning Chinese. Junior international students can use digital pen to record their handwriting as digital ink. Various information can be extracted from the digital ink text, such as text line, Chinese characters, stroke errors, shape normalization. Digital ink Chinese texts written by junior international students contain many information including errors and unnormal issues. It is difficult to recognize them. We proposed some intelligent methods to extract information, such as adaptive segmentation based on statistics analysis, classification using machine learning, stroke matching using Genetic Algorithm, evaluating the normalization for entire characters and their components using knowledge bases. With developing new intelligent methods and collecting more data, more valued information can be extracted.


Senior Lecturer Dr. Qingqing Xing

The Hong Kong University of Science and Technology (Guangzhou) , China


Dr. Qingqing Xing is a Senior Lecturer at the University of Education Sciences, the Hong Kong University of Science and Technology (Guangzhou). She holds a PhD in Education from Peking University and has more than 23 years of teaching experience in science and technology-oriented universities. She is committed to promoting research ideas and interdisciplinary collaboration, including as a Project Manager in the Bureau of International Cooperation at the National Science Foundation of China and as the Associate Director of the International Office at the Beijing Institute of Technology. These experiences have given her insights into promoting research-oriented education internationally, especially for the world's first interdisciplinary university as HKUST(GZ).
As an education practitioner, Dr. Xing actively explores the pedagogy of Project-Based Learning. In addition to her efforts to teach Interdisciplinary Design Thinking and Effective Academic Communication, she collaborates with interdisciplinary research teams in computational media and arts, metaverse research, and health care. As part of this collaboration, it uses educational technologies and artificial intelligence generated content tools to help students present their research ideas in engaging ways to facilitate their “niche” exploration process, with a focus on developing Self-Organized Maker Education. Within just one year of its inception, HKUST(GZ) research students have actively contributed insights and examples of project-based learning in higher education.


Title: Exploring the Benefits of Project-Based Learning: Insights from an Interdisciplinary University


Abstract: This invited talk is about project-based learning (PBL) at an interdisciplinary university with features of self-organized maker education. The speaker will present how the university differs from other universities in its academic structure and learning and teaching mode. A Design Thinking course will be discussed as an example of how PBL is implemented in the classroom. Exemplary student projects are presented to illustrate this approach. The first project is a virtual bicycle that combines elements of virtual reality and exercise physiology. The second project is an RFID asset management system that streamlines inventory tracking and management. These projects demonstrate how PBL fosters creativity, critical thinking, and collaboration among students.



Assoc. Prof. Vincent CS Lee

Monash University, Australia ( IEEE Senior Member)


Vincent CS Lee is currently an Associate Professor with the Faculty of IT, Monash University and a Senior Member of IEEE. His education qualifications include Bachelor and Master degrees in EEE, both from the National University of Singapore; MBA from Henley Management College in Oxford, England; BBus (Hons 1st class in Economics & Finance) and MBus (Accountancy), both from RMIT University in Melbourne; and PhD degree from University of Newcastle, NSW in Australia. He is an active researcher and educator (with Graduate Certificate in Higher Education Teaching from Monash University) with 30 years as academicians for four universities including Monash University and Swinburne University, both in Melbourne, joint Monash-South East University in Suzhou, Nanyang Technological University in Singapore. He was visiting Professors with School of Economics and Management, and School of Computing and Technology, Tsinghua University in Beijing. Lee’s research and higher education teaching (developed and delivered undergraduate and postgraduate courses) span multi-disciplinary domains across IT, Digital Health, Signal and Information Processing, Financial Engineering (FinTech), Educational Data Mining (with learner-centric education technology tools), Explainable AI, Deep ML, Computer Vision for dynamic objects tracking, and Multi-agent Autonomous Systems. Lee has published 200+ papers in IEEE/ACM SCImago ranked Q1 High Impact factors of Journals, and in CORE A/A* Peer-review International Conferences proceedings (AAAI, IJCAI, ICDM, ICWS, ICDE, PAKDD, CIKM, WWW, IEEE IC Signal Processing, IC-EDM). Lee also served as invited keynote speakers for a number of these IEEE and ACM Flagship conferences’ and General Chair and Co-chair of steering committees and technical programs.


Title: GPT AI for teaching and learning: issues and opportunities


Abstract: The body of education literature asserts that GPT AI, in particular Chat GPT version 3.5 is an effective education tool. It can be used to overcome three barriers to teaching and learning (including blended mode) in the face-to-face classroom: improving transfer, breaking the illusion of explanatory depth, and training learners to critically evaluate explanations. This talk provides background information and techniques on how GPT AI can be used to overcome the three barriers and includes prompts and assignment tasks design that teachers can incorporate into their teaching and evaluation of assignments.




Assoc. Prof. Sherif Welsen

University of Nottingham Ningbo China, China


Dr. Sherif Welsen is an accomplished associate professor in the Department of Electrical and Electronic Engineering at the University of Nottingham Ningbo China (UNNC). Since joining the faculty of science and engineering in November 2013, Dr. Welsen has been dedicated to student success and academic excellence, currently serving as Campus Lead Senior Tutor and Faculty Senior Tutor since 2022 and 2017, respectively.
Dr. Welsen is a distinguished researcher and academic leader, having founded and headed the Science and Engineering research group. He has also led the teaching and learning initiatives within the Faculty of Science and Engineering from 2017 to 2021, during which he served as both the Faculty Deputy Director of Teaching and Learning and the Director of Teaching and Learning. These roles allowed him to make significant contributions to curriculum development, course design, and student engagement.
With a master's degree from the Arab Academy for Science and Technology, Cairo, and a Ph.D. from Ain-Shams University, Dr. Welsen has held various academic and research positions worldwide. He served as a scientist in Shenzhen, China, from 2011 to 2013, an assistant professor in Egypt from 2010 to 2011, and an associate lecturer and researcher from 2004 to 2010. This breadth of experience has given him a global perspective on engineering education and research.
Dr. Welsen's research interests are diverse and innovative, focusing on emerging wireless technologies, coding techniques, location estimation, digital chip design, and future engineering education. He has also explored blended learning, digital reading, and pedagogies for digital transformation, highlighting his forward-thinking approach to teaching and learning.


Title: A View on Digital Reading in International Education: Science and Engineering Students’ Perspective


Abstract: As remote education and e-learning have taken center stage, the role of digital reading in shaping the learning experiences of students has grown substantially. This speech will present a groundbreaking study, building upon previous research to delve into digital reading amidst the pandemic. The study casts its net wide, encompassing science and engineering students from Leeds Joint School and Southwest Jiaotong University (SWJTU) in China. Specifically, the research explores the reading habits of undergraduate students hailing from diverse engineering disciplines such as Civil Engineering, Electronic and Electrical Engineering, Mechanical Engineering, and Computer Science. The findings of this study reveal a fascinating transformation in the reading strategy of engineering students. It becomes evident that their approach to reading has undergone a profound shift towards an "e-centric" paradigm. This evolution stands in stark contrast to previously published studies, which often examined reading practices either during or post-pandemic times. The speech, will shed light on these transformative findings, providing valuable insights for policymakers and education authorities, particularly in the context of engineering higher education




Reader Dr. Neil Gordon
University of Hull, UK

Neil Gordon is a Reader  in Computer Science at the University of Hull in England. Neil is a National Teaching Fellow, and a Principal Fellow of the UK Higher Education Academy. He has produced a number of reports for AdvanceHE, with major ones on the way that technology enhanced learning can enable flexible pedagogy, on the role of assessment in education, and on ways to address issues in retention and attainment in computing education. His awards include University Teaching Fellowships and awards for scholarship in teaching and learning. His research interests include applications of computer science to enable true technology enhanced learning, issues around sustainable development, as well as more discipline specific work on applications of computer algebra and formal methods. He has published over 50 journal articles, a similar number of refereed conference proceedings, along with a variety of book chapters, reports and other publications.



Assoc. Prof. Yang Chen

Harbin Institute of Technology (Shenzhen), China

Yang Chen is currently an associate professor in the college of humanity and social sciences of Harbin Institute of Technology (Shenzhen), China. She received her bachelor’s degree in mass communication from Communication University of China, master’s degree in digital media from Harbin Institute of Technology, China, and doctoral degree in computer graphics technology with a concentration in human-computer interaction from Purdue University, USA. Her research interests include social media, user experience, environmental communication, and educational gamification. As principal investigator, she has undertaken funded research projects on gamified pro-environmental communication, gamification in second language acquisition, and big data and education resources, which were funded by national/provincial social science foundations. She has publications in international journals including International Journal of Human-Computer Interaction, sustainability, and International Journal of Language, Literature and Linguistics. She also published in international conferences such as ICBDE, ICESS, ICIET, WCEEE, and ELEARN. In addition, she serves as a reviewer for several prestigious international journals (such as Information, Communication & Society, Information Processing and Management, Social Media and Society, Behaviour & information Technology, and Interacting with Computers) and international conferences in the fields of social media, technology, and education.


Title: Understanding Chinese EFL Learners’ Acceptance of Gamified Vocabulary Learning Apps


Abstract: Implementing the idea of gamification in mobile-assisted language learning has recently been gaining increasing attention from academia and industry. I will introduce three studies about this topic. The first one is about investigating students’ perception, motivation to use, and acceptance of popular gamified English vocabulary learning apps. The second is a longitudinal study on students’ foreign language anxiety and cognitive load in gamified classes of higher education. The third is understanding Chinese EFL learners’ acceptance of gamified vocabulary learning Apps: An integration of self-determination theory and technology acceptance model.





Assoc. Prof. Wei-Hua Hu
Harbin Institute of Technology (Shenzhen), China

Weihua Hu is currently an associate professor of Civil Engineering in the Harbin Institute of Technology (Shenzhen). Dr. Hu obtained his PhD degree from the University of Porto in Portugal in 2011, and he continued his postdoc research work in the Federal Institute for Material Research and Testing (Bundesanstalt für Materialforschung und -prüfung,BAM) in Berlin, Germany. Since 2016, he started his education and research work in Harbin Institute of Technology (Shenzhen). He is dedicated to specialized basic courses in high-rise buildings and seismic resistance, earthquake engineering and structural seismic design and experimental modal analysis.
In recent years, he has mainly focused on the innovation of traditional civil engineering education by integrating the remote monitoring technology based on Internet of Things (IOT) with lecture-based teaching method. Under his guidance, students won the bronze prize in the 7th China International "Internet plus" Undergraduate Innovation and Entrepreneurship Competition for their intelligent building technology. In the past years, he was awarded with Teaching Achievement Prize (2020) in the Harbin Institute of Technology (Shenzhen) and Teaching Competition for Young Teachers (2018) in the Harbin Institute of Technology.



Assoc. Prof. Zhi Liu

Central China Normal University, China

Zhi Liu is the PI of affective computing research group, associate researcher and doctoral supervisor at the National Engineering Research Center for Big Data in Education, Central China Normal University. He was a guest researcher at the Institute of Computer Science of Humboldt University of Berlin from 2017 to 2018.
He is the guest associate editor of the international journal “Frontiers in Artificial Intelligence”, the editorial board member of “Frontiers in Psychology”, and the chair of the special Conference on Learning Analytics of the Learning Science Research Branch of the Chinese Association of Higher Education. At the International EITT, AMMCS, GCCCE and other well-known international conferences, he works as committee members. He has been engaged in the research and development of education data mining, learning analysis, intelligent tutoring systems, etc.
In the top journals such as Knowledge-Based Systems, Computers & Education, IEEE Transactions on Learning Technologies, Journal of Educational Computing Research and other leading journals in the interdisciplinary field of computer and educational technology, he have published more than 40 full papers. He won the 11th Annual Research Excellence Award in the education filed of IGI Global Publishing house in 2019.


Title: Modeling, computing and adaptation of group discussion learning processes

Abstract: As an important learning paradigm in large-scale online scenarios, group learning discussion plays an important role in promoting learning motivation and effectiveness. However, the behavior-emotion-cognitive dynamic correlation and its internal mechanism remain unclear. Centering on relevant theories and methods of group learning, the research carries out the data-driven relational modeling of discussion learning behaviors, calculation of learning subjects and adaptation of group learning process, builds a closed-loop research framework of theory, technology and application demonstration, and forms an intelligent learning technology system with "modeling, calculation and adaptation" as the core. It provides theoretical and technical support for revealing the interaction law of behavior, emotion and cognition in discussion learning, and promoting higher-order cognition and knowledge construction.