invited speakers / 特邀报告专家

 

British Educational Research Association (BERA) Invited Speakers

Onsite Speaker (Digital Education group convenor for the British Educational Research Association (BERA)

Dr. Nashwa Ismail
Fellow of Advance HE and Digital Education group convenor for the British Educational Research Association (BERA)
University of Liverpool, UK

Biography: Dr. Nashwa holds an MSc and PhD from the University of Southampton. She is a Fellow of Advance HE and Digital Education group convenor for the British Educational Research Association (BERA). Currently, she is a lecturer in Digital Education and Innovation at the University of Liverpool, UK. Her expertise lies in Technology-Enhanced Learning (TEL), with a particular focus on Artificial Intelligence (AI) and Games-Based Learning (GBL). Dr. Nashwa has extensive international experience, including work in the Global South, to equip academics with the skills and knowledge required to integrate technology including AI into teaching and research effectively.

 

Online speakers (Digital Education group convenors for the British Educational Research Association (BERA)

 

Dr. Koula Charitonos
Open University, UK

Biography: Dr Koula Charitonos is a Senior Lecturer at the Institute of Educational Technology in the Open University. Her research is integrative and spans three areas: 1. Professional learning for complex professional knowledge work; 2. Pedagogies and educational practices for connected learning across formal and informal settings and 3. Participatory approaches to research with educational technology.

 

Dr. Felix Kwihangana
Kings College London, UK

Biography: Dr Felix is a Senior Lecturer in Transnational Education at Kings College London. His research and teaching focus on the educational use of digital technologies, especially teacher education and digital technologies in under-resourced contexts. He is also co-leading the Digital Inequalities strand of the Digital Technology, Communication & Education research group (DTCE RSG) at Manchester.

 

Jennifer Crowdy
PhD Convenor for the British Educational Research Association (BERA)’s Digital Education Special Interest Group, Peter Gosden Fellow for the History of Education Society
University of Winchester, UK

Biography: Mrs Jennifer Crowdy is a final year PhD student and Senior Digital Ambassador at the Faculty of Education and the Arts, University of Winchester. Her research is on ‘rethinking the concept of creativity in technology education through ‘philosophies of the encounter’’. Alongside her studies, from 2022-2024 Jennifer created and co-led the Winchester Digital Academy Pilot Programme, where students from all backgrounds and modes of study learnt and harnessed the latest trends and development in digital education and AI. She is also a former successful content creator, who created live educational and edutainment content on the broadcasting platform Twitch. Jennifer is the PhD Convenor for the British Educational Research Association (BERA)’s Digital Education Special Interest Group, and is currently the Peter Gosden Fellow for the History of Education Society. She also currently works as a Personal Assistant for the University of Winchester’s Dean of Health & Wellbeing. Jennifer has worked in state education since 2011, with a wealth of experience teaching all phases of educational life with a technology specialism.

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Prof. Xiangjie Kong
Vice Dean in the College of Computer Science & Technology, Distinguished Member of CCF
Zhejiang University of Technology, China

Speech Title: Knowledge and Data Driven Computational Social Science: From Academic Networks to Urban Networks

Abstract: The rapid development of technologies such as online social networks, intelligent monitoring, automatic data collection, intelligent sensing, and high-performance computing in recent years has contributed to the explosive growth of big data. The accessibility of various types of human-related data has significantly influenced the research topics and methods that researchers focus on. These data allow for traditional social issues to be studied from new perspectives and enable the discovery of more social phenomena. Simultaneously, the availability of data has led to the emergence of new research topics or methods. As a result, exploring research topics in the field of computational social science, which centers on knowledge and data, has garnered increasing attention. Traditional methods for retrieving empirical data to analyze issues in the social sciences often rely on manual processes, such as human resource surveys, which are not only resource-intensive but also prone to significant inaccuracies due to human error or inherent limitations. Data-driven computational social science uses mathematical theories and data processing and analysis techniques from computer science to address these social issues. This approach has attracted widespread attention and recognition from research institutions and scholars in disciplines such as computer science, network science, data science, management science, social science, behavioral science, and physics. This report will introduce some relevant research efforts in computational social science based on academic big data and urban big data, taking the fields of academic collaboration and smart cities as examples.

Biography: Xiangjie Kong is currently a Full Professor and Vice Dean in the College of Computer Science & Technology, Zhejiang University of Technology (ZJUT), China. Previously, he was an Associate Professor in School of Software, Dalian University of Technology (DUT), China, where he was the Head of the Department of Cyber Engineering. He is the Founding Director of City Science of Social Computing Lab (The CSSC Lab) (http://cssclab.cn/). He is/was on the Editorial Boards of 6 International journals. He has served as the General Chair or Program Chair of more than 10 conferences. Dr. Kong has authored/co-authored over 200 scientific papers in international journals and conferences including IEEE TKDE, IJCAI, ACL, IEEE TMC, ACM CSUR, ACM TKDD, IEEE TNSE, IEEE TII, IEEE TITS, IEEE NETW, IEEE COMMUN MAG, IEEE TVT, IEEE IOJ, IEEE TSMC, IEEE TETC, IEEE TASE, IEEE TCSS, ACM TSON, ACM TSAS, WWWJ, etc.. 5 of his papers is selected as ESI- Hot Paper (Top 1‰), and 20 papers are ESI-Highly Cited Papers (Top 1%). His research has been reported by Nature Index and other medias. He has been invited as Reviewers for numerous prestigious journals including IEEE TKDE, IEEE TMC, IEEE TNNLS, IEEE TNSE, IEEE TII, IEEE IOTJ, IEEE COMMUN MAG, IEEE NETW, IEEE TITS, TCJ, JASIST, etc.. Dr. Kong has authored/co-authored three books (in Chinese). He has contributed to the development of 14 copyrighted software systems and 30 filed patents. He has an h-index of 53 and i10-index of 131, and a total of more than 9700 citations to his work according to Google Scholar. He is named in the 2019 - 2024 world's top 2% of Scientists List published by Stanford University. He is named in the 2022-2024 Best Computer Science Scientists List published by Research.com. Dr. Kong received IEEE Vehicular Technology Society 2020 Best Land Transportation Paper Award, IEEE CSCWD 2024 Best Paper Award, and The Natural Science Fund of Zhejiang Province for Distinguished Young Scholars. He has been invited as Keynote Speaker at more thant 10 international conferences, and delivered a number of Invited Talks at international conferences and many universities worldwide. His research interests include big data, network science, and computational social science. He is a Distinguished Member of CCF, a Senior Member of IEEE, a Full Member of Sigma Xi, and a Member of ACM.

 

Prof. Zhiquan Liu
Jinan University, China

Speech Title: Security Trust and Privacy in Vehicular Networks

Abstract: Vehicular networks, as an important application of Internet of things in the automotive industry, and as the core component of intelligent transportation system, can realize all-round network connection and efficient information interaction between vehicles and other nearby vehicles, road infrastructures, pedestrians, and network, etc., so as to provide various information services, improve driving safety and efficiency, and promote energy saving and emission reduction. Vehicular networks are regarded as a global innovation hotspot and an important commanding point of economic development, with huge industrial development potential and application market space. However, due to the large, open, highly dynamic, delay sensitive, and other characteristics, the security, trust, and privacy in vehicular networks face huge challenges. Thus, this talk will focus on highlighting the recent advances, challenges, and approaches for the security, trust, and privacy in vehicular networks.

Biography: Zhiquan Liu is a full professor with the College of Cyber Security, Jinan University. In recent years, Prof. Liu has published more than 100 SCI/EI-indexed papers on authoritative journals and conferences (including more than 50 papers on CCF-A/JCR-1/TOP journals, 4 best papers on international conferences, 2 most popular papers on international journals, 1 ESI hot paper, and 4 ESI highly cited paper), and has applied for/been authorized more than 100 invention patents and PCT patents. Besides, Prof. Liu has served as the Chair, Co-Chair, Program Committee Chair, Publication Chair, Publicity Chair, Finance Chair, Workshop Chair, or Program Committee Member for more than 20 international conferences. Meanwhile, Prof. Liu has served as the editor-in-chief of Advances in Transportation and Logistics, and has served as the area editor, associate editor, or academic editor for more than 10 SCI-indexed journals. His homepage is https://www.zqliu.com.

 

Prof. Xiwen Zhang
Beijing Language and Culture University, China

Speech Title: Intelligently Recognizing 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 is a new media compared with digital image and digital video. It is captured from handwriting and freehand drawing using digital pen. Point samples are captured by digital pens, containing positions, time stamp, and pressures. A stroke is a list of sampling points from pen down and movement to pen up. A list of strokes consists of a digital ink. Digital ink Chinese text are stroke sets, have neither text line, nor Chinese characters.
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 and deep 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.

Biography: XiWen Zhang is currently a full professor of Digital Media Department, School of Information Science, Beijing Language and Culture University.
Prof. Zhang 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 Post doctor advised by Prof. Michael R. Lyu in the Department of Computer Science and Engineering, the Chinese University of Hong Kong. From 2000 to 2002 he was a Post doctor 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, video, and ink. Prof. Zhang has published over 60 refereed journal and conference papers. His SCI papers are published in Pattern Recognition, IEEE Transactions on Systems Man and Cybernetics B, 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.

 

Assoc. Prof. A.Y.M. Atiquil Islam
Founder and Lead Editor of the book series Assessment of Educational Technology (AET) with Routledge Taylor & Francis Group
East China Normal University, China

Biography: Assoc. Prof. A.Y.M. Atiquil Islam serves as the Director of the International Graduate Program in Educational Technology at East China Normal University. He is also a Guest Professor at the School of Teacher Education, Jiangsu University, and an Honorary Chair Professor at Shanghai Jian Qiao University. Dr. Islam earned a multidisciplinary PhD by integrating two faculties—Education and Computer Science & Information Technology—at the University of Malaya. With nearly 21 years of experience across academia, industry, and business, he has made significant contributions to his field. Notably, he developed and validated three influential models: the Technology Adoption and Gratification (TAG) Model, the Technology Satisfaction Model, and the Online Database Adoption and Satisfaction (ODAS) Model. An accomplished author, Dr. Islam has published nearly 100 papers in leading international journals and conferences. In the last two years, he authored two books published by the Taylor & Francis Group: The Technology Adoption and Gratification (TAG) Model and Its Application and Applying the Rasch Model and Structural Equation Modeling to Higher Education. In addition to his academic roles, Dr. Islam is an Editorial Board Member of the British Journal of Educational Technology, Executive Editor of the International Journal of Smart Technology and Learning, and Editor of Cogent Education. Dr. Islam is particularly enthusiastic about leveraging his expertise in areas such as Artificial Intelligence in education, STEM education, and the Metaverse to inspire students, enhance teaching and learning experiences, and drive cutting-edge research initiatives.

 

Assoc. Prof. Zhi Liu
Central China Normal University, China

Speech Title: Knowledge and Emotional Scaffolding-based Intelligent Tutoring

Biography: Zhi Liu is a senior fellow researcher and PhD supervisor at the National Engineering Research Center of Education Big Data, Faculty of Artificial Intelligence in Education, Central China Normal University. He also holds a position as a guest researcher at the Computer Science Institute, Humboldt University of Berlin. With deep expertise in educational data mining, learning analytics, and intelligent tutoring systems, Liu has published over 50 SCI/SSCI indexed papers in top journals, including Knowledge-Based Systems, Computers & Education, Internet and Higher Education, and IEEE Transactions on Learning Technologies. In addition, he serves as a key member of the national expert database for graduate education evaluation, a peer review expert for the National Natural Science Foundation of China, and the principal investigator of National Natural Science Foundation and the National Key R&D Program of China (2030 Major Projects). Liu is actively involved in international academic communities, serving in various leadership roles including as the chair of the organizing committee for the ICET. He is a guest associate editor for the international journal Frontiers in Artificial Intelligence and sits on the editorial boards of Discover Education and Frontiers in Psychology, and holds the Lifetime Member status of the Chinese Association of Automation. His contributions have been widely recognized, earning him numerous awards including the First Prize of the Science and Technology Progress Award of Hubei Province in 2024, First Prize of the Teaching Achievement Award of Higher Education Institutions in Hubei Province in 2022, and the honor of being a Top 1% Highly Cited Scholar in China National Knowledge Infrastructure (CNKI) for 2024.

 

Dr. Alexandre St-Vincent Villeneuve
McGill-UQAM Université du Québec à Montréal, Canada

Speech Title: GenAI in special education: Exploring leadership paradigms and practical insights

Abstract: The speech examines the transformative potential of Generative Artificial Intelligence (GenAI) in special education, positioning leadership as a foundational element for innovative management frameworks. By integrating insights from educational methodologies, organizational leadership, and GenAI tools, it investigates a spectrum of leadership paradigms to address the multifaceted challenges of special education. Among these, caring leadership is presented as an emerging construct, informed by the most recent advancements in leadership scholarship, underscoring empathy and strategic foresight as critical enablers of collaboration and educator empowerment. The discussion is anchored in a practical case study, showcasing measurable outcomes one year post-implementation and illustrating the tangible impact of these approaches.

Biography: Dr. Alexandre St-Vincent Villeneuve is an academic researcher and multi-entrepreneur, recognized for his transformative work at the intersection of neuropsychology and artificial intelligence. His research drives innovation in special education, where advanced tools support neurodiverse learners and in cancer detection, where AI enhances diagnostic precision. He also explores algorithmic video surveillance to improve security in schools and other facilities. As a leader with extensive experience across entrepreneurship, education, healthcare and management, he excels at translating complex research into practical solutions with real-world impact. His ventures combine technological innovation with a commitment to improving outcomes for vulnerable populations. He has shared his advancements at international conferences in Asia, Europe and the United States, contributing to global efforts in leveraging AI for societal progress.