Invited Speakers

Rubing received his M.Eng and Ph.D. degree in Computer Science and Technology from Huazhong University of Science and Technology. After that, Rubing spent one year at Monash University as an academic visitor advised by Dr. Xin Xia and Dr. Robert G. Merkel and three months at Swinburne University of Technology as an academic visitor advised by Prof. T. Y. Chen. Currently, he is an associate professor in the School of Computer Science and Engineering, Faculty of Innovation Engineering, Macau University of Science and Technology (MUST). Before joining MUST, he was a faculty member at Jiangsu University, China.
He has more than 80 publications in journals and proceedings, including IEEE Transactions on Software Engineering (IEEE TSE), IEEE Transactions on Reliability (IEEE TRel), Journal of Systems and Software (JSS), Information and Software Technology (IST), Software: Practice and Experience (SPE), Science of Computer Programming (SCP), IET Software, International Journal of Software Engineering and Knowledge Engineering (IJSEKE), IEEE Transactions on Emerging Topics in Computational Intelligence (IEEE TETCI), Expert Systems with Applications (ESWA), The Computer Journal, Tsinghua Science and Technology (TST), ICSE, ISSRE, ICST, and COMPSAC. He has served as the program committee member of ICST2020 (poster track), APSEC2023-2024, and AI Testing 2019-2021. He has served as the reviewer for many journals such as IEEE TSE, ACM TOSEM, IEEE TC, IEEE TIFS, IEEE TAI, IEEE TBD, ACM TWEB, IEEE TRel, IEEE TFS, IEEE TNSE, IEEE T-ASE, IEEE TCAD, ACM CSUR, STVR, JSS, IST, SPE, JSEP, ASEJ, SCP, EAAI, FCS, IEEE Software, etc. He is a senior member of the IEEE and the China Computer Federation.
His current research interests include: 1) AI for Software Engineering (AI4SE), i.e., adopting AI knowledge and techniques such as Machine Learning (ML), Deep Learning (DL), and Large Language Model (LLM), to support the development of software engineering (including software requirements, testing, debugging, and maintenance); 2) Software Engineering for AI (SE4AI), i.e., applying the principles of software engineering to AI systems (such as AI systems testing, debugging, and maintenance); 3) Failure-Based Testing (FBT), i.e., taking advantage of the knowledge of software failures to support the testing process; and 4) Testing of Complex Software Systems such as IoT systems, intelligent systems, and autonomous driving systems.

Assoc. Prof. Jining Han

Southwest University, China

Dr. Song Yanjie (PhD HKU; MEd Leeds, UK) is an Associate Professor in the Department of Mathematics and Information Technology and Associate Director of Centre for Immersive Learning and Metaverse in Education (CILME). Her research interests include augmented reality (AR), virtual reality (VR), artificial intelligence (AI) and metaverse in education, multimodal learning analytics (MMLA), and innovative pedagogy designs. She was successful in leading her team to develop a few award-winning apps and a metaverse platform “Learningverse”.

Title: Leveraging AI and 3D Metaverse – “Learningverse” to Scaffold Students in Immersive and Collaborative Learning

Abstract: Generative artificial intelligence (AI) has been adopted in various fields. However, few studies have integrated generative AI into the metaverse environments to enhance students’ learning. In this talk, I will share my experiences in how to leverage generative AI in the 3D metaverse platform “Learningverse" to scaffold students for immersive and collaborative learning. Advantages and pitfalls are explored.