The Panel on
Generative AI (GenAI) in Research and Education: Opportunities, Challenges, and Future Directions
Date and Time: TBA
Generative AI (GenAI) — including large language models, image-generation models, and other multimodal systems — is rapidly transforming the ways in which researchers, educators, students, and institutions conduct academic work. From literature review, scientific writing, coding, data analysis, and research collaboration to personalised learning, assessment design, and curriculum innovation, GenAI is creating new opportunities across both research and education.
At the same time, the adoption of GenAI also raises important challenges, including reliability, academic integrity, responsible use, privacy, intellectual property, fairness, and governance. These issues require interdisciplinary discussion among researchers, educators, academic leaders, and practitioners.
This panel aims to bring together invited experts to share their perspectives on the opportunities, challenges, and future directions of GenAI-empowered research and education. The discussion will focus on how GenAI can be responsibly and effectively used to support academic innovation, research productivity, teaching practice, and international collaboration.
Topics of Interest
The panel will cover, but is not limited to, the following topics:
- GenAI for research productivity and academic collaboration
- GenAI-assisted scientific writing, coding, and data analysis
- GenAI in teaching, learning, assessment, and curriculum design
- Academic integrity and responsible use of GenAI
- Privacy, security, copyright, and ethical considerations
- Institutional policies and governance for GenAI adoption
- Future directions of AI-empowered research and education
The panel will be organised as an interactive discussion session. Invited panelists will first provide short position statements, followed by a moderated discussion and audience Q&A.
Format: Invited panel discussion
Duration: 60-90 minutes
Panel Chairs:
Prof. Yang Xiang, Swinburne University of Technology, Australia
A/Prof. Chao Chen, RMIT University, Australia
Panel Speakers: TBA
Panel Coordinator:
Dr. Wanlun Ma, Swinburne University of Technology, Australia
Venue: RMIT, Melbourne, Australia
Panel Chairs
Prof. Yang Xiang
Swinburne University of Technology, Australia
Biography: Professor Yang Xiang is a Full Professor and Director of the Digital Capability Research Platform at Swinburne University of Technology, Australia, and a Fellow of the IEEE. His research spans cybersecurity and artificial intelligence, with particular expertise in software security, network systems, and the privacy and robustness of algorithms. Over more than two decades he has authored over 300 peer-reviewed publications in premier venues including ACM CCS, IEEE S&P, and USENIX Security.
He serves as Editor-in-Chief of SpringerBriefs in Information Security and Cryptography and as Associate Editor of ACM Computing Surveys, and has previously served as Associate Editor for several IEEE Transactions focused on dependable computing and distributed systems. He is a current member of the Australian Research Council's College of Experts. Through the Digital Capability Research Platform he established, his work emphasises translating academic research into practical applications across the manufacturing, healthcare, energy, finance, and transportation sectors.
A/Prof. Chao Chen
RMIT University, Australia
Biography: Dr Chao Chen is currently an Associate Professor in AI and Data Analytics at RMIT University. He received his PhD degree in Information Technology from Deakin University in 2017. From 2016 to 2018, he worked as a Data Scientist at Telstra to create customer value from huge and heterogeneous data sources using advanced analytics and big data techniques. He then worked as a Research Fellow and a Senior Lecturer at Swinburne University of Technology and James Cook University, respectively.
He is conducting interdisciplinary research between cybersecurity and artificial intelligence (AI), such as AI for cybersecurity and security issues in AI systems. He has published more than 60 research papers in high quality journals and CORE rank A*/A conferences, such as AAAI, IJCAI, RAID, and ESORICS. One of his papers was the featured article of that issue (IT Professional, Mar.-Apr. 2016). His work has been cited more than 3000 times with an h-index of 29 on Google Scholar, and he has secured more than $4M in research funding to support his research.
Panel Speakers
TBA