Panel-R | Research in the Age of LLMs
— How will LLMs change the way knowledge is discovered?
(Part of FFRise Forum)
From data-intensive science and the “Fourth Paradigm” to AI-assisted reasoning and autonomous scientific discovery, Panel-R explores how LLMs may transform the research process itself: asking questions, forming hypotheses, connecting knowledge across disciplines, designing experiments, and accelerating discovery.
Background: 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 discovery of new laws or new knowledge governing both the physical and virtual worlds, GenAI is creating new opportunities across various research fields.
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, academic leaders, and practitioners.
Goal: This panel aims to bring together invited experts to share their perspectives on the opportunities, challenges, and future directions of GenAI-empowered research. The discussion will focus on how GenAI can be responsibly and effectively used to support cross-disciplinary research, scientific discovery, and international collaboration.
Format: The panel will be organized as an interactive discussion session. The panelists will first provide short position statements, followed by a moderated discussion and audience Q&A.
Panel Chairs
A/Prof. Chao Chen
RMIT University, Australia
Biography: Dr Chao Chen is currently an Associate Professor in AI and Data Analytics at RMIT University and Director of the RMIT Enterprise AI and Data Analytics Hub, where he leads applied AI research and industry collaboration to support the trusted adoption of AI. He received his PhD degree in Information Technology from Deakin University in 2017 and worked as a Data Scientist at Telstra from 2016 to 2018, before holding academic positions at Swinburne University of Technology and James Cook University. His research bridges cybersecurity and AI, spanning AI for cybersecurity and the security, privacy, and trustworthiness of AI systems — foundations for the responsible use of AI and GenAI in business and research. Through the Hub, he works with industry and government partners including Microsoft, CSIRO, BaptistCare, and Wyndham City Council to translate research into practice, from industry-funded PhD programs to GenAI workshops delivered as part of Australia’s National AI Month and AI-for-business programs for local communities. He has also contributed to national AI policy, including submissions to the Senate Select Committee on Adopting Artificial Intelligence and the Department of Industry, Science and Resources’ consultation on safe and responsible AI. He has published more than 80 research papers in high-quality journals and CORE rank A*/A conferences, such as AAAI, IJCAI, KDD, RAID, and ESORICS.
A/Prof. Xingliang Yuan
The University of Melbourne, Australia
Biography: Dr Xingliang Yuan is currently an Associate Professor in the School of Computing and Information Systems at The University of Melbourne and an Australian Research Council (ARC) Future Fellow. He received his PhD degree from City University of Hong Kong in 2016 and held a faculty position at Monash University from 2017 to 2024 before joining the University of Melbourne. His research focuses on data security and privacy, including secure networked systems, encrypted data processing, trustworthy machine learning, and the security of modern AI deployment. His work has been published in top-tier security and systems venues such as ACM CCS, IEEE S&P, USENIX Security, NDSS, IEEE TDSC, and IEEE TIFS, and has been recognised with the Best Paper Award at ESORICS 2021 and an Honourable Mention Award at USENIX Security 2025. His research has been supported by the ARC, CSIRO, the Australian Department of Home Affairs, and the Australian Department of Health and Aged Care. He serves on the editorial boards of IEEE Transactions on Dependable and Secure Computing (TDSC) and IEEE Transactions on Services Computing (TSC), and has served as General Co-Chair of RAID 2025 and General Chair of IEEE ICDCS 2027. He is a Senior Member of the IEEE.
Panelists
Prof. Xiaokang Wang
Zhengzhou University, China
Biography: Xiaokang Wang is a professor with School of Computer Science and Artificial Intelligence, Zhengzhou University, China. He got his Ph. D degree in Computer Architecture from Huazhong University of Science and Technology, China, in 2017. His research interests include Cyber-Physical-Social Intelligence, Parallel and Distributed Computing, and Tensor Decomposition. He authored more than 70 papers published in many high-quality journals including IEEE TC, IEEE TNNLS, IEEE TII. He serves as the Program Chair or Executive Chair of the 2026 IEEE HPCC, 2025 IEEE UIC, 2024 IEEE ISPA, 2023 IEEE ICPADS. He is the recipient of 2017 IEEE TCSC Outstanding Ph. D Dissertation Award, 2019 IEEE SCSTC Raising Star Award, 2021 IEEE TCSC Early Career Award and 2023 IEEE HITC Early Career Award. He is the winner of the Best Paper Award of 2021 IEEE Transactions on Sustainable Computing. He has been ranked in the Elsevier and Stanford University’s top 2% of Scientists list from 2021 to 2025.
Coordinators
Dr. Wanlun Ma, Swinburne University of Technology, Australia
Dr. Lifei Wang, Hosei University, Japan
Email: ffrise.forum@gmail.com
← Back to FFRise Forum