PNC 2025 Annual Conference and Joint Meetings
Mind Meets Machine:
Rethinking Intelligence and Knowledge in the Age of AI
September 20-22, 2025 @ Vietnam Academy of Social Sciences, Hanoi, Vietnam
PNC 2025 Annual Conference and Joint Meetings
Mind Meets Machine:
Rethinking Intelligence and Knowledge in the Age of AI
September 20-22, 2025 @ Vietnam Academy of Social Sciences, Hanoi, Vietnam
Keynote Speakers
Dr. Huu Hanh Hoang (HOÀNG HỮU HẠNH)
-Deputy Director General, Ministry of Science and Technology, Department of International Cooperation, Vietnam
-Associate Professor, Department of Information Technology, Posts and Telecommunications Institute of Technology, Hanoi, Vietnam
Education
2007 Dr. techn., Information Technology (Information Systems), Vienna University of Technology, Austria
2001 M.S., Information Technology, Hanoi University of Technology, Vietnam
1996 B.S., Mathematics – Informatics, Hue University, Vietnam
Career
2018.10 ~ present Associate Professor, Department of Information Technology (Information Systems), Posts and Telecommunications Institute of
Technology, Hanoi, Vietnam
1996 ~ 2018.09 Lecturer, Hue University, Vietnam
2019 ~ 2024 Member of PTIT Council of Professor Titles, Posts and Telecommunications Institute of Technology, Hanoi, Vietnam
2013 ~ 2018 Member of Hue University Council of Professor Titles, Hue University, Vietnam
Vietnam's Journey in Digital Transformation and AI Mastery:
National Strategy meets Machine Intelligence to Shape Future Knowledge
[Abstract]
Amidst globalization, Vietnam is vigorously advancing a national development strategy centered on Science & Technology, Innovation, and Digital Transformation, with Artificial Intelligence (AI) as its core technology. This presentation will analyze this approach, shaped by breakthrough policies like Resolution 57-NQ/TW, and connect it directly to the PNC 2025 conference theme, “Mind Meets Machine.”
Here, "Mind" represents Vietnam's strategic vision and political will, while "Machine" embodies the power of AI. The talk will elaborate on how Vietnam is leveraging this synergy to "rethink intelligence and knowledge," viewing AI as a partner that augments human capabilities rather than merely an automation tool.
Through exemplary case studies in healthcare, education, and agriculture, the keynote will address how AI is being applied to solve practical challenges. Despite facing difficulties regarding human resources and data, Vietnam remains strongly committed to this journey and seeks international cooperation, affirming its proactive efforts to shape its future in the digital age.
Dr. The Anh Han
-Director, Center for Digital Innovation, School of Computing, Engineering and Digital Technologies, Teesside University, the United Kingdom
-Full Professor, Department of Computer Science, Teesside University, the United Kingdom
Biography
The Anh Han is a Full Professor of Computer Science and Director of the Center for Digital Innovation at School of Computing, Engineering and Digital Technologies, Teesside University. He received his BSc in Computer Science at St. Petersburg State University in 2007, MSc in Computational Logic from the Technical University of Dresden in 2009, and PhD in Artificial Intelligence from the New University of Lisbon in 2012. Following his PhD, he was a FWO Postdoctoral Fellow at the Free University of Brussels (VUB) from 2012 to 2014.
His current research spreads several topics in Artificial Intelligence (AI) and interdisciplinary research, including the dynamics of human cooperation, evolutionary game theory, complex systems, agent-based simulations, and AI governance modelling. He has published over 150 peer-reviewed articles in top-tier computer science conferences and high-ranking scientific journals. He is the co-Editor-in-Chief of the Computers in Industry journal and serves on the Editorial Boards of several international journals, including Journal of the Royal Society Interface, Adaptive Behavior, Plos One, and Humanities and Social Sciences Communication. He regularly serves in the programme committees of most of top-tier AI conferences (e.g., IJCAI, AAAI, AAMAS). Currently, he is the lead editor of a Theme Issue titled “The evolution of sociality in hybrid human-AI populations” for the Philosophical Transactions of the Royal Society A. He has received prestigious research fellowships and grants as Principal Investigator from organisations such as the Future of Life Institute, the UK Engineering and Physical Sciences Research Council, the Leverhulme Trust Foundation, and FWO Belgium.
From Human Cooperation to AI Existential Risks:
Unveiling Emergent Collective Behaviours through Game Theoretical Analysis
[Abstract]
The mechanisms of emergence and evolution of collective behaviours in evolving systems of multiple interacting agents, be they robots, humans, or even human teams, have been undergoing mathematical study via evolutionary and behavioural modelling methods. Their systematic study also resorts to agent-based modelling and simulation techniques, thus enabling the study of aforesaid mechanisms under a variety of conditions, parameters, and alternative virtual games. Numerous important questions faced by several disciplines have been addressed, e.g. what are the mechanisms underlying the evolution of cooperative behaviour at various levels of organisation (from genes to human society)? How to mitigate existential risks such as those posed by climate change or advanced Artificial Intelligence? In this talk, I will discuss these collective behaviour research issues, including results and prospects, which are accruing in importance for the modelling of minds with machines and the engineering of prosocial behaviours in both real-world and artificial life systems.
Dr. Richard Tzong-Han Tsai
-Research Fellow, Research Center for Humanities and Social Sciences, Academia Sinica, Taiwan
-President, Taiwanese Association for Digital Humanities, Taiwan
Biography
Dr. Richard Tzong-Han Tsai is a distinguished researcher and professor at the forefront of Taiwan's artificial intelligence development, specializing in the interdisciplinary integration of Natural Language Processing (NLP), computer science, and the humanities. His career is a testament to the power of bridging disciplines to create high-impact, culturally-aware technology.
As the Co-Principal Investigator and former Convener of the Model Training Group for the TAIDE (Trustworthy AI Dialogue Engine) project, supported by the National Science and Technology Council, Dr. Tsai is a key architect behind Taiwan's first national-level large language model. This landmark initiative focuses not only on achieving state-of-the-art performance but also on deeply embedding the linguistic nuances and cultural context of Traditional Chinese. His pioneering contributions in this area include building the first corpora of Taiwanese Hokkien and Mandarin-Taiwanese code-mixing for Large Language Model (LLM) training, with his foundational research published in top-tier international conferences such as ACL, EMNLP, and COLING.
His dedication to interdisciplinary research extends to his significant achievements in Digital Humanities. He employs advanced computational methods to analyze classical historical texts, such as the Ming Shilu (the Annals of the Ming Dynasty), to uncover novel historical insights. This important work has been recognized and published in premier international venues, including the Digital Scholarship in the Humanities journal and the EMNLP conference.
Under his leadership, his research team has earned a formidable reputation in the international AI community, achieving top rankings in numerous global competitions. This includes multiple first-place victories in the BioASQ Challenge (2020-2023) and a championship in the NIH-led BioCreative Challenge (2021). These exceptional achievements have earned him multiple Google Research Awards (2023, 2024), underscoring the global significance and innovative value of his work.
As a passionate advocate for public science education, Dr. Tsai is dedicated to making AI knowledge accessible to a broader audience. He is the author of the best-selling books, An AI Course for Middle School Students and An AI Course for Elementary School Students. Among them, An AI Course for Middle School Students received numerous accolades, including the Special Recommendation Award for Youth from the 12th Wu Ta-You Popular Science Book Award. His societal impact was further recognized when he was named one of the "Taiwan AI 20" by CommonWealth Magazine, a list celebrating the key figures shaping Taiwan's AI future.
In academia, Dr. Tsai serves as a Research Fellow at the Research Center for Humanities and Social Sciences, Academia Sinica; a Professor in the Department of Computer Science and Information Engineering at National Central University; and an Adjunct Professor at the Graduate Institute of Linguistics at National Taiwan University. He also holds the positions of President of the Taiwanese Association for Artificial Intelligence (TAAI) and President of the Taiwan Association for Digital Humanities (TADH). He holds a Ph.D. in Computer Science and Information Engineering from National Taiwan University.
His keynote will draw upon this rich, interdisciplinary experience to explore why the fusion of humanistic knowledge and machine intelligence is essential for building the next generation of truly intelligent and responsible AI systems.
From Human Learning to Machine Knowledge:
A Cross-Disciplinary Approach to Building Culturally-Aware AI
[Abstract]
The advent of large language models (LLMs) like ChatGPT marks a pivotal moment, shifting our focus from mere information access to interactive knowledge creation. However, a critical question remains: can we build AI that understands not just language, but also local culture and context? This keynote addresses the PNC 2025 theme, "Mind Meets Machine," by bridging the gap between humanistic inquiry and AI engineering.
Drawing parallels between AI training and human learning theories—Constructivism (pre-training), Behaviorism (fine-tuning), and Social Learning Theory (alignment)—this talk demystifies the process of building an LLM for a non-technical audience. Using Taiwan's own language model, TAIDE (Trustworthy AI Dialogue Engine), as a central case study, we demonstrate how a strategy of localizing an open-source model can achieve performance on par with global giants while embedding deep cultural nuances.
Furthermore, the presentation will showcase high-impact applications born from cross-disciplinary collaboration, such as "EDU TAIDE" for generating pedagogical materials and the "Taihucais" conversational search system for digital humanities research. These projects underscore a crucial message: the most valuable AI is specialized AI, and creating it requires the deep involvement of domain experts from fields like history, linguistics, and education. The talk will conclude with a call to action for humanities scholars and researchers within the Pacific Neighborhood Consortium, highlighting the immense opportunity to contribute to, and shape, the future of culturally-aware AI.