HKU IDS Interdisciplinary Workshop: Understanding Complex Networks for Advancing Fundamental Data Science
Organizer: Prof Alec Kirkley, Musketeers Foundation Institute of Data Science, The University of Hong Kong
Workshop Introduction
"The next century will be the century of complexity.” - Stephen Hawking
The HKU Complex Networks Lab is proud to host this two-day interdisciplinary workshop at the University of Hong Kong to bring together researchers working at the frontiers of network theory and interdisciplinary applications of networks.
Network science has emerged as a powerful framework for understanding complex systems across diverse domains including social sciences, biology, transportation, and information systems. This workshop will explore cutting-edge research in network theory, computational methods, and real-world applications.
Participants will have the opportunity to engage with world-class speakers, present their own research, and participate in collaborative sessions designed to identify new research directions and potential partnerships. The workshop is designed for researchers, graduate students, and practitioners interested in advancing the field of network science.
Date and Venue
Date
August 28-29, 2025
9:30 AM - 5:00 PM (Day 1)
9:30 AM - 5:00 PM (Day 2)
Speakers
Keynote Speakers
Guanrong Chen
City University of Hong Kong
Professor Chen received his master's degree in computer science from Sun Yat-sen University at Guangzhou in 1981 and his Ph.D. in applied mathematics from Texas A&M University in 1987. Since 2000, he has been a Chair Professor at the City University of Hong Kong. Professor Chen was elected Fellow of the IEEE in 1997 and Fellow of the Network Science Society in 2025. He was awarded the second prize of the National Natural Science Award in 2008, 2012 and 2016, respectively. In 2011, he was conferred an honorary doctorate by St. Petersburg State University and awarded the Euler Gold Medal by the Euler Foundation in Russia. In 2014, he was conferred an honorary doctorate by the University of Normandy France and was elected Member of the European Academy of Sciences. In 2015, he was elected Member of the European Academy of Engineering and Fellow of The World Academy of Sciences.
eegchen@cityu.edu.hk
Tiago Peixoto
IT:U Austria
Tiago P. Peixoto is a Professor of Complex Systems and Network Science at IT:U, Austria. His research group works at the interface between statistical physics, computational statistics, information theory, Bayesian inference, and machine learning, and has as its main focus the study of inverse problems in network science and complex systems. He received an habilitation in theoretical physics at the University of Bremen in 2017. Previously, he was an Associate Professor at the Central European University (2019-2024), Assistant Professor in Applied Mathematics at the University of Bath (2016-2019), External Researcher at the ISI Foundation (2015-2020), and post-doc researcher at the University of Bremen (2011-2016) and Technical University of Darmstadt (2008-2011). He received a PhD in Physics at the University of São Paulo in 2008.
tiago.peixoto@it-u.atInvited Speakers
Jean-Gabriel Young
University of Vermont
Jean-Gabriel Young is an Assistant Professor at the University of Vermont, where he studies statistical inference and complex systems, with a focus on network science and epidemiology. Trained as a physicist, he earned his PhD from Université Laval and was a James S. McDonnell Fellow at the University of Michigan. His work blends theory and computation to understand how structure shapes dynamics in social and biological systems.
Jean-Gabriel.Young@uvm.edu
George Cantwell
University of Cambridge
Dr George Cantwell was trained as a physicist and is now Assistant Professor of Innovative Computational Methods at the University of Cambridge. He is interested in stochastic processes and inference, particularly when these involve non-trivial structure, i.e., complex networks.
gtc31@cam.ac.uk
Hao Liao
Shenzhen University
Dr. Hao Liao is a tenured associate professor at Shenzhen University since 2015, holds a Ph.D. in Theoretical Physics from the University of Fribourg, Switzerland (2015). His research investigates the intersection of information mining and complex systems, with a focus on information dissemination, large language models, and explainable recommendation systems. Leading multiple projects funded by the National Natural Science Foundation of China, Guangdong Provincial Funds, and Shenzhen Basic Research Programs, he has secured over 40 national invention patents.
liaohao@szdx.wecom.work
Lin Wang
Shanghai Jiao Tong University
Lin Wang, Professor at Shanghai Jiao Tong University, Shanghai Dawn Scholar. Her research focuses on collaborative control and game theory for networked systems, along with scheduling optimization for large-scale swarm systems. She was honored with the First Prize of Natural Science Award by Chinese Association of Automation (2022) and the Second Prize of Shanghai Natural Science Award (2022). She currently serves as the Vice Chair of IFAC Technical Committee on Large-Scale Complex Systems, and the Vice Director of CSIAM Technical Committee on Complex Networks and Complex Systems.
wanglin@sjtu.edu.cn
Xiang Li
Fudan University
Xiang Li is a Distinguished Professor with the Research Institute of Intelligent Complex Systems, Fudan University, Shanghai, China. He chairs the CSIAM Complex networks and Complex systems Technical Committee, and served/serves as an Associate Editor (2018–2021), an Area Editor (2022–2024), and an Editor-at-large (since 2025) of IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING. His main research interests include network science and intelligent systems in both theory and applications.
lix@fudan.edu.cn
Yi Zhao
Harbin Institute of Technology (Shenzhen)
Yi Zhao received the Ph.D. degree from Hong Kong Polytechnic University, Hong Kong, China, in 2007. Since graduating, he has been with the Harbin Institute of Technology, Shenzhen, China, and is currently a professor. His recent works have been on the application of mathematical methods to a diverse range of application problems. His research interests include nonlinear dynamics, nonlinear time series analysis, and complex system modeling. He is also a Distinguished Professor of Shenzhen Pengcheng Scholars and a Fellow of the Institute of Mathematics and its Applications (FIMA, UK).
zhao.yi@hit.edu.cn
Kwang-Il Goh
Korea University
I received a PhD in statistical physics from Seoul National University, Korea, in 2004. After a postdoctoral training at University of Notre Dame, USA, I joined the faculty of Physics Department at Korea University, Korea, in 2007. My main research interest is theoretical network science---in particular, the statistical physics of network systems ranging from scale-free networks and multiplex networks to hypergraphs most recently.
kgoh@korea.ac.kr
Gangmin Son
Korea Institute for Advanced Study
Gangmin Son is a Research Fellow at the Korea Institute for Advanced Study (KIAS). He received his PhD in Physics from KAIST in 2024. During his PhD, he studied the statistical physics of networks and its real-world applications. His current research focuses mainly on generalized networks, such as multiplex networks and hypergraphs, and how their structural properties influence collective phenomena, including phase transitions.
gmson102@gmail.com
Wenwu Yu
Southeast University
Wenwu Yu received the B.Sc. degree in information and computing science and M.Sc. degree in applied mathematics from the Department of Mathematics, Southeast University, Nanjing, China, in 2004 and 2007, respectively, and the Ph.D. degree from the Department of Electronic Engineering, City University of Hong Kong, Hong Kong, China, in 2010. Currently, he is the Dean in the School of Mathematics. He is also a Full Professor with the Endowed Chair Honor in Southeast University, China. His research interests include multi-agent systems, complex networks and systems, disturbance control, distributed optimization, machine learning, game theory, cyberspace security, smart grids, intelligent transportation systems, big-data analysis, etc.
wwyu@seu.edu.cnHKU Speakers
Qingpeng Zhang
University of Hong Kong
Qingpeng Zhang is an Associate Professor in the Musketeers Foundation Institute of Data Science and the Department of Pharmacology and Pharmacy at HKU. He received the B.S. degree in Automation from Huazhong University of Science and Technology in 2009, and the Ph.D. degree in Systems and Industrial Engineering (minor in Management Information Systems) from the University of Arizona in 2012. Prior to joining HKU in 08/2023, he was an Associate Professor with the School of Data Science at The City University of Hong Kong (CityU). He previously worked as a Postdoctoral Research Associate in the Tetherless World Constellation, Department of Computer Science at Rensselaer Polytechnic Institute.
qpzhang@hku.hk
Shihui Feng
University of Hong Kong
Dr. Shihui Feng is an Assistant Professor in the Faculty of Education at The University of Hong Kong. Specializing in complex networks and learning analytics, her research focuses on developing new analytical methods and advancing theoretical frameworks to investigate collaborative learning dynamics and social interactions in digital environments.
shihuife@hku.hk
Guodong Li
University of Hong Kong
Professor Guodong Li joined the Department of Statistics & Actuarial Science, The University of Hong Kong, in 2009 as an Assistant Professor, and currently is a Professor. Prior to this, Professor Li had worked at the Division of Mathematical Sciences, Nanyang Technological University, Singapore, as an Assistant Professor since he received his PhD degree in statistics from the University of Hong Kong in 2007. He got his Bachelor and Master degrees in Statistics from Peking University.
gdli@hku.hk
Alec Kirkley
University of Hong Kong
Professor Alec Kirkley is a physicist interested in the theory of complex networks, statistical physics, as well as their applications to urban and social systems. The mathematical and computational methods he develops in his research draw on ideas from a range of disciplines including statistical physics, information theory, Bayesian inference, scientific computing, and machine learning. He received his PhD in Physics at the University of Michigan in 2021 under the supervision of Mark Newman and joined HKU as an Assistant Professor in 2022. His main research interests lie in developing principled unsupervised learning methods for noisy network data and improving the efficiency and interpretability of statistical inference methods for networks. He also adapts and applies these techniques to uncover new insights about the structure and dynamics of urban mobility as well as the underlying topology of geographical data.
akirkley@hku.hkEvent Schedule
Day 1 - August 28, 2025
| Time | Session / Speaker / Affiliation / Title |
|---|---|
| 08:45 – 09:30 | Registration |
| 09:30 – 09:35 | Opening remarks by Prof Yi Ma |
| 09:35 – 10:35 | Keynote 1 Guanrong Chen City University of Hong Kong Optimal synchronization of higher-order complex networks |
| 10:35 – 10:50 | Coffee break |
| 10:50 – 11:20 | Invited talk 1 Jean-Gabriel Young University of Vermont Independent cascades in clustered graphs |
| 11:20 – 11:50 | Invited talk 2 Qingpeng Zhang University of Hong Kong Data organization limits the predictability of binary classification |
| 11:50 – 13:20 | Lunch break (90 min) |
| 13:20 – 13:50 | Invited talk 3 Hao Liao Shenzhen University Strategic Influence Maximization from Network Science perspective |
| 13:50 – 14:20 | Invited talk 4 Lin Wang Shanghai Jiao Tong University Controllability of Large-Scale Networked Systems |
| 14:20 – 14:35 | Coffee break |
| 14:35 – 15:05 | Invited talk 5 Xiang Li Fudan University On Sync and Chimera of Higher-order Networks and Beyond |
| 15:05 – 15:35 | Invited talk 6 Kwang-Il Goh Korea University Statistical physics on random hypergraphs |
| 15:35 - 16:05 | Lab spotlight Alec Kirkley University of Hong Kong Recent research from the HKU Complex Networks Lab |
| 16:05 onwards | Panel discussion "Going beyond AI: Why data science needs complex systems and network science" Guanrong Chen, Tiago Peixoto, Kwang-Il Goh, Xiang Li, George Cantwell |
Day 2 - August 29, 2025
| Time | Session / Speaker / Affiliation / Title |
|---|---|
| 09:30 – 09:35 | Day-2 welcome & recap |
| 09:35 – 10:35 | Keynote 2 Tiago Peixoto IT:U Austria Reconstructing complex networks from dynamics and behavior |
| 10:35 – 10:50 | Coffee break |
| 10:50 – 11:20 | Invited talk 7 George Cantwell University of Cambridge Ranking and comparison |
| 11:20 – 11:50 | Invited talk 8 Yi Zhao Harbin Institute of Technology (Shenzhen) Study on higher-order propagation behaviors in networks based on simplicial complexes |
| 11:50 – 13:20 | Lunch break (90 min) |
| 13:20 – 13:50 | Invited talk 9 Gangmin Son Korea Institute for Advanced Study Phase Transitions in the Simplicial Ising Model on Hypergraphs |
| 13:50 – 14:20 | Invited talk 10 Wenwu Yu Southeast University Theories and Applications of Distributed Optimization in Networks |
| 14:20 – 14:35 | Coffee break |
| 14:35 – 15:05 | Invited talk 11 Shihui Feng University of Hong Kong Nodes and Edges in Education: A Network Science Approach to Educational Research |
| 15:05 – 15:35 | Invited talk 12 Guodong Li University of Hong Kong TBA |
| 15:35 onwards | Panel discussion "Emerging opportunities for interdisciplinary applications of network science" Qingpeng Zhang, Jean-Gabriel Young, Lin Wang, Shihui Feng |
Registration Information
Registration is required for this workshop. Please register using the form below or contact us for more information about attendance and logistics.
For questions, please email:akirkley@hku.hk