IEEE CS Guangzhou Chapter Academic Seminar Notice
Dear IEEE CS Guangzhou Chapter Members,
IEEE CS Guangzhou Chapter will host two academic seminars on the afternoon of October 12, 2026 (Monday). All members and interested colleagues are welcome to attend.
Seminar 1: Graph Structure Learning
- Speaker: Prof. Cesare Alippi (Politecnico di Milano, Italy; Università della Svizzera italiana, Switzerland)
- Time: 15:00 – 16:00, October 12, 2026
- Venue: Room 418, Engineering Building 2, Guangdong University of Technology (University Town Campus), Guangzhou
Abstract:
Graph Neural Networks rely on graph structure as a fundamental inductive bias, yet in many real-world applications the underlying relational structure is unknown, incomplete, or potentially inaccurate. Graph Structure Learning (GSL) addresses this challenge by inferring relational structures directly from data and optimizing them for the downstream task. This seminar provides an overview of the main approaches to GSL, focusing on structure initialization, edge scoring, graph sparsification, and loss design. We discuss several strategies for constructing an initial graph, including Pearson correlation, Granger causality, pairwise input similarity, Dirichlet energy minimization, and graph rewiring. Different edge-scoring approaches are then considered, ranging from input-independent parameterizations to input-dependent models based on neural networks and attention mechanisms. Particular attention is given to the challenges of learning sparse and discrete graph structures, including thresholding and Bernoulli sampling, as well as the gradient-estimation techniques required for their optimization. Finally, we discuss how downstream objectives and regularization terms can guide the learned graph toward structures that are both task-relevant and consistent with desired properties. Overall, the seminar highlights the potential of GSL as an alternative to predefined graph topologies, while emphasizing the trade-offs between expressiveness, computational efficiency, and structural constraints.
Seminar 2: Designing Feedback Systems for Rare but Devastating Events
- Speaker: Prof. Marios M. Polycarpou (University of Cyprus)
- Time: 16:00 – 17:00, October 12, 2026
- Venue: Room 418, Engineering Building 2, Guangdong University of Technology (University Town Campus), Guangzhou
Abstract:
The development of AI-enabled cyber-physical systems with multiple sensor/actuator components and feedback loops has given rise to advanced automation applications, including energy and power, intelligent transportation, water systems, manufacturing, etc. Traditionally, feedback control has focused on enhancing the tracking and robustness performance of the closed-loop system; however, as cyber-physical systems become more complex and interconnected and more interdependent, there is a need to refocus our attention not only on performance but also on the resilience of cyber-physical systems. The goal of this presentation is to provide insight into the design and analysis of intelligent monitoring methods for AI-enabled cyber-physical systems, which will ultimately lead to more resilient societies.
Speaker Bios
Cesare Alippi is Professor with the Università della Svizzera italiana (Switzerland) and Professor with the Politecnico di Milano (Italy); he is visiting Professor at the Guangdong University of Technology (China) and Consultant Professor at the Northwestern Polytechnic of Xi'an (China). He has been a visiting researcher/professor at UCL (UK), MIT (USA), ESPCI (F), CASIA (RC), A*STAR (SIN), U. Kobe (Japan). Alippi is an IEEE Fellow, ELLIS Fellow, INNS Fellow and AAIA Fellow, Past Board of Governors member of the International Neural Network Society, Past member of the Administrative Committee of the IEEE Computational Intelligence Society (CIS), Past Board of Directors member of the European Neural Network Society, Past Vice-President education of the IEEE Computational Intelligence Society, Associate Editor of Proceedings of IEEE and other journals, Past Associate editor of the IEEE Computational Intelligence Magazine, the IEEE Transactions on Instrumentation and Measurements, IEEE Transactions on Neural Networks, IEEE Transactions on Emerging Topics in Computational Intelligence and member and chair of many IEEE committees. In 2024 he received the IEEE CIS Enrique Ruspini Meritorious Service Award, the 2018 IEEE CIS Outstanding Computational Intelligence Magazine paper award, the 2016 Gabor Award from the International Neural Networks Society and the Outstanding Transactions on Neural Networks and Learning Systems Paper Award from the IEEE Computational Intelligence Society; in 2013 the IBM Faculty award; in 2004 the IEEE Instrumentation and Measurement Society Young Engineer Award. Current research activity addresses graph-based learning, adaptation and learning in non-stationary environments and Intelligence for embedded, cyber-physical systems and IoT. He holds 8 patents, has published one monograph book (translated in Chinese), 7 edited books and about 250 papers in international journals and conference proceedings.
Marios M. Polycarpou is a Professor of Electrical and Computer Engineering and the Chair of the Board of the KIOS Research and Innovation Center of Excellence at the University of Cyprus. He is also a Founding Member of the Cyprus Academy of Sciences, Letters, and Arts, a Visiting Professor of Imperial College London, and a Member of Academia Europaea (The Academy of Europe). He served as Founding Chair of the Department of Electrical and Computer Engineering and Founding Director of the KIOS Center of Excellence at the University of Cyprus. Prof. Polycarpou is the recipient of the 2023 IEEE Frank Rosenblatt Technical Field Award and the 2016 IEEE Neural Networks Pioneer Award for contributions to the theory and application of neural networks and learning systems in monitoring and control. He is a Fellow of IEEE and IFAC. He served as the President of the IEEE Computational Intelligence Society (2012–2013), as the President of the European Control Association (2017–2019), and as the Editor-in-Chief of the IEEE Transactions on Neural Networks and Learning Systems (2004–2010). Prof. Polycarpou currently serves on the Editorial Boards of the Proceedings of the IEEE and the Annual Reviews in Control. His research work has been funded by several agencies and industry in Europe and the United States, including the prestigious European Research Council (ERC) Advanced Grant, the ERC Synergy Grant and the EU-Widening Teaming program.
Registration:
Please reply to zhwyu@scut.edu.cn or contact the Chapter Secretary if you plan to attend, so we can estimate the number of participants.
We look forward to your participation.
IEEE CS Guangzhou Chapter
October 1, 2026
Date and Time
Location
Hosts
Registration
-
Add Event to Calendar
- Room 418, Engineering Building 2, Guangdong University of Technology, University Town
- Guangzhou, Guangdong
- China