The 7th ZJU Graduate International Summer School on“Distributed Control, Optimization and Learning”Was Successfully Held

Edit: Admin Date: 2021-08-19 Visitcount: 999

From August 2 to 13, 2021, the ZJU Graduate International Summer School on Distributed Control, Optimization and Learning, organized by the Network Sensing and Control Research Group, College of Control Science and Engineering, Zhejiang University, was successfully held in the Yuquan Campus. The summer school consists of 9 guest lectures and 7 seminars delivered by leading research scholars from Zhejiang University, Chinese University of Hong Kong, Tufts University, Rice University, Arizona State University, Purdue University, Carleton University, Nanyang Technological University, Pennsylvania State University, Nankai University and Alibaba Damo Academy, respectively. This event attracts more than 200 graduate students from the worldwide. The summer school is designed with two modules. The first module is dedicated to the teaching of basic knowledge in the field of distributed control and optimization, while the second module is for bringing students frontier advanced topics related to distributed optimization. This summer school adopted the combination of online and offline teaching, with offline teaching mainly for students of Zhejiang University and online teaching for students from other universities.


Offline participation


Online participation

The opening ceremony on August 2 marked the start of the event. Professor Jinming Xu from the College of Control Science and Engineering of Zhejiang University presided over the opening ceremony and taught the first class, introducing some basic knowledge of convex optimization and explaining his profound understanding of optimization theory. Professor Xu's vivid explanation stimulated students' interest in distributed control and optimization, and the following courses and activities were carried out very smoothly. In the first week of the basic courses, the professors gave a detailed explanation of convex optimization, graph theory and consistency, distributed stochastic optimization, large-scale machine learning, distributed control and other related basic knowledge.

In the second week of the lecture, Professor Gesualdo Scutari from Purdue University introduced some new ideas and novel analyses of distributed optimization from the statistical perspective, and pointed out the underlying reasons for the failure of distributed learning in high-dimensional scenarios and the mismatch between experimental results and theoretical analysis. Professor Usman Khan from Tufts University introduced a novel algorithm framework that enables distributed learning on non-convex optimization problems, and demonstrated the reliability of his proposed method with provable theoretical results and numerical experiments with real data. Professor Cesar Uribe from Rice University explained the optimal complexity of distributed optimization algorithms, introduced a scalable algorithm that can achieve the same convergence rate as centralized counterparts, and shared some interesting application examples of distributed optimization and learning. Professor Lihua Xie from Nanyang Technological University introduced a complete set of smart sensing and localization technologies for IoT and unmanned systems, such as WiFi-based indoor positioning and human activity recognition, UWB-based positioning, and Visual-Inertial-Distance sensor fusion for positioning and mapping, and their wide interesting applications in various domains. Last but not the least, Professor Hoi To Wai from Chinese University of Hong Kong introduced the recent techniques for optimizing distributed nonconvex models  that process batch/streaming data, and explained how to balance communication and computation complexity to design efficient algorithms. Professor Shichao Liu from Carleton University introduced a co-design scheme that properly combines distributed control and event-triggered scheduling so as to meet the challenges of load frequency control in multi-area smart grid. These informative and wonderful lectures and seminars left a deep impression on the students, which would be beneficial to their own research!

In addition to the impressive online lectures, the summer school also provided lab visits and academic seminars for the students. During the lab visits, Professor Xu led the students to visit the smart micro-grid laboratory, industrial control safety laboratory (involving PLC, mechanical arm safety) and anti-aerial-robotic systems laboratory, which helped students have a deep understanding of intelligent micro-grid technology, industrial control system attack and defense technology, and anti-anti-aerial-robotic technology based on multi-sensor fusion, and have a further understanding of the engineering application of distributed control and optimization.


Students of Zhejiang University participated in lab visits

This summer school is an important measure for the School of Control Science and Engineering of Zhejiang University to build a world-class discipline and promote the level of internationalization. It also promoted the academic exchange between students and broadened their horizons. This summer school ended successfully!

Reporter: YAN Changzhi

Editor: HE Yushan

College of Control Science and Engineering

Zhejiang University

38 Zheda Rd.(Yuquan Campus)

Hangzhou, Zhejiang 310027, P. R. China


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