Events

Seminar on "From Micro To Nano: Manipulating Structure And Function" by Prof Zhang Haixia

Date: 8 January 2024, Monday Time: 10:00 am Venue: Room CF617, Department of Electrical and Electronic Engineering, PolyU Speaker: Prof Zhang Haixia, School of Integrated Circuit, Peking University

Seminar on "High Impact Publishing at Joule" by Dr Andrew Wadsworth

Date: 11 December 2023, Monday Time: 4:30 pm Venue: Room CD634, Department of Electrical and Electronic Engineering, PolyU Speaker: Dr Andrew Wadsworth, Scientific Editor at Joule

Seminar on Reinforcement Learning Approach to Data-Driven Optimal Control of Dynamical Systems with Communication Uncertainties

Date: 8 December 2023, Friday Time: 4:30 pm Venue: YEUNG Y5-203, City University of Hong Kong Zoom Meeting ID: 967 1968 0176 Password: 123456 Speaker: Dr Yi Jiang, City University of Hong Kong   Reinforcement Learning Approach to Data-Driven Optimal Control of Dynamical Systems with Communication Uncertainties Dr Yi Jiang, City University of Hong Kong   Abstract: Data-driven optimal control problem is a focal issue in systems and control engineering, which have attracted considerable attention from the systems and control communities. Notably, in many practical applications, control systems suffer from various uncertainties from modeling, parameter estimation and the environment. In engineering applications, actuator, sensor, controller, and their communication channels are generally contaminated with noise. Moreover, system models and communication networks are subjected to uncertain constraints such as packet dropouts, transmission delays, data quantization errors, and data rate limitation. All such uncertainties typically render the underlying systems to be uncertain, which in turn adversely affects the equipped online algorithms designed and operated based on the advanced reinforcement learning and adaptive/approximate dynamic programming. In this talk, data-driven optimal control problems for both linear and nonlinear systems in presence of packet dropout are investigated. A modified Algebraic Riccati equation and a Bernoulli model-based Hamilton-Jacobi-Bellman equation are developed with known system dynamics and probability models of packet dropouts. Two reinforcement learning-based policy iteration and value iteration algorithms are further developed to obtain the solutions to them, and their convergence analysis is also provided.   Speaker’s Bio: Dr Yi Jiang received the B.Eng. degree in automation, M.S. and Ph.D. degrees in control theory and control engineering from Northeastern University, Shenyang, Liaoning, China in 2014, 2016 and 2020, respectively. From January to July 2017, he was a Visiting Scholar with the UTA Research Institute, University of Texas at Arlington, TX, USA, and from March 2018 to March 2019, he was a Research Assistant with the University of Alberta, Edmonton, Canada. Currently, he is a Postdoc Fellow with the City University of Hong Kong, China. His research interests include networked control systems, industrial process operational control, reinforcement learning and event-triggered control.   WEBINAR WEBSITE: http://cccn.ee.cityu.edu.hk/webinar/  

Seminar on "Meet the Editors" by Professor Wang Mu and Dr Noriaki Horiuchi

Date: 8 December 2023, Friday Time: 2:00 - 3:00pm Venue: Room CD634, Department of Electrical and Electronic Engineering, PolyU Speaker: Professor Wang Mu and Dr Noriaki Horiuchi

Seminar on "Organic Photovoltaics：From High-performance Narrow Bandgap Materials to Mechanism Study" by Professor Ke Gao

Date: 6 December 2023, Wednesday Time: 4:30 pm Venue: Room CD634, Department of Electrical and Electronic Engineering, PolyU Speaker: Professor Ke Gao, Shandong University

Seminar on "Towards ICT-empowered E-Mobility Service Management" by Professor Yue Cao

Date: 6 December 2023, Wednesday Time: 2:00 PM Venue: Room EF112, Department of Electrical and Electronic Engineering, PolyU Speaker: Professor Yue Cao , Wuhan University

AAEIE AGM cum Alumni Gathering

The AAEIE AGM cum Alumni Gathering 2023 was held by the Alumni Association of Department of Electronic and Information Engineering (AAEIE) at the PolyU Staff Club Restaurant, U.Green, for about 30 alumni and staff members on 5 December 2023. Mr Dominic Tse, the Chairman of AAEIE, reported the Association’s annual activities in this occasion. Prof. C.Y. Chung, Head of Department was also invited to share the latest development of EEE and the direction of the new department after the merger. Everyone was excited to see each other and catch up with old friends and teachers during this reunion!

Joint EEE-RISE-CRF Seminar on “Fused-ring electron acceptors for organic photovoltaics” conducted by Professor Zhan Xiaowei from Peking University

Date: 4 December 2023, Monday Time: 10:00 am Venue: Room CD634, Department of Electrical and Electronic Engineering, PolyU Speaker: Professor Zhan Xiaowei, Peking University

Mentorship Programme 2023-24 (for current students)

The mentorship programme 2023-24 was held by the Department at EF003, on 2 December 2023 with the support of over 70 participants, including students, teachers, and alumni. The aim of the programme is to provide students an opportunity to learn beyond the classroom; to develop a link with the industry; to enhance their educational, social and personal growth; and to have a good planning on their career development.   During the programme, students were paired with alumni and interacted with them in a delightful atmosphere. 

Seminar on "From macro to microscopic: leveraging connected automated vehicles for traffic control" by Dr Huan Yu

Date: 1 December 2023, Friday Time: 4:30 PM Venue: YEUNG B5-211, City University of Hong Kong Zoom Meeting ID: 967 1968 0176 Password: 123456 Speaker: Dr Huan Yu, Hong Kong University of Science and Technology (Guangzhou)   From macro to microscopic: leveraging connected automated vehicles for traffic control Dr Huan Yu, Hong Kong University of Science and Technology (Guangzhou)   Abstract: Emerging technologies in communications and autonomous driving technologies will enable vehicles that are “physically-connected” via car-following to be “cyber-connected” via wireless communications. As one of the most important cyber-physical systems (CPS) applications, connected automated vehicles (CAV) have been envisioned to greatly enhance efficiency, stability and safety of transportation systems. This talk will focus on CAV-based control problems in mixed traffic that consist of human-driven vehicles (HV). Cruising control strategies of CAVs are developed to not only guarantee smooth and safe driving behaviors of the ego vehicle, but also to stabilize the surrounding HVs. This talk begins with conventional traffic control of which actuation and sensing are conducted from a macroscopic viewpoint. A methodological Partial Differential Equation model-based control design for stop-and-go traffic stabilization will be discussed. Motivated by the proposed fixed-boundary traffic control, I will discuss how CAV-based sensing and control can be designed for a string of vehicles. In particular, a safety-critical traffic control framework will be introduced, employing control barrier functions to impart collision-free safety guarantees for both the CAV and HVs. Data validations using vehicle trajectory will demonstrate the efficacy of our designs. I will also highlight how the data can enhance theoretical control designs in intelligent transportation systems using physics-informed machine learning.   Speaker’s Bio: Dr. Huan Yu is an Assistant Professor at the Hong Kong University of Science and Technology (Guangzhou), jointly appointed with the Intelligent Transportation Thrust and the Robotics and Autonomous Systems Thrust, and also an Affiliate Assistant Professor in the Department of Civil and Environmental Engineering at the Hong Kong University of Science and Technology (HKUST). She received the B.Sc. degree from Northwestern Polytechnical University, and the M.Sc. and Ph.D. degrees in Mechanical and Aerospace Engineering from the University of California, San Diego, United States. She was a visiting scholar at University of California, Berkeley and Massachusetts Institute of Technology. Her research has been focused on finding safe, stable and robust solutions that combine control theory, machine learning, and traffic flow theory to advance the boundaries of intelligent transportation systems.   WEBINAR WEBSITE: http://cccn.ee.cityu.edu.hk/webinar/