Events

Seminar on "Resilience of Multimodal Public Transportation Infrastructure systems in Hong Kong" by Prof. Shauhrat Chopra

Date: 15 September 2023, Friday Time: 4:30 PM Venue: YEUNG Building Y5-303, City University of Hong Kong Zoom Meeting ID: 967 1968 0176 Password: 123456 Speaker: Prof. Shauhrat Chopra, City University of Hong Kong   Resilience of Multimodal Public Transportation Infrastructure systems in Hong Kong Prof. Shauhrat Chopra, City University of Hong Kong   Abstract: Cities worldwide are striving to enhance their resilience in order to withstand extreme weather events such as floods, storms, and extreme temperatures associated with climate change. Concurrently, these cities are aggressively pursuing their sustainability and climate change mitigation targets. This necessitates a rethinking of urban planning and a re-engineering of infrastructure systems in the urban built environment to ensure long-term sustainability and short-term resilience. In this talk, I will discuss resilience and sustainability of interconnected and interdependent infrastructure systems in the context of the multimodal urban public transport system. As it is one of the critical infrastructure systems, any disruption on the public transportation system, even if partial, could have a debilitating impact on a city’s health, security, and economy. The public transport system in Hong Kong, for example, accounts for 90% of passenger trips in a day, and any disruption could have catastrophic cascading impacts on the city’s economic and social interactions. This is particularly concerning considering the increasing instances of climate change-induced extreme weather events. A multi-dimensional quantitative resilience assessment framework, called the ‘Resilience Cycle’ will be discussed in the context of the Hong Kong public transport system. The utility of this framework in offering insights for improving the resilience of Hong Kong’s transportation system to disruptions will be discussed, while also considering its adaptability towards sustainable infrastructure. The talk will discuss the use of systems modelling approaches, such on network analysis and GIS, and tools like life cycle assessment (LCA) to address the potential trade-offs between resilience and sustainability in decision-making. Finally, I will stress the applicability of our findings from the study of resilient multimodal public transport systems in Hong Kong to the broader realm of real-world critical infrastructure systems.   Speaker’s Bio: Dr. Shauhrat S. Chopra is an Assistant Professor at the School of Energy and Environment (SEE), City University of Hong Kong (CityU). He received his PhD in Civil and Environmental Engineering from the Swanson School of Engineering at the University of Pittsburgh, USA, in 2015. Chopra’s doctoral dissertation was focused on resilience of complex systems, including economic systems, industrial symbiosis, and critical infrastructure systems at urban and national levels. Before joining SEE, he also worked as a Postdoctoral Researcher at the Institute for Environmental Science and Policy, University of Illinois at Chicago, on the U.S. EPA-funded project focused on sustainable design of future transformative emerging technologies. At CityU, his data-driven research is focused on designing indicators for sustainability and resilience of the built environment in support of environmental decision-making.  

Seminar by Prof Quek on "A Look at Federated Learning from Different Perspectives"

Date:  14 September 2023, Thursday   Time:  10:30 am   Venue: CD634 Speaker: Prof. Tony Q.S. Quek (Cheng Tsang Man Chair Professor, Singapore University of Technology and Design (SUTD))

The Technical Committee 2 of the International Association for Pattern Recognition

The Technical Committee 2 of the International Association for Pattern Recognition is offering a PhD Summer School on Deep Learning on Graphs to be held at The Hong Kong Polytechnic University on the 31st of August 2023. The event will cover topics ranging from graph neural networks for computer vision to quantum-inspired architectures and will include a hands-on session with PyTorch Geometric.   Event website: https://sites.google.com/view/tc2-dlg

The 1st TC2 Summer School on Deep Learning on Graphs concluded on PolyU campus on the last day of August.

The 1st TC2 Summer School on Deep Learning on Graphs concluded on PolyU campus on the last day of August. Organised by Technical Committee 2 (TC2) of the International Association for Pattern Recognition (IAPR), the event saw a team of five international speakers delivering six seminars to nine local and seven non-local students, selected out of a total of 25 applicants, evenly split between MSc and PhD levels.   Prof. Andrea Torsello from Ca' Foscari University of Venice kickstarted the event with a seminar covering the history of graph (deep) learning, highlighting the challenging issues faced by researchers in this area. Prof. Xiao Bai from Beihang University showed how graph neural networks can be applied to the processing of 3D computer vision data. Dr. Luca Rossi from PolyU drew the students’ attention to the importance of creating AI models whose predictions are interpretable and explainable. Finally, Prof. Edwin Hancock from University of York talked about the exciting opportunities lying at the intersection of quantum machine learning and graph analysis. The event also included two PyTorch coding sessions delivered by Dr Luca Cosmo from Ca' Foscari University of Venice where the students had an opportunity to put the concepts they had just learned into practice.   The event was free for the attendees and financially sponsored by the PolyU Department of Electrical and Electronic Engineering. The Summer School was the first of a series of similar events that TC2 plans to organise in alternate years with the Joint IAPR International Workshops on Statistical Techniques in Pattern Recognition and Structural and Syntactic Pattern Recognition (S+SSPR), a bi-annual event now in its 20th iteration jointly organised by TC1 and the TC2, respectively the first and second oldest technical committees of the IAPR.

Seminar by Prof. Angela Yingjun Zhang on "Task-oriented communications by maximum coding rate reduction"

Presenter: Prof. Angela Yingjun Zhang Date:  17 August 2023, Thursday   Time:  4:00 pm   Venue: Room CD634, Department of Electrical and Electronic Engineering, PolyU 

High-performance Perovskite Optoelectronic Devices via Defect Passivation & Potential Career Development Opportunities at Huaqiao University

Presenter: Prof. Zhanhua Wei Date: 16 August 2023 (Wednesday) Time: 9:30 a.m. Venue: Room CD634, EEE, PolyU

Optimally Scheduling Public Safety Power Shutoffs

Date: August 3, 2023 (THU) Time: 2p.m. to 5p.m. Venue: CF617 Speaker: Antoine LESAGE-LANDRY (Assistant Professor in the Department of Electrical Engineering at Polytechnique Montréal, QC, Canada)   Abstract In an effort to reduce power system-caused wildfires, utilities carry out public safety power shutoffs (PSPS) in which portions of the grid are de-energized to mitigate the risk of ignition. The decision to call a PSPS must balance reducing ignition risks and the negative impact of service interruptions. In this talk, we consider three PSPS scheduling scenarios, which we model as dynamic programs. In the first two scenarios, we assume that N PSPSs are budgeted as part of the investment strategy. In the first scenario, a penalty is incurred for each PSPS declared past the Nth event. In the second, we assume that some costs can be recovered if the number of PSPSs is below N while still being subject to a penalty if above N. In the third, the system operator wants to minimize the number of PSPS such that the total expected cost is below a threshold. We provide optimal or asymptotically optimal policies for each case, the first two of which have closed-form expressions. Lastly, we establish the applicability of the first PSPS model’s policy to critical-peak pricing, and obtain an optimal scheduling policy to reduce the peak demand based on weather observations.   Biography Antoine Lesage-Landry is an Assistant Professor in the Department of Electrical Engineering at Polytechnique Montréal, QC, Canada. He received the B.Eng. degree in Engineering Physics from Polytechnique Montréal, QC, Canada, in 2015, and the Ph.D. degree in Electrical Engineering from the University of Toronto, ON, Canada, in 2019. From 2019 to 2020, he was a Postdoctoral Scholar in the Energy & Resources Group at the University of California, Berkeley, CA, USA. His research interests include optimization, online learning, machine learning, and their application to power systems with renewable generation.   ALL ARE WELCOME For further information, please contact Dr. KOCAR Ilhan at ilhan.kocar@polyu.edu.hk , Department of Electrical and Electronic Engineering, The Hong Kong Polytechnic University

Localized surface plasmonic sensing and microfluidics for immunodetection

Presenter: Prof Jianhua Zhou (Professor of Biomedical Engineering, Sun Yat-sen University) Date: August 3, 2023 (Thursday) Time: 11:00 a.m. - 12:00 p.m. Venue: CD634  

Analyzing and Mitigating the Impacts of Grid-edge Technologies on Power Distribution Networks

Date: August 2, 2023 (WED) Time: 2p.m. to 4p.m. Venue: CF617 Speaker: Antoine LESAGE-LANDRY (Assistant Professor in the Department of Electrical Engineering at Polytechnique Montréal, QC, Canada)   Abstract In this talk, we first present a new rapid estimation method (REM) to perform stochastic impact analysis of grid-edge technologies (GETs) to the power distribution networks. The evolution of network states' probability density functions (PDFs) in terms of GET penetration levels are characterized by the Fokker-Planck equation. The approach is illustrated on a large-scale, realistic distribution network using a modified version of the IEEE 8500 feeder, where electric vehicles (EVs) or photovoltaic systems are installed at various penetration rates. Second, we design an incentive-based mitigation strategy for equipment overloading leveraging the REM. The objective is to shift the EV charging during the peak hours when the equipment is overloaded to the off-peak hours and maintain equipment service lifetime. The incentive level and corresponding contributions from customers to alter their EV charging habits are determined by a search algorithm with provable convergence guarantee. The strategy is illustrated on the same IEEE 8500 feeder with a high EV penetration to mitigate overloads on the substation transformer.   Biography Antoine Lesage-Landry is an Assistant Professor in the Department of Electrical Engineering at Polytechnique Montréal, QC, Canada. He received the B.Eng. degree in Engineering Physics from Polytechnique Montréal, QC, Canada, in 2015, and the Ph.D. degree in Electrical Engineering from the University of Toronto, ON, Canada, in 2019. From 2019 to 2020, he was a Postdoctoral Scholar in the Energy & Resources Group at the University of California, Berkeley, CA, USA. His research interests include optimization, online learning, machine learning, and their application to power systems with renewable generation.

Research Activities on Simulation of Power System Transients at Polytechnique Montreal

Date: August 1, 2023 (TUE) Time: 2p.m. - 4p.m. Venue: CF617 Speaker: Jean MAHSEREDJIAN (Fellow, IEEE)   Abstract Jean is the main developer of the EMTP software, and his talk will reflect on recent advances in simulation technologies and capabilities. Biography Jean Mahseredjian (Fellow, IEEE) received the M.Sc. and Ph.D. degrees from Polytechnique Montréal, Montréal, QC, Canada, in 1985 and 1991, respectively. From 1987 to 2004, he was with IREQ (Hydro-Quebec), working on research and development activities related to the simulation and analysis of electromagnetic transients. In December 2004, he joined the Faculty of Electrical Engineering with Polytechnique Montréal, where he is currently a Professor.