Prof. Dr. Ralf Borndörfer, Freie Universität Berlin &
Zuse-Institut Berlin, Germany
Ralf Borndörfer is a professor for
Discrete Mathematics at Freie Universität Berlin and Head of the Network
Optimization Department at Zuse Institute Berlin. He works in combinatorial
optimization and integer programming with applications to the optimization of
traffic and transportation. He is a chair of the Research Campus Mathematical
Optimization and Data Analysis Laboratories (MODAL), Scientist in Charge of the
Application Area Networks of the Mathematics Cluster of Excellence MATH+, chair
of the heureka Foundation for Traffic and the Environment, and Deputy Head of
the working group Transporation and Logistics of the German Operations Research
Society; he is one of the founders of LBW Optimization Ltd. As a member of Team
Deutsche Bahn, he was a finalist of the INFORMS Franz Edelman Award 2020 for
Achievement in Operations Research.
Prof. Dr. Thorsten Koch, TU-Berlin, Germany
Prof. Dr. Thorsten Koch is
Professor for Software and Algorithms for Discrete Optimization at TU-Berlin and
head of the Applied Algorithmic Intelligence Methods and the Digital Data and
Information for Society, Science, and Culture departments at the Zuse Institute
Berlin (ZIB). He has worked in several areas, especially the planning of
infrastructure networks, chip verification, mathematics education and integer
optimization. From 2008-2014 he was the coordinator of the FORNE project, an
industry collaboration project regarding gas transportation involving five
universities and two research institutes. The project received the 2016 EURO
Excellence in Practice Award of the European OR Society. From 2013-2019 he was
head of the GasLab and the SynLab within the Research Campus MODAL (Mathematical
Optimization and Data Analysis Laboratory). The project Optimized Execution of
Dispatching conducted together with Germanys largest Gas Transmission System
Operator became finalist of the 2020 INFORMS Innovative Applications in
Analytics Award. Currently, the work is focused on developing high-performance
parallel methods for solving large-scale structured optimization problems. Such
problems arise, for example, in data-driven, real-world analysis and planning of
sustainable network infrastructures. This includes high-performance solvers for
Steiner Tree Problems in Graphs (STPG) and Quadratic Unconstraint Binary
Optimization (QUBO).
Invited Speakers
Prof. Rolysent K. Paredes
Misamis University, Philippines
Rolysent Paredes is a faculty
member of Misamis University in Ozamiz City, Philippines, where he teaches core
professional subjects for the BSIT and BSCS programs. He is also the
administrator of the university’s network infrastructure. He is a
Cisco-certified Academy instructor as well. He received his doctorate degree in
information technology from the Technological Institute of the Philippines,
Quezon City. He is an associate member of the National Research Council of the
Philippines (NRCP). His research interests include data mining, artificial
intelligence, and computer networks.
Assoc.Prof. AMIRRUDIN BIN KAMSIN
University of Malaya, Malaysia
ASSOCIATE PROFESSOR DR AMIRRUDIN
KAMSIN is a Senior Lecturer at the Department Computer System & Technology,
Faculty of Computer Science and Information Technology, Universiti Malaya,
Malaysia. He was Acting Director of Universiti Malaya Centre for Continuing
Education (UMCCed)
2019 - 2022. He was also Acting Director at the Universiti Malaya Professional
Development and Leadership Centre (UM-LEAD) 2022 - 2023 and Deputy Director
(ODL) at UMCCed 2017 – 2022. He received his BIT (Management) in 2001 and MSc in
Computer Animation in 2002 from Universiti Malaya and Bournemouth University, UK
respectively. He obtained his PhD in Computer Science from University College
London (UCL) in 2014. His research areas include human-computer interaction
(HCI), authentication systems, e-learning, mobile applications, serious game,
augmented reality and mobile health services.
Senior Engineer Zhang Shiling, State Grid Chongqing Electric Power Company,
China
As the first author, Zhang Shiling has published more than 90 SCI/EI search
papers in the domestic and foreign journals and international academic
conferences, 19 Chinese Core Journals of Peking University, won 9 provincial and
ministerial awards such as the first prize of Chongqing scientific and
technological progress and the special first prize of China Water Conservancy
and power quality management Association, authorized 1 international invention
patent, 20 national invention patents and utility models, 18 software
copyrights, and more than 20 reports of international and domestic conferences,
As the project leader, he presided over 2 provincial and ministerial projects at
the basic frontier and 3 science and technology projects at the headquarters of
State Grid Corporation of China.
Title: Research and practice of the large-scale parallel computing and
artificial intelligence algorithm in typical equipment of new power system
Abstract: Taking the converter transformer for UHV converter valve hall
as the research object, this special speech discusses the construction process
of its three-dimensional digital model from the insulation structure of the
transformer body. Further, focusing on the outgoing device and bushing structure
of converter transformer, this paper introduces the typical structure, the
actual valve hall operation environment and the heating theoretical model of
high-voltage power equipment under high harmonic load from the perspective of
high-voltage power equipment operation, analyzes electro-thermal coupling
nonlinear electric field of transformer outgoing device, and optimizes its
insulation structure by using RBF neural network and NSGA-II multi-objective
optimization algorithm. Focuses on the 3D construction of digital twin model in
the outgoing area of converter transformer. Its research method can be extended
to key components such as the converter body winding structure, oil paper
insulation area and on the load switch. The research results of this paper can
provide theoretical guidance and technical reference for the insulation
structure design of the converter transformer body, especially for the
structural design and operation maintenance of outlet device area, and can
provide some theoretical guidance for the on-line analysis of short-term current
carrying capacity and long-term aging performance of converter transformer
outlet device area.
Asst.Prof. Tianyi Li
Aalborg University, Denmark
Tianyi Li is an Assistant
Professor with Department of Computer Science, Aalborg University, Denmark. She
received her Ph.D. from Aalborg University in 2022. Her research focuses on big
data management and analytics, database technologies, and machine learning. She
has published nearly 30 papers in top-tier international conferences and
journals, including SIGMOD, ICDE, PVLDB, KDD, WWW, and TKDE. She has received
several awards, including the Best Paper Award at ICDE 2022 (as the first
author), the One of the Best Paper Award at NDBC 2022, and the Best Paper Award
at ICCSIE 2022. She serves on the program committees of prestigious conferences
such as ICDE, KDD, and AAAI. She is the project co-investigator of the Horizon
European Framework (HORIZON) Program and the Digital Research Centre Denmark
(DIREC) project.