Prof. Jiangchuan Liu
(CAE Fellow, IEEE Fellow, and an NSERC E.W.R. Steacie Memorial Fellow)
(加拿大工程院院士; IEEE 会士;
E.W.R.Steacie纪念奖获得者)
Simon Fraser University, Canada
加拿大西蒙弗雷泽大学
Biography:
Jiangchuan Liu is a Full Professor in the
School of Computing Science, Simon Fraser University, British Columbia,
Canada. He is a Fellow of The Canadian Academy of Engineering, an IEEE
Fellow, and an NSERC E.W.R. Steacie Memorial Fellow. In the past he
worked as an Assistant Professor at The Chinese University of Hong Kong,
a research fellow at Microsoft Research Asia, and an EMC-Endowed
Visiting Chair Professor of Tsinghua University. He received the BEng
degree (cum laude) from Tsinghua University, Beijing, China, in 1999,
and the PhD degree from The Hong Kong University of Science and
Technology in 2003, both in computer science. His research interests
include multimedia systems and networks, cloud and edge computing,
social networking, online gaming, and Internet of
things/RFID/backscatter. He has served on the editorial boards of
IEEE/ACM Transactions on Networking, IEEE Transactions on Network
Sciences and Engineering, IEEE Transactions on Big Data, IEEE
Transactions on Multimedia, IEEE Communications Surveys and Tutorials,
and IEEE Internet of Things Journal. He is a Steering Committee member
of IEEE Transactions on Mobile Computing and Steering Committee Chair of
IEEE/ACM IWQoS (2015-2017). He was TPC Co-Chair of IEEE INFOCOM'2021 and
General Co-Chair of IEEE INFOCOM’2024.
Speech Title: Online Multimedia Data Analytics in Challenging Environments: Experiences and Solutions (Speech Abstract)
Prof. Haijun Zhang | 张海君教授
(IEEE Fellow, IET Fellow, Distinguished Lecturer of IEEE)
IEEE会士, IET会士, IEEE通信学会杰出讲师
University of Science and Technology
Beijing, China
北京科技大学
Biography:
Haijun Zhang is currently a Full Professor and Associate Dean in School
of Computer and Communications Engineering at University of Science and
Technology Beijing, China. He was a Postdoctoral Research Fellow in
Department of Electrical and Computer Engineering, the University of
British Columbia (UBC), Canada. He serves/served as Track Co-Chair of
VTC Fall 2022 and WCNC 2020/2021, Symposium Chair of Globecom'19, TPC
Co-Chair of INFOCOM 2018 Workshop on Integrating Edge Computing,
Caching, and Offloading in Next Generation Networks, and General
Co-Chair of GameNets'16. He serves/served as an Editor of IEEE
Transactions on Communications, and IEEE Transactions on Network Science
and Engineering. He received the IEEE CSIM Technical Committee Best
Journal Paper Award in 2018, IEEE ComSoc Young Author Best Paper Award
in 2017, IEEE ComSoc Asia-Pacific Best Young Researcher Award in 2019.
He is a Distinguished Lecturer of IEEE and a Fellow of IEEE.
Speech Title: Energy Efficient 6G Resource Optimization and Management (Speech Abstract)
Prof. Xiaowen Chu | 褚晓文教授
(IEEE Fellow, Head of the Data Science and Analytics Thrust)
(IEEE 会士, 数据科学与分析学域主任)
The Hong Kong University of Science and Technology (Guangzhou)
香港科技大学（广州）
Biography:
Professor Xiaowen Chu is a Full Professor
and Head of the Data Science and Analytics Thrust at The Hong Kong
University of Science and Technology (Guangzhou). He received his
Bachelor’s degree from Tsinghua University and his Ph.D. from The Hong
Kong University of Science and Technology. His research focuses on
high-performance computing, machine learning systems, and distributed
systems. He has received seven Best Paper Awards at international
conferences, including the CCF-A ranked conferences EuroSys 2025 and
INFOCOM 2021. Professor Chu has been recognized multiple times in the
Stanford University World’s Top 2% Scientists List. He serves (or has
served) as an Associate Editor or Guest Editor for SCI-indexed journals
such as IEEE Transactions on Cloud Computing, IEEE Transactions on
Network Science and Engineering, IEEE Internet of Things Journal, IEEE
Transactions on Big Data, IEEE Network, and IEEE Transactions on
Industrial Informatics. He was the TPC Co-Chair or General Co-Chair of
IEEE MetaCom 2025, IEEE/ACM IWQoS 2024, BigCom 2023, IEEE GreenCom 2022,
IEEE HPCC 2021, IEEE DSS 2020, EAI QShine 2019, etc. For his
contributions to algorithms for communication-efficient distributed
machine learning, he was elected as an IEEE Fellow Class of 2025.
Speech Title: Accelerating Large Mixture-of-Experts Models via Pipelining and Scheduling (Speech
Abstract)
Invited Speakers/邀请报告
Assoc. Prof. Azhar Imran
(软件工程学院副教授)
Beijing University of Technology, China
北京工业大学
Biography:
Dr. Azhar Imran is currently an Associate Professor at the School of
Software Engineering, Beijing University of Technology, China. Prior to
this, he served as an Assistant Professor at the Department of Creative
Technologies, Faculty of Computing & Artificial Intelligence, Air
University, Islamabad, Pakistan. He holds a Ph.D. in Software
Engineering from Beijing University of Technology and a Master's in
Computer Science from the University of Sargodha, Pakistan. Dr. Azhar
has over 13 years of national and international academic experience,
including a tenure as Senior Lecturer at the University of Sargodha.
A renowned expert in Image Processing, Healthcare Informatics, and
Social Media Analysis, Dr. Azhar has authored 85 research articles
published in prestigious international journals and conferences. He is a
Senior Member of IEEE and serves as an editorial board member and
reviewer for several high-impact journals, including IEEE Access, MDPI
Cancers, Applied Sciences, Mathematics, and Springer Visual Computer,
among others. Dr. Azhar has delivered guest lectures and conducted
seminars at various national and international forums, contributing
significantly to multiple international conferences in various roles,
including keynote speaker and technical committee member. His research
interests span Image Processing, Social Media Analysis, Medical Image
Diagnosis, Machine Learning, and Data Mining, with a focus on
interdisciplinary research bridging computer science and human-related
fields.
Asst. Prof. Dariusz Jacek Jakóbczak
(电子与计算机科学系助理教授)
Koszalin University of Technology, Poland
波兰科沙林工业大学
Biography:
Dariusz Jacek Jakóbczak was born in Koszalin, Poland, on December 30, 1965. He graduated in mathematics (numerical methods and programming) from the University of Gdansk, Poland in 1990. He received the Ph.D. degree in 2007 in computer science from the Polish – Japanese Institute of Information Technology, Warsaw, Poland. From 1991 to 1994 he was a civilian programmer in the High Military School in Koszalin. He was a teacher of mathematics and computer science in the Private Economic School in Koszalin from 1995 to 1999. Since March 1998 he has worked in the Department of Electronics and Computer Science, Koszalin University of Technology, Poland and since October 2007 he has been an Assistant Professor in the Chair of Computer Science and Management in this department. His research interests connect mathematics with computer science and include computer vision, artificial intelligence, shape representation, curve interpolation, contour reconstruction and geometric modeling, numerical methods, probabilistic methods, game theory, operational research and discrete mathematics.
Dr. Shaofei Sun
(网络空间学院)
Beijing University of Posts and Telecommunications, China
北京邮电大学
Biography:
Sun Shaofei is currently an associate researcher at the School of
Cyberspace Security, Beijing University of Posts and Telecommunications.
His main research areas include chip security, side-channel analysis,
hardware trojans, and artificial intelligence. He has published multiple
academic papers in well-known domestic and international academic
journals. He has hosted and participated in several projects, including
National Natural Science Foundation of China projects, the National Key
R&D Program, and open projects from national key laboratories. He has
also contributed to drafting two industry standards for security chips
and has accumulated extensive knowledge and experience in the field of
sidPe-channel analysis.
Speech Title: Unsupervised Hierarchical Side-Channel Analysis on ML-KEM Cryptographic Algorithms (Speech Abstract)