History
ICNGN 2023
Hangzhou, China | November 17 to 18, 2023
Welcome you to the 2nd International Conference on Intelligent Computing and Next Generation
Networks (ICNGN2023). ICNGN2023 was held as a hybrid event, with both online participation via
Zoom and in-person attendance at Hangzhou, China on Nov. 17-18, 2023. It is glad to see ICNGN
hybrid conference brought you an unforgettable and meaningful experience.
We are also pleased to have submissions and supports from a wide spectrum of academic
institutions and universities; it has really been a difficult task to select the most
representative papers. The evaluation of all the papers was performed based on the reports of
anonymous reviewers, who are qualified within the related fields.
As an official conference supported by IEEE, ICNGN 2023 has been listed on the official website
of IEEE with the ID 59831:
https://conferences.ieee.org/conferences_events/conferences/conferencedetails/59831. The
conference proceedings was successfully published and included in IEEE Xplore.
And we still have a great line-up of keynote & invited speakers including:
Prof. Kin K. Leung, Imperial College, London, UK
Dr. Yik-Chung Wu, The University of Hong Kong (HKU), China
Prof. Xiaojun Yuan, University of Electronic Science and Technology of China, China
Assoc. Prof. Yuanwei Liu, Queen Mary University of London, London, UK
Prof. Mohamed-Slim Alouini, King Abdullah University of Science and Technology (KAUST),
Saudi Arabia
Prof. Yang Yue, Xi'an Jiaotong University, China
Prof. Academician Sergey V. Ablameyko, Belarusian State University, Belarus
Prof. Chengnian Long, Shanghai Jiao Tong University, China
Prof. Tieyong Zeng, The Chinese University of Hong Kong (CUHK), Hong Kong, China
Dr. Yishu Zhang, Zhejiang University, China
Dr. Jingfeng Zhang, University of Auckland, New Zealand
Mr. Ruiqi (Richie) Liu, Wireless Research Institute, ZTE Corporation, China
Dr. Xiaogang Wang, LIGHTSPEED STUDIOS, Singapore
Appreciated so much for their contributions and willing to share their new research
developments in ICNGN.
ICNGN 2023 has been successfully held in online participation
via Zoom and
in-person attendance at Hangzhou, China on November 17-18, 2023.
For more information about ICNGN 2023, please
click here.
OUR SPEAKERS
Prof. Kin K. Leung
Imperial College, London
IEEE Fellow, IET Fellow
Kin K. Leung received his B.S. degree from the Chinese University of Hong Kong,
and his M.S. and Ph.D. degrees from University of California, Los Angeles. He joined AT&T Bell Labs
in New Jersey in 1986 and worked at its successor companies until 2004. Since then, he has been the
Tanaka Chair Professor in the Electrical and Electronic Engineering (EEE), and Computing Departments
at Imperial College in London. He serves as the Head of Communications and Signal Processing Group
in the EEE Department at Imperial. His current research focuses on optimization and machine-learning
techniques for system design and control of large-scale communications, computer and sensor
networks. He also works on multi-antenna and cross-layer designs for wireless networks.
He is a Fellow of the Royal Academy of Engineering (2022), IEEE Fellow (2001), IET Fellow (2022),
and member of Academia Europaea (2012). He received the Distinguished Member of Technical Staff
Award from AT&T Bell Labs (1994) and the Royal Society Wolfson Research Merits Award (2004-09).
Jointly with his collaborators, he received the IEEE Communications Society (ComSoc) Leonard G.
Abraham Prize (2021), the IEEE ComSoc Best Survey Paper Award (2022), the U.S.–UK Science and
Technology Stocktake Award (2021), the Lanchester Prize Honorable Mention Award (1997), and several
best conference paper awards. He currently serves as the IEEE ComSoc Distinguished Lecturer
(2022-23). He was a member (2009-11) and the chairman (2012-15) of the IEEE Fellow Evaluation
Committee for the ComSoc. He has served as guest editor and editor for 10 IEEE and ACM journals and
chaired the Steering Committee for the IEEE Transactions on Mobile Computing. Currently, he is an
editor for the ACM Computing Survey and International Journal on Sensor Networks.
Title: Machine Learning for Optimal Resource Allocationin Communications Networks
Dr. Yik-Chung Wu
The University of Hong Kong (HKU), China
IEEE Senior Member
Yik-Chung Wu received the B.Eng. (EEE) degree in 1998 and the M.Phil. degree in
2001 from the University of Hong Kong (HKU). He received the Croucher Foundation scholarship in 2002
to study Ph.D. degree at Texas A&M University, College Station, and graduated in 2005. From August
2005 to August 2006, he was with the Thomson Corporate Research, Princeton, NJ, as a Member of
Technical Staff. Since September 2006, he has been with HKU, currently as an Associate Professor. He
was a visiting scholar at Princeton University, in summers of 2015 and 2017. His research interests
are in general areas of signal processing and communication systems , and in particular Bayesian
inference, distributed algorithms, and large-scale optimization. Dr. Wu served as an Editor for IEEE
Communications Letters, and IEEE Transactions on Communications. He is currently a Senior Area
Editor for IEEE Transactions on Signal Processing, an Associate Editor for IEEE Wireless
Communications Letters, and an Editor for Journal of Communications and Networks. He was a TPC
member for over 100 IEEE major conferences. He received four best paper awards in international
conferences, with the most recent one from IEEE International Conference on Communications (ICC)
2020. He is a senior member of the IEEE.
Title: Parameter tuning-free matrix completion: A Bayesian approach
Prof. Xiaojun Yuan
University of Electronic Science and Technology of China, China
IEEE Senior Member
Assoc. Prof. Yuanwei Liu
Queen Mary University of London, London, UK
IEEE Senior Member, Web of Science Highly
Cited Researcher
Prof. Mohamed-Slim Alouini
King Abdullah University of Science and Technology (KAUST), Saudi Arabia
IEEE Fellow
Prof. Yang Yue
Xi'an Jiaotong University, China
SPIE Fellow, IEEE Senior Member and Optica Senior Member
Yang Yue received the B.S. and M.S. degrees in electrical engineering and optics
from Nankai University, China, in 2004 and 2007, respectively. He received the Ph.D. degree in
electrical engineering from the University of Southern California, USA, in 2012. He is a Professor
with the School of Information and Communications Engineering, Xi'an Jiaotong University, China. Dr.
Yue’s current research interest is intelligent photonics, including optical communications, optical
perception, and optical chip. He has published over 260 journal papers (including Science) and
conference proceedings with >10,000 citations, six edited books, two book chapters, >60 issued or
pending patents, >200 invited presentations (including 1 tutorial, >30 plenary and >50 keynote
talks). Dr. Yue is a Fellow of SPIE, a Senior Member of IEEE and Optica. He is an Associate Editor
for IEEE Access and Frontiers in Physics, Editor Board Member for four other scientific journals,
Guest Editor for >10 journal special issues. He also served as Chair or Committee Member for >100
international conferences, Reviewer for >70 prestigious journals.
Title: Machine-Learning-based Multiparameter Performance Monitoring for Optical
Communications Channels
Prof. Sergey V. Ablameyko
Belarusian State University, Belarus
IEEE Senior Member, Fellows of IEE, IAPR, NAS, BEA,
IAIPT, AE, SRAD and AAIA
Sergey Ablameyko (born in 1956, DipMath in 1978, PhD in 1984, DSc in 1990, Prof
in 1992). He was a Rector (President) of the Belarusian State University (2008-2017) and now he is a
Professor of BSU.
He has more than 650 publications including 25 authored/co-authored books and 25 edited books. In
his academic career he was a visiting scientist in Italy, Japan, Sweden, Finland, England, Germany,
UK, Greece, Spain, Australia, New Zealand, China.
He was a chair/co-chair, member of Program Committees of numerous international conferences. He is
in Editorial board of many international journals. His scientific interests are: artificial
intelligence, computer vision, knowledge based systems, geographical information systems, medical
imaging.
He is an Academician of the National Academy of Sciences of Belarus, Academician of Belarusian
Academy of Engineering, Academician of Academy of Europe, Academician of Spanish Royal Academy of
Doctors, Academician of European Academy of Economy and Enterprise Management, Academician of
Russian Academy of Natural Sciences and Russian Space Academy, Academician of Spanish Royal Academy
of Economics and Finance, Honorary professor of universities in China, Russia, Vietnam, Serbia,
Belarus. He is a Fellow and Vice-President of Asia-Pacific Artificial Intelligence Association,
Fellow of International Association for Pattern Recognition, Fellow of IEE (1995). For his activity
he was awarded by State Prize of Belarus (highest national scientific award), Friendship Award of
Russian Federation, Friendship Award of Zhejiang Province of China and many other national and
international awards.
Title: Crowd behavior analysis in video by using optical flow and CNN
Prof. Chengnian Long
Shanghai Jiao Tong University, China
IEEE Senior Member
Chengnian Long is a tenured professor of Department of Automation, School of
Electronic Information and Electrical Engineering, Shanghai Jiao Tong University. He is Deputy
Director at Blockchain Research Center, Shanghai Jiao Tong University and adjunct professor at
Intelligent Connected Electric Vehicle Innovation Center, Shanghai Jiao Tong University. His
research interest mainly focuses on the Intelligent Connected Systems(ICS), including Artificial
Intelligence of Things (AIoT), Blockchain, and Distributed Autonomous System. He was the Editor of
IEEE Transactions on Intelligent Transportation Systems, IEEE Blockchain Technical Briefs and IET
Blockchain. He is a senior member ofthe IEEE.
Title: Trustworthy Privacy-Preserving Computation for the Circulation of Data Factor
Market
Prof. Tieyong Zeng
The Chinese University of Hong Kong (CUHK), Hong Kong, China
Dr. Tieyong Zeng is a Professor at the Department of Mathematics, The Chinese
University of Hong Kong (CUHK). Together with colleagues, he has founded the Center for Mathematical
Artificial Intelligence (CMAI) since 2020 and served as the director of CMAI. He received the B.S.
degree from Peking University, Beijing, China, the M.S. degree from Ecole Polytechnique, Palaiseau,
France, and the Ph.D. degree from the University of Paris XIII, Paris, France, in 2000, 2004, and
2007, respectively. His research interests include image processing, optimization, artificial
intelligence, scientific computing, computer vision, machine learning, and inverse problems. He has
published around 100 papers in the prestigious journals such as SIAM Journal on Imaging Sciences,
SIAM Journal on Scientific Computing, Journal of Scientific Computing, IEEE Transactions on Pattern
Analysis and Machine Intelligence (TPAMI), International Journal of Computer Vision (IJCV), IEEE
Transactions on Neural Networks and Learning Systems (TNNLS), IEEE Transactions on Image Processing
(TIP), IEEE Medical Imaging (TMI), and Pattern Recognition. He is laureate of the 2021 Hong Kong
Mathematical Society (HKMS) Young Scholars Award, due to the significant contributions in
mathematical imaging and data science.
Title: Real-Time Scene Recovery
Dr. Yishu Zhang
Zhejiang University, China
Dr. Yishu Zhang is a researcher of the Science and Technology Hundred Talents
Program of the School of Micro-Nano Electronics, Zhejiang University. He graduated from Jilin
University with a bachelor's degree in Microelectronics in 2014. In 2019, he received a doctorate in
engineering from the Singapore University of Technology and Design, and later served as a
postdoctoral researcher at the National University of Singapore. During his Ph.D. study, he was
engaged in neuromorphic computing research at Sungkyunkwan University in South Korea and the
Institute of Information and Communications in Singapore. The main research directions include the
design and development of brain-inspired smart chips based on new memristive devices and
biocompatible biological smart electronic chips. During his doctoral period, he designed and
developed biologically similar ultra-low power artificial neurons and synaptic devices, laying a
solid foundation for the realization of large-scale artificial intelligence chips. Relevant results
have been published in top international academic journals such as Nature Communications, Nano
Letters, Small and Applied Physics Letters. In the Singapore Industrial Symposium, the research
results have won several poster awards from internationally renowned semiconductor companies such as
AMD, MediaTek and STMicroelectronics. In addition, he won the 2019 National Scholarship for
Outstanding Self-Financed International Students.
Title: Brain-inspired Computing with Emerging Memristors: Opportunity and challenges
Dr. Jingfeng Zhang
University of Auckland, New Zealand
Jingfeng Zhang is tenured assistant professor at the University of Auckland, and
also a scientist at the “Imperfect Information Learning Team’’ in RIKEN-AIP. He serves as guest
lecturer at the University of Tokyo in 2022-2023 and serves as main lecturer at the University of
Auckland, giving machine learning related courses.
He serves as an associate editor for IEEE Transactions on Artificial Intelligence. He is a
long-standing reviewer for prestigious ML conferences such as ICLR, ICML, NeurIPS, etc. His
long-term research interest is to build a secure and responsible ML environment.
Jingfeng is now PhD Accredited Supervisor at the University of Auckland, and actively seeking
motivated individuals who are willing to pursue a PhD degree under Jingfeng’s supervision. Jingfeng
is now interested in robust foundation models.
He obtained his Ph.D. degree at the School of Computing at the National University of Singapore. He
was the PI of multiple grants, including “JST Strategic Basic Research Programs, ACT-X,
FY2021-2023”, “JSPS Grants-in-Aid for Scientific Research (KAKENHI), Early-Career Scientists,
FY2022-2023”, “RIKEN-Kyushu Univ Science & Technology Hub Collaborative Research Program, FY2022”,
and was a recipient of the RIKEN Ohbu Award 2021 (50 recipients each year in all RIKEN's
disciplines).
Title: Towards Robust Foundation Model: Adversarial Contrastive Learning
Mr. Ruiqi (Richie) Liu
Wireless Research Institute, ZTE Corporation, China
Ruiqi (Richie) Liu (S'14-M'20) received the B.S. and M.S. degree (with honors) in
electronic engineering from the Department of Electronic Engineering, Tsinghua University in 2016
and 2019 respectively. He is now a master researcher in the wireless and computing research
institute of ZTE Corporation, responsible for long-term research as well as standardization. His
main research interests include reconfigurable intelligent surfaces, integrated sensing and
communication and wireless positioning. He is the author or co-author of several books and book
chapters. He has participated in national key research projects as the researcher or research lead.
During his 3-year service at 3GPP from 2019 to 2022, he has authored and submitted more than 500
technical documents with over 100 of them approved, and he served as the co-rapporteur of the work
item (WI) on NR RRM enhancement and the feature lead of multiple features. He currently serves as
the Vice Chair of ISG RIS in the ETSI. He actively participates in organizing committees, technical
sessions, tutorials, workshops, symposia and industry panels in IEEE conferences as the chair,
organizer, moderator, panelist or invited speaker. He served as the guest editor for Digital Signal
Processing and the lead guest editor for the special issue on 6G in IEEE OJCOMS. He serves as the
Deputy Editor-in-Chief of IET Quantum Communication and the Editor of ITU Journal of Future and
Evolving Technologies (ITU J-FET). He is the Standardization Officer for IEEE ComSoc ETI on
reconfigurable intelligent surfaces (ETI-RIS) and the Standards Liaison Officer for IEEE ComSoc
Signal Processing and Computing for Communications Technical Committee (SPCC-TC). His recent awards
include the 2022 SPCC-TC Outstanding Service Award and the Beijing Science and Technology Invention
Award (Second Prize, 2022).
Title: Reconfigurable intelligent surface enabled future network
Dr. Xiaogang Wang
LIGHTSPEED STUDIOS, Singapore
Xiaogang Wang is a senior researcher in LIGHTSPEED STUDIOS, Singapore, where he
focuses on applying computer vision techniques to design and generate 3D scenes. Before that, he was
a senior engineer at Motional, Singapore, where he conducts BEV perceptions and HD map generation.
Before joining Motional, he was a research fellow at National University of Singapore (NUS) from
Oct. 2020 to Sep. 2021. Prior to that, he did his PhD in NUS from Aug. 2016 to Aug. 2020. He has
published several top journals and conference papers, including IEEE TPAMI, CVPR, ICCV, etc. His
research focuses on deep learning and computer vision, especially for 3D generation and
reconstruction. He also serves as a reviewer for TPAMI, TNNLS, TVCG, TIP, RA-L, ICCV, ECCV, CVPR,
IROS and ICRA.
Title: Advancing Point Cloud Processing: Novel Approaches to Upsampling, Completion, and
Generation of 3D Data
