Keynote Speakers
Prof. Kun Yang(Personal
Page)
Member of Academia
Europaea (MAE)欧洲科学院院士,
IEEE Fellow, IET Fellow,
ACM Distinguished
Scientist
Chair Professor in the
School of Computer Science
& Electronic Engineering
Head of the Network
Convergence Laboratory
(NCL)
Nanjing
University, China /
University of Essex, UK
Speech Title:
AI-enabled Self-driving
Communication Networks
Abstract:
Modern Artificial
Intelligence (AI) has proven
to be a powerful enabler
that has gained success in
many vertical fields. There
is a clear evidence of
determined effort in the
communication and network
community to explore the AI
power to deliver 6G mobile
network’s promises of being
faster, greener and smarter.
This talk starts with a
brief introduction of 6G
mobile communication
systems, and then looks into
how new AI technologies, and
in particular machine
learning, come into play in
6G from different
perspectives. It covers new
trends in 6G communication
research such as data-driven
communication system design,
semantic communications,
digital twin networks (DTN),
and large model for wireless
networks. One major
objective of these
researches is to achieve
self-driving communication
networks where lengthy
standardization of such as
communication waveforms or
protocol design can be
somehow reduced or even
eliminated, thus enabling 6G
to self-drive to versatile
requirements from vertical
industries.
Bio: Kun
Yang received his PhD from
the Department of Electronic
& Electrical Engineering of
University College London
(UCL), UK. He is currently a
Chair Professor in the
School of Computer Science &
Electronic Engineering,
University of Essex, UK,
leading the Network
Convergence Laboratory
(NCL). He is also an
affiliated professor of
UESTC. His main research
interests include wireless
networks and communications,
future Internet and edge
computing. In particular he
is interested in energy
aspects of future
communication systems such
as 6G, promoting energy
self-sustainability via both
energy efficiency (green
communications and
networking) and energy
harvesting (wireless
charging). He has managed
research projects funded by
UK EPSRC, EU FP7/H2020, and
industries. He has published
400+ papers and filed 20
patents. He serves on the
editorial boards of a number
of IEEE journals (e.g., IEEE
ComMag, TNSE, WCL, TVT). He
is a Deputy Editor-in-Chief
of IET Smart Cities Journal.
He is a Distinguished
Lecturer of IEEE ComSoc. He
has been a Judge of GSMA
GLOMO Award at World Mobile
Congress – Barcelona since
2019. He is a Member of
Academia Europaea (MAE),
IEEE Fellow, IET Fellow, and
an ACM Distinguished
Scientist.
Prof. Tony Q.S. Quek(Personal
Page)
Fellow of Academy of
Engineering
Singapore新加坡工程院院士, IEEE
Fellow,
Cheng Tsang Man Chair
Professor
ST Engineering
Distinguished Professor
Director, Future Comms R&D
Programme
Head of ISTD Pillar
Singapore University of Technology and Design, Singapore
Speech Title:
Unlocking the Potential of
Federated Learning: A Path
towards Future Network
Intelligence
Abstract:
Machine learning,
particularly distributed
learning, stands as the
cornerstone in the vision of
future network intelligence,
owing to its remarkable
capability of addressing
intricate computational
tasks and modeling
complexities. In this talk,
we provide a comprehensive
coverage of a distributed
learning paradigm rooted in
federated learning.
Specifically, we start with
a brief overview of
federated learning. Then, we
elucidate an over-the-air
computation-based variant of
federated learning, which
circumvents the
communication bottleneck by
harnessing the superposition
properties of wireless
channels. Notably, such a
scheme presents new
advantages, such as reduced
processing latency and
enhanced privacy protection.
We also discuss several
approaches to personalize
the federated learning
framework by addressing
challenges stemming from
data heterogeneity. Lastly,
we share some of our recent
works investigating the
interplay between federated
learning and foundation
models.
Bio: Tony
Q.S. Quek received the B.E.
and M.E. degrees in
Electrical and Electronics
Engineering from Tokyo
Institute of Technology,
respectively. At
Massachusetts Institute of
Technology, he earned the
Ph.D. in Electrical
Engineering and Computer
Science. Currently, he is
the Cheng Tsang Man Chair
Professor with Singapore
University of Technology and
Design (SUTD) and ST
Engineering Distinguished
Professor. He also serves as
the Head of ISTD Pillar,
Director for Future
Communications R&D
Programme, Sector Lead for
SUTD AI Program, and the
Deputy Director of SUTD-ZJU
IDEA. His current research
topics include wireless
communications and
networking, 6G, network
intelligence,
non-terrestrial networks,
and open radio access
network.
Dr. Quek has been actively
involved in organizing and
chairing sessions and has
served as a TPC member in
numerous international
conferences. He is currently
serving as an Area Editor
for the IEEE Transactions on
Wireless Communications. He
was an Executive Editorial
Committee Member of the IEEE
Transactions on Wireless
Communications, an Editor of
the IEEE Transactions on
Communications, and an
Editor of the IEEE Wireless
Communications Letters.
Dr. Quek received the 2008
Philip Yeo Prize for
Outstanding Achievement in
Research, the 2012 IEEE
William R. Bennett Prize,
the 2016 IEEE Signal
Processing Society Young
Author Best Paper Award, the
2017 CTTC Early Achievement
Award, the 2017 IEEE ComSoc
AP Outstanding Paper Award,
the 2020 IEEE Communications
Society Young Author Best
Paper Award, the 2020 IEEE
Stephen O. Rice Prize, the
2020 Nokia Visiting
Professorship, the 2022 IEEE
Signal Processing Society
Best Paper Award, and the
2021-2023 World's Top 2%
Scientists. He is a Fellow
of IEEE and a Fellow of the
Academy of Engineering
Singapore.
Prof. Qingfu Zhang(Personal
Page)
IEEE Fellow
Chair Professor of Department of Computer Science
City University of Hong Kong, China
Speech Title: Multiobjective Evolutionary Computation based Decomposition
Abstract: Many optimization problems in the real world, by nature, have multiple conflicting objectives. Unlike a single optimization problem, multiobjective optimization problem has a set of Pareto optimal solutions (Pareto front) which are often required by a decision maker. Evolutionary algorithms are able to generate an approximation to the Pareto front in a single run, and many traditional optimization methods have been also developed for dealing with multiple objectives. Combination of evolutionary algorithms and traditional optimization methods should be a next generation multiobjective optimization solver. Decomposition techniques have been well used and studied in traditional multiobjective optimization. Over the last decade, a lot of effort has been devoted to build efficient multiobjective evolutionary algorithms based on decomposition (MOEA/D). In this talk, I will describe main ideas and techniques and some recent development in MOEA/D. I will also discuss some possible research issues in multiobjective evolutionary computation.
Bio: Qingfu Zhang is Chair Professor of Computational Intelligence at the Department of Computer Science, City University of Hong Kong. His main research interests include evolutionary computation, optimization, neural networks, data analysis, and their applications. Professor Zhang is an Associate Editor of the IEEE Transactions on Evolutionary Computation and the IEEE Transactions Cybernetics. MOEA/D, a multiobjective optimization algorithm developed by him and his students, is one of the two most used multiobjective optimization framework. He was awarded the 2010 IEEE Transactions on Evolutionary Computation Outstanding Paper Award. He has been in the list of SCI highly cited researchers for five consecutive years, from 2016 to 2020. He is an IEEE fellow.
Invited Speakers
Prof. Valentina Emilia Balas
Head of Intelligent
Systems Research Centre
Aurel Vlaicu
University of Arad,
Romania
Bio: Valentina
E. Balas is currently Full
Professor in the Department
of Automatics and Applied
Software at the Faculty of
Engineering, “Aurel Vlaicu”
University of Arad, Romania.
She holds a Ph.D. Cum
Laude, in Applied
Electronics and
Telecommunications from
Polytechnic University of
Timisoara. Dr. Balas is
author of more than 400
research papers in refereed
journals and International
Conferences. Her research
interests are in Intelligent
Systems, Fuzzy Control, Soft
Computing, Smart Sensors,
Information Fusion, Modeling
and Simulation.
She is
the Editor-in Chief to
International Journal of
Advanced Intelligence
Paradigms (IJAIP) and to
International Journal of
Computational Systems
Engineering (IJCSysE),
member in Editorial Board
member of several national
and international journals
and is evaluator expert for
national, international
projects and PhD Thesis.
Dr. Balas is the Head of
Intelligent Systems Research
Centre in Aurel Vlaicu
University of Arad and Head
of the Department of
International Relations in
the same university.
She
served as General Chair of
the International Workshop
Soft Computing and
Applications (SOFA) in ten
editions organized in the
interval 2005-2022 and held
in Romania and Hungary.
Dr. Balas participated in
many international
conferences as Organizer,
Honorary Chair, Session
Chair, member in Steering,
Advisory or International
Program Committees and
Keynote Speaker.
Recently
she was working in a
national project with EU
funding support:
BioCell-NanoART = Novel
Bio-inspired Cellular
Nano-Architectures - For
Digital Integrated Circuits,
3M Euro from National
Authority for Scientific
Research and Innovation.
She is a member of European
Society for Fuzzy Logic and
Technology (EUSFLAT), member
of Society for Industrial
and Applied Mathematics
(SIAM) and a Senior Member
IEEE, member in Technical
Committee – Fuzzy Systems
(IEEE Computational
Intelligence Society), chair
of the Task Force 14 in
Technical Committee –
Emergent Technologies (IEEE
CIS), member in Technical
Committee – Soft Computing
(IEEE SMCS). She is member
in the Committee of IEEE
Romania Section as
Volunteers Training
Coordinator and vice chair
of IEEE Computational
Intelligence Society Chapter
– CIS 11. During the
interval 2021-2022 she was a
member of IEEE European
Public Policy Committee
Working Group on ICT. From
May 2023 Dr. Balas is
associate member of Romanian
Academy of Scientists.
Dr. Balas was past Vice
President (awards) of IFSA -
International Fuzzy Systems
Association Council
(2013-2015), is a Joint
Secretary of the Governing
Council of Forum for
Interdisciplinary
Mathematics (FIM), - A
Multidisciplinary Academic
Body, India. She is the
recipient of the "Tudor
Tanasescu" Prize from the
Romanian Academy for
contributions in the field
of soft computing methods
(2019) and “Stefan Odobleja”
Prize from Romanian Academy
of Scientists (2023).
Assoc. Prof. Masnida Hussin
IEEE Senior Member
University Putra
Malaysia (UPM), Malaysia
Bio: Ts.
Dr. Masnida Hussin (Senior
Member, IEEE) is an
Associate Professor at the
Department of Communication
Technology and Network,
Faculty of Computer Science
and Information Technology,
University Putra Malaysia
(UPM), Malaysia. She
received her Ph.D. degree
from the University of
Sydney, Australia, in 2012.
She is a member of the
Malaysia Board of
Professional Technologies
(MBOT), which has the title
Technologies (Ts). Her main
research interests are in
quality of services (QoS),
green computing, and
resource management for
large-scale distributed
computing such as Cloud,
Edge and Fog computing.
Masnida has authored and
coauthored a number of
research papers published in
refereed journals and
conference proceedings and
also serves on the editorial
board of several highly
reputation international
journals. Besides her
research work, she has also
been appointed coordinator
for the Master in Computer
Network since 2012. Masnida
becomes a subject-matter
expert in Cloud security in
collaboration with the Cyber
Security Malaysia (CSM)
agency. There are also
Memoranda of Understanding
(MoU) and Non-Disclosure
Agreements (NDA) with
private organizations that
are under her
responsibility. She also did
research for teaching and
learning (T&L) scopes and
received several awards from
T&L competitions and
appreciation. She has
teaching experience spanning
more than 10 years in the
areas of Computer Network
and Parallel & Distributed
computing. Masnida has
secured several research
grants in the areas of
computer networks and T&L.
She also actively
participates in other
research grants with her
colleagues. With her busy
role as an academician and
researcher, she also has
time to join community
programs, one of which is
the Digital Entrepreneurship
Workshop for Small-Medium
Enterprise Businesses that
was held in Muar, Johor,
Malaysia.
Previous ICWCSN Speakers Gallery
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