Invited Speakers
2023 8th International Conference on
Intelligent Information Technology (ICIIT 2023) aims to gather professors, researchers, scholars and industrial pioneers all
over the world. ICIIT is the premier forum for the presentation and exchange of
past experiences and new advances and research results in the field of
theoretical and industrial experience. The conference welcomes contributions
which promote the exchange of ideas and rational discourse between educators and
researchers all over the world. We aim to building an idea-trading platform for
the purpose of encouraging researcher participating in this event. ICIIT 2023 is welcome qualified persons to delivery a speech in the
related fields. If you are interested, please send a
brief CV with photo to the conference email box:
iciit@cbees.net.
Invited Speaker I

Prof. Vinod A. Prasad
Singapore Institute of Technology,
Singapore
Vinod A Prasad received his B. Tech.
degree in Instrumentation & Control Engg. From University of
Calicut, India in 1993 and the Master of Engineering (by Research)
and Ph.D. degrees from School of Computer Engineering, Nanyang
Technological University (NTU) Singapore in 2000 and 2004
respectively. In May 2022, Vinod joined the Information
Communication Technology Cluster, Singapore Institute of Technology
(SIT), Singapore, as a Professor. He also served as a Visiting
Associate Professor in Electrical & Computer Engg. Dept., University
of British Columbia, Canada, during June-July 2013. Vinod’s research
interests include digital signal processing, VLSI signal processing
circuits and systems for wireless communications, Brain-Computer
Interface and its applications in neurofeedback,
neurorehabilitation, neuroprosthetics and assistive technology
devices. He is an Associate Editor of five journals - IEEE
Transactions on Human-Machine Systems, IEEE Transactions on Neural
Systems and Rehabilitation Engineering, IEEE Transactions on
Cognitive and Developmental Systems, IEEE Systems Man & Cybernetics
Magazine, and Circuits, Systems & Signal Processing (Springer).
Invited Speaker II

Assoc. Prof. Minh Nguyen
Auckland University of Technology,
New Zealand
Associate Professor Minh Nguyen MSc,
PhD, FHEA, MIITP, is currently the Head of the Computer Science and
Software Engineering (CSSE@AUT) Department in The School of
Engineering, Computer and Mathematical Sciences at Auckland
University of Technology (AUT). The Computer Science and Software
Engineering department is one of the largest departments at AUT,
with 50 academic staff, including ten full professors and nine
associate professors. Our teaching and research staff are among the
best in New Zealand and internationally; and over 90% of our
department have PhD degrees. Minh is a Fellow of the Higher
Education Academy (UK Professional Standards Framework for teaching
and learning support in higher education) and a Full Member of IT
Professionals New Zealand. He obtained a PhD degree from the
University of Auckland in 2014 and is currently the deputy director
of the Centre for Robotics & Vision @ AUT. His research focused on
the computational theory and practice of Computer and Robot Vision,
Image Processing, Virtual Reality and Augmented Reality for
Educational and Medical purposes. He has produced over 50
publications, organised many international research conferences, and
received several grants, including three Callaghan Innovation R&D
Student-Fellow Grants, an External Fund for Multidisciplinary
Computational Anatomy, a Collaborative Research, Innovation and
Development Programme grant, etc.
Invited Speaker III

Prof. Chuan-Ming Liu
National Taipei University of
Technology,
Taiwan
Dr. Chuan-Ming Liu is a professor in
the Department of Computer Science and Information Engineering
(CSIE), National Taipei University of Technology (Taipei Tech),
Taiwan, where he was the Department Chair from 2013-2017 as well as
the Head of the Extension Education Center at the same school from
2018-2021. Dr. Liu received his Ph.D. in Computer Science from
Purdue University in 2002 and joined the CSIE Department in Taipei
Tech in the spring of 2003. In 2010 and 2011, he has held visiting
appointments with Auburn University, Auburn, AL, USA, and the
Beijing Institute of Technology, Beijing, China. He has services in
many journals, conferences and societies as well as published more
than 100 papers in many prestigious journals and international
conferences. Dr. Liu was the co-recipients of many best paper
awards, including ICUFN 2015, ICS 2016, MC 2017, WOCC 2018, MC 2019,
MC 2021, and WOCC 2021. His current research interests include big
data management and processing, uncertain data management, data
science, spatial data processing, data streams, ad-hoc and sensor
networks, location-based services.
Invited Speaker IV

Assoc. Prof. Hai Van Pham
Hanoi University of Science and
Technology,
Vietnam
Hai Van Pham is received Doctor of
Engineering degree (Ph.D.) at Ritsumeikan University (Japan) in
2013. He is currently an Associate Professor at School of
Information and Communication Technology, Hanoi University of
Science and Technology. His major includes Artificial Intelligence,
Big data, Soft Computing, Machine learning and Fuzzy Systems. He
also serves as Chairs and Co-chairs of organized several sessions at
international conferences such as KSE 2021, KSE 2019, KSE 2017, KSE
2015, SOICT 2014, etc. His publications are over 100 research papers
in Artificial Intelligence with 60 publications in ISI indices. He
is an expert of International projects such as WB experts, FORMIS
II, MOC02-WB, and US Asian Foundation, in previous years, conducting
in applied AI international and domestic projects and applications.
Speech Title: "Applied AI in Healthcare
in Covid-19 Pandemic"
Abstract: Recently, AI technologies
and tools play a key role in every aspect of the COVID-19 pandemic.
AI tools and techniques can support policymakers and medical doctors
identify COVID-19 virus together with treatments by rapidly the
world. The purpose of this talks is to give an overviews of applied
AI in COVID-19 pandemic in detecting, diagnosing the virus,
predicting its evolution monitoring the recovery and improving early
warning tools. In addition, an assistance of preventing virus'
spread is through surveillance and contact tracing human. This talks
are also given in demonstrations of COVID applications in real-world
problems to show how combined engineering and science in new
challenges of Covid-19 pandemic.
Invited Speakers
of ICIIT 2022

Prof. Xingbo Wang
Foshan University, China
Dr. & Prof. Xingbo Wang got his Master and
Doctor’s degrees at National University of Defense Technology (NUDT) of China.
Since 1994, he had worked at NUDT on CAD/CAM/CNC technologies till 2010. Since
2010, he has been a professor in Foshan University with research interests in
intelligent manufacturing system and computer applications. Prof. Wang is now in
charge of Guangdong Engineering Center of Information Security for Intelligent
Manufacturing System, where a lot of cryptography problems have to be dealt with
the elementary number theory. He then set up a new method to study odd integers
by means of perfect full binary tree and derived out many new properties of the
odd integers, including genetic property that makes it easier to factorize an
odd integer. Now Prof. Wang is devoting himself to developing a fast algorithm
to integer factorization and intending to solve the hard problem of integer
factorization.
Speech Title: "Progress in Applying
Valuated Binary Tree to Factorize Big Integers"
Abstract: Finding new methods to solve
the hard problem of integer factorization has gone on for tens of
years in cryptography but better methods are still in need. Even in
the era of quantum computing, conventional approaches are necessary
as a part of science researches. The method derived from valuated
binary tree, which was raised in 2016, has revealed rigorous power
in studying odd integers. This paper overviews the method from its
origination to its achievements so as to make people know the method
well. Four characteristics of symmetric property, genetic property,
boundary property and connection property are introduced with their
main traits. Achievements are exhibited briefly in integer
factorization of both general purpose and special purpose. The paper
shows that, the new method might be rigorous and prosperous in the
future.

Assoc. Prof. Xiaolong Li
University of Electronic Science and
Technology of China,
China
Xiaolong Li was
born in Jiangxi, China. He received the B.S. and the Ph.D. degrees
from the University of Electronic Science and Technology of China
(UESTC), Chengdu, China, in 2011 and 2017, respectively. Since 2017,
he has been a Faculty at the School of Information and Communication
Engineering, UESTC. From 2018 to 2019, he was a Visiting Researcher
with the Department of Electrical and Computer Engineering, National
University of Singapore, Singapore. He is currently an Associate
Professor at UESTC. His research interests include radar moving
target detection, weak signal parameter estimation, and MIMO radar
signal processing and radar imaging, with an emphasis on coherent
integration technique for high speed maneuvering target detection.
He was the recipient of the Prize for Excellent Ph.D. degree
dissertation of the Chinese Institute of Electronics in 2017. In
2020, he was selected in the Young Talents Program of the China
Association for Science and Technology. He was the Section Chair of
the 2019 ICCAIS, 2020 IET International Radar Conference, and 2021
CIE International Conference on Radar. He is the Guest Editor of the
Journal of Radars and frequently a Reviewer of IEEE TSP, IEEE TGRS,
IEEE GRSL, SP, DSP, and many international conferences.
Speech Title: "Signal Integration
Processing Method for Radar High Speed Moving Target Detection"
Abstract: With the development of
science technology, more and more moving objects with high speed
appear in the radar detection filed. These moving targets are often
with fast flight velocity, long attack range and strong stealth
ability, which bring great challenges to modern radar signal
processing field. How to improve the radar detection ability for the
high-speed moving targets also attracts much attentions in the
recent years. It is well-known that the signal-to-noise ratio (SNR)
of radar returns and detection performance could be enhanced
significantly via long-time signal integration of different sampling
pulses. However, because of the target’s high velocity and
maneuverability, some issues, such as range migration and Doppler
spread, should be addressed within the l signal integration
processing. Otherwise, the integration performance of traditional
moving target detection (MTD) algorithm will be severely degraded.
In this presentation, we will analyze the problems of high-speed
target coherent integration processing and establish the
corresponding target echo signal model. At the same time, we will
introduce the research progress of our group in signal coherent
integration processing area.