Keynote Speakers
Prof. Rajkumar Buyya
IEEE Fellow
Redmond Barry Distinguished Professor
Director of the Cloud Computing and
Distributed Systems (CLOUDS) Laboratory
University of Melbourne, Australia
Speech Title:
Neoteric Frontiers in Cloud and Quantum
Computing
Abstract:
The twenty-first-century digital
infrastructure and applications are driven
by Cloud computing and Internet of Things
(IoT) paradigms. The Cloud computing
paradigm has been transforming computing
into the 5th utility wherein "computing
utilities" are commoditized and delivered to
consumers like traditional utilities such as
water, electricity, gas, and telephony. It
offers infrastructure, platform, and
software as services, which are made
available to consumers as
subscription-oriented services on a
pay-as-you-go basis over the Internet. Its
use is growing exponentially with the
continued development of new classes of
applications such as AI-powered models
(e.g., ChatGPT) and the mining of crypto
currencies such as Bitcoins. To make Clouds
pervasive, Cloud application platforms need
to offer (1) APIs and tools for rapid
creation of scalable and elastic
applications and (2) a runtime system for
deployment of applications on geographically
distributed Data Centre infrastructures
(with Quantum computing nodes) in a seamless
manner.
This keynote presentation
will cover (a) 21st century vision of
computing and identifies various emerging IT
paradigms that make it easy to realize the
vision of computing utilities; (b)
innovative architecture
for creating
elastic Clouds integrating edge resources
and managed Clouds, (c) Aneka 6G, a 6th
generation Cloud Application Platform, for
rapid development of Big Data/AI
applications and their deployment on
private/public Clouds driven by user
requirements, (d) experimental results on
deploying Big Data/IoT applications in
engineering, health care (e.g., COVID-19),
deep learning/Artificial intelligence (AI),
satellite image processing, and natural
language processing (mining COVID-19
literature for new insights) on elastic
Clouds, (e) QFaaS: A Serverless
Function-as-a-Service Framework for Quantum
Computing, and (f) new directions for
emerging research in Cloud and Quantum
computing.
Biography:
Dr. Rajkumar Buyya is a Redmond Barry
Distinguished Professor and Director of the
Cloud Computing and Distributed Systems
(CLOUDS) Laboratory at the University of
Melbourne, Australia. He is also serving as
the founding CEO of Manjrasoft, a spin-off
company of the University, commercializing
its innovations in Cloud Computing. He has
authored over 850 publications and seven
textbooks including "Mastering Cloud
Computing" published by McGraw Hill, China
Machine Press, and Morgan Kaufmann for
Indian, Chinese and international markets
respectively. Dr. Buyya is one of the highly
cited authors in computer science and
software engineering worldwide (h-index=168
g-index=369, and 150,600+ citations). He has
been recognised as IEEE Fellow, a "Web of
Science Highly Cited Researcher" for seven
times since 2016, the "Best of the World"
twice for research fields (in Computing
Systems in 2019 and Software Systems in
2021/2022/2023) as well as "Lifetime
Achiever" and "Superstar of Research" in
"Engineering and Computer Science"
discipline twice (2019 and 2021) by the
Australian Research Review.
Software
technologies for Grid, Cloud, Fog, and
Quantum computing developed under Dr.
Buyya's leadership have gained rapid
acceptance and are in use at several
academic institutions and commercial
enterprises in 50+ countries around the
world. Manjrasoft's Aneka Cloud technology
developed under his leadership has received
"Frost New Product Innovation Award". He
served as founding Editor-in-Chief of the
IEEE Transactions on Cloud Computing. He is
currently serving as Editor-in-Chief of
Software: Practice and Experience, a
long-standing journal in the field
established 54+ years ago. He has presented
over 750 invited talks (keynotes, tutorials,
and seminars) on his vision on IT Futures,
Advanced Computing technologies, and
Spiritual Science at international
conferences and institutions in Asia,
Australia, Europe, North America, and South
America. He has recently been recognized as
a Fellow of the Academy of Europe. For
further information on Dr.Buyya, please
visit his cyberhome: www.buyya.com
Prof. Jiankun Hu
IEEE Fellow
Senior Area Editor
of IEEE Transactions on Information
Forensics and Security
University of New South Wales,
Australia
Speech Title: Privacy-Preserving
Biometric Authentication
Abstract: It is well-known
that biometrics can provide an
authentication of genuine users. Significant
advances have been made in the field with
many successful applications, e.g., border
control and digital access control.
Biometrics involves a person’s privacy data
which is regulated by laws in many
countries. There is a trend/need to develop
privacy-preserving biometrics authentication
technologies. In this talk, I’ll introduce
some major research works in this field. It
will cover the popular infinite-to-one
mapping-based cancelable biometrics template
design, Attack via Record Multiplicity
(ARM), ARM attack resilient cancelable
biometrics designs, and hill-climbing
attacks on biometrics templates. We will
introduce our latest projects/works on ARM
and hill-climbing resilient cancelable deep
learning models.
Biography:
Jiankun Hu is a professor with the School of
Systems and Computing, University of New
South Wales, Canberra, Australia. He has
received eleven Australian Research Council
(ARC) Grants and has served at the Panel on
Mathematics, Information, and Computing
Sciences, Australian Research Council ERA -
The Excellence in Research for Australia
Evaluation Committee in 2012. His research
interests are in the field of cyber security
covering intrusion detection, sensor key
management, and biometrics authentication.
His main research interest is in the field
of cyber security, including biometrics
security, where he has publications at top
venues including the IEEE TRANSACTIONS ON
PATTERN ANALYSIS AND MACHINE INTELLIGENCE,
IEEE TRANSACTIONS ON INFORMATION FORENSICS
AND SECURITY, and PATTERN RECOGNITION. He is
a Senior Area Editor of the IEEE
TRANSACTIONS ON INFORMATION FORENSICS AND
SECURITY. He has a Google h-index of 72.
Prof. Jiong Jin
World
Top 2% Scientists
for Citation
Impact since 2019
of Stanford University’s
List
Associate Dean Research (acting) in the
School of Science, Computing and Engineering
Technologies
Swinburne University of Technology,
Australia
Speech Title: Real-time Internet of
Things: Architecture, Algorithms and
Applications
Abstract: The Internet of
Things (IoT) is an emerging revolution,
which targets anytime connectivity for
anything to create smart environments in
which there is fast-paced interaction
between systems (networked sensors,
heterogeneous devices, actuators, robots)
and between such systems and people. To
further enable real-time services in IoT, a
new multi-tier computing paradigm is
recently introduced and explored in both
academic and industrial fields. Its basic
concept is to construct local computing
nodes (aka edge/fog nodes), which moves
computation, control, networking, storage
and security functionalities from
traditional remote cloud right to a place
closer to the end-users in order to
optimally support time-critical
applications. Meanwhile, it also empowers a
new set of industrial applications, such as
networked robotics and cloud-fog automation,
to achieve real-time operations. In this
talk, a complete overview and recent
developments of real-time IoT will be
presented with its applications in smart
manufacturing, smart transportation and
smart cities.
Biography:
Jiong Jin is currently a full Professor and
Associate Dean Research (acting) in the
School of Science, Computing and Engineering
Technologies, Swinburne University of
Technology. He received the B.E. degree with
First Class Honours in Computer Engineering
from Nanyang Technological University,
Singapore, in 2006, and the Ph.D. degree in
Electrical and Electronic Engineering from
the University of Melbourne, Australia, in
2011. His research interests include network
design and optimization, edge computing and
intelligence, robotics and automation, and
cyber-physical systems and Internet of
Things as well as their applications in
smart manufacturing, smart transportation
and smart cities. He is recognized as an
Honourable Mention in the AI 2000 Most
Influential Scholars List in IoT (2021 and
2022) and included in Stanford University’s
list of the world Top 2% scientists for
citation impact since 2019. He is currently
an Associate Editor of IEEE Transactions on
Industrial Informatics.
Invited Speakers
Prof. Rubita Sudirman
Universiti Teknologi Malaysia, Malaysia
Speech Title:
Prediction of Cognitive States using
Physiological Signals: A Machine Learning
Approach
Abstract:
The relationship between physiological
signals and cognitive states has been a
focus of increasing research interest due to
its potential applications in education,
healthcare, and workplace environments. This
study aimed to predict cognitive states
using multimodal physiological data. Data
were collected from ten participants during
academic exams and preprocessed to remove
artifacts. Features such as mean, standard
deviation, variance, maximum amplitude,
minimum amplitude, and power spectral
density were extracted and classified using
supervised machine learning classifiers. The
results demonstrated that EDA alone achieved
the highest classification accuracy of 80%
during Midterm 1. However, the predictive
power of EDA and other signals varied across
exams, with accuracies ranging between 40%
and 60% in Midterm 2 and the final exam.
Smaller combinations of signals, such as HR
and TEMP, also showed promising results,
achieving 60% accuracy. This study
demonstrates the feasibility of leveraging
physiological data for accurate and
efficient cognitive assessment, laying the
groundwork for future advancements in this
field.
Biography:
Professor Rubita Sudirman received her Bachelor’s and Master’s degrees in Electrical Engineering from the University of Tulsa, USA, and obtained her Ph.D. in Electrical Engineering from Universiti Teknologi Malaysia (UTM). Currently, she is a professor and certified professional engineer serving at the Faculty of Electrical Engineering, UTM. She has published more than 150 indexed papers, including journals and conference papers. Her current research interests include applications of soft computing in biomedical engineering, particularly in speech processing, EEG & EOG signal analysis, medical electronics, and rehabilitation engineering.
Prof. Qiu Chen
Kogakuin University, Japan
Speech Title: A Scene Recognition
Algorithm Using Features of Hybrid Scene
Concepts
Abstract:
A scene image is usually composed of
foreground objects and background contexts
with a certain spatial layout. For better
scene representation, we proposed in this
paper a novel scene recognition algorithm
using Features of Hybrid Scene Concepts
(FoHSC). Our approach can be simply
described as three steps, namely patch
sampling, feature extraction, and feature
encoding. First, we apply Class Activation
Mapping (CAM) to implement a special
sampling strategy, which can preserve the
essential spatial structure of the scene.
Secondarily, Convolutional Neural Networks
(CNNs) are used to extract the
learning-based features from sampling
patches. Finally, non-negative sparse coding
and spatial max pooling are performed on
each feature sub-space, respectively. The
forward path of our model is separated into
two independent data streams after patch
sampling. Experimental results on publicly
available scene datasets show that the
proposed algorithm can perform better than
the state-of-the-art methods, demonstrating
that our concatenated features benefit scene
recognition.
Biography:
Qiu Chen received his Ph.D. in
electronic engineering from Tohoku
University, Japan, in 2004. Since then, he
has held positions as an assistant professor
and associate professor at Tohoku
University. Currently, he is a professor
with Kogakuin University. His research
interests include pattern recognition,
computer vision, deep learning, information
retrieval, and their applications. He serves
on the editorial boards for several
journals, as well as committees for numerous
international conferences.
Prof. Chen Li
Anhui Jianzhu University, China
Speech Title: Construction of
PSO-SVM Model and Evaluation of Information
Service Quality in Smart Libraries in China
Abstract: Information
services play an important role in the
construction of smart libraries in
universities. Starting from domestic and
international research on smart libraries,
this article explores the connotation of
smart libraries and elaborates on the role
of information services in the construction
of smart libraries in universities. Analyze
the advantages of smart libraries in
information services. Construct an
evaluation index system for the quality of
information services in smart libraries,
including 10 indicators such as intelligent
services, information resource integration,
efficient data management and services,
convenience of information services, and
real-time updates of information data.
Analyzing the current evaluation methods for
the quality of information services in smart
libraries, there are problems such as
subjective weight setting. The evaluation
methods need to further integrate
information technology, and it is of great
significance to improve the evaluation
methods with the help of artificial
intelligence technology. This article
constructs an evaluation model for the
information service quality of the smart
library of Anhui Jianzhu University Library
in China based on PSO-SVM, and conducts
empirical analysis. The research results
show that the correlation fitting
coefficient between the simulated values and
the real values of the PSO-SVM method is
99.7789%, indicating that the PSO-SVM method
has strong reliability in the application of
information service quality evaluation in
smart libraries and is a reliable method.
Biography: CHEN LI is a
Doctoral Supervisor, Level-2 Professor, a
Renowned Teacher in Anhui Province, the
Director of the Library of Anhui Jianzhu
University, and holds a Doctorate degree.
For years, she has been engaged in research
related to artificial intelligence, project
evaluation theories and methods, and spatial
econometric analysis. She has presided over
nearly 10 national and provincial
ministerial level projects, including 1 post
- funded project of the National Social
Science Foundation, 1 project of the Anhui
Provincial Philosophy and Social Science
Planning, 3 soft science projects of the
Anhui Provincial Department of Science and
Technology, 1 general project of the Anhui
Natural Science Foundation, and 2 research
topics on the innovative development of
social sciences in Anhui Province.
She
has published over 100 academic papers,
among which nearly 30 are in SSCI, EI (JA),
CSCD, CSSCI, and core journals. As the first
completed person, she won the Second Prize
of the Anhui Provincial Social Science Award
(Social Science Category) (2019 - 2020). One
of her independently written research
reports received instructions from the main
leaders of the Anhui Provincial Party
Committee.
She presides over the
Provincial Renowned Teacher Studio, leads a
provincial level teaching team, teaches
provincial level excellent courses, has
edited 2 provincial planned textbooks,
presided over a major educational reform
project of the Anhui Provincial Department
of Education. In 2021, the postgraduate
education led by her won the First Prize of
the Provincial Teaching Achievement Award;
in 2022, she won the Second Prize of the
Anhui Provincial Social Science Award. The
case written by the team she led was
included in the case library of the China
Professional Degree Teaching Case Center of
the Ministry of Education. She has edited 2
provincial planned textbooks and published 5
monographs.
Prof. Kazuyuki Shimizu
Meiji University, Japan
Speech Title: Beating Bitcoin
Abstract: Using
Bitcoin, often referred to as "digital gold
(Proof of Work, POW)," as a benchmark, this
study investigates the development and
promotion of ecosystems driven by "digital
oil (Proof of Stake, POS)." The findings can
be summarized in three key points: (1)
Revolution in Decentralized Governance,
While current systems are dominated by
centralized control, often referred to as
the "Magnificent Seven," the Bitcoin network
achieves decentralized data management and
governance through consensus mechanisms like
PoW and PoS. This shift enables a democratic
revolution where ownership lies with the
users. (2) Universal Law of Success, The
Bitcoin network exemplifies the mathematical
"power law," representing universal
principles of success. It quantifies
economic growth dynamics exponentially,
offering a hybrid perspective that combines
traditional capital market investment
strategies with approaches tailored to
emerging (startup) markets. This framework
facilitates a paradigm shift in the economy
by enhancing productivity. (3) Optimizing
Resource Allocation, The current global
economy relies on single value benchmarks,
such as the US dollar, which leads to
inefficiencies and resource misallocations.
Adopting new benchmarks like Bitcoin,
combined with alternative indicators
(including altcoins), could enable better
resource allocation and measurement. This
process, driven by "tokenized time" as a new
productivity metric, holds the potential to
improve resource management and create a
more efficient economic framework.
Biography: Prof. Dr.
Kazuyuki Shimizu is a Professor at the
Faculty of Business Administration, Meiji
University, Japan. His research focuses on
corporate governance, stakeholder theory,
and digital transformation, with a
particular interest in blockchain
technologies and ESG investment strategies.
He has been a visiting scholar at the
University of Limerick, Ireland, and
regularly presents his work at international
conferences, including ETHICOMP and other
conferences.
Prof. Shimizu's recent
research explores the impact of digital
innovation on corporate governance and
sustainability, and he has published
extensively in both Japanese and
international academic journals. His
practical experience includes working in
institutional investor relations at German
investment banking and Barclays Capital in
Tokyo, providing him with a unique blend of
academic and industry insights.
Assoc. Prof.
Wasi Haider Butt
National University of Sciences and
Technology (NUST), Pakistan
Speech Title: Pair Elicitation, A
Novel Software Requirements Elicitation
Technique, Inspired by Pair Programming
Abstract: The success
or failure of a software product is mainly
dependent on its fitness to purpose which in
turn is fully dependent on the quality of
software requirements. The quality of
software requirements is defined by
adherence to standard software engineering
process comprising elicitation, analysis,
specifications, validation and management.
Elicitation means proactively discovering
the actual stakeholder’s requirements.
Various methods are currently being used to
elicit software requirements including
interviews, questionnaires, workshops,
storyboarding and ethnomethodology. The
traditional conventional interviews are
conducted in an old fashion and requirement
error are figured out later during analysis.
To address this issue, a novel pair
elicitation method is proposed, drawing
inspiration for extreme programming practice
of pair programming, where code writing and
inspection occur simultaneously. Using the
same approach is elicitation, requirement
elicitation and analysis to detect the
straight forward requirement errors is made
side by side. The effectiveness of the
proposed approach has been validated through
a case study of a university management
information system. The results demonstrate
significant improvements in both error
reduction and time efficiency for elicited
requirements.
Biography: Dr. Wasi
Haider Butt is a tenured Associate Professor
in the Department of Computer and Software
Engineering at the College of Electrical and
Mechanical Engineering (CEME), National
University of Sciences and Technology
(NUST), Pakistan.
He earned his Ph.D. in
Computer Software Engineering from NUST and
leads the Automated Software Engineering
Research Group at the university. Dr. Butt's
research interests encompass various facets
of computer science and software
engineering, with a particular focus on
automated software engineering.
Dr.
Butt's contributions to the field are
recognized through his publications and
research work, which are accessible via his
Google Scholar profile.
His dedication to
advancing software engineering education and
research continues to impact both his
students and the broader academic community.
Keynote Speakers of ICINT2024
|
|
|
Prof. Koichi Asatani |
Prof. Wei Xiang |
Prof. Kanta Matsuura |
