IEEE TRUSTCOM/BIGDATASE/CSE/EUC/ISCI 2020 - INSTITUTE OF ...
←
→
Page content transcription
If your browser does not render page correctly, please read the page content below
IEEE TrustCom/BigDataSE/CSE/EUC/iSCI 2020
December 29, 2020 - January 1, 2021
Guangzhou, China
7-11 October, 2018
Guangzhou, Guangdong Province, China
Copyright © Institute of Computer Networks, Guangzhou University, China
http://trust.gzhu.edu.cn
The 19th IEEE International Conference on Trust, Security and Privacy in
Computing and Communications (TrustCom 2020)
The 14th IEEE International Conference on Big Data
Science and Engineering (BigDataSE 2020)
The 23rd IEEE International Conference on Computational
Science and Engineering (CSE 2020)
The 18th IEEE International Conference on Embedded and
Ubiquitous Computing (EUC 2020)
The 8th IEEE International Conference on Smart City and
Informatization (iSCI 2020)
1
Advance Program
Copyright © Institute of Computer Networks, Guangzhou University, China
http://trust.gzhu.edu.cn/
TABLE OF CONTENTS
Program at a Glance Page 03
Quick Guide to Meeting Rooms Page 07
Program Preview Page 08
Keynote Speeches Page 10
Invited Talks Page 19
Panel Discussions Page 46
Technical Sessions and Papers Page 47
Conference Venue Page 62
Introduction to Guangzhou University Page 63
Introduction to School of Computer Science and
Page 71
Cyber Engineering at Guangzhou University
Back-Cover
Sponsors and Organizers
Page
2
`IEEE TrustCom/BigDataSE/CSE/EUC/iSCI 2020
Program at a Glance (Day 1-2)
December 29 (Tuesday)
15:00-20:00 On-Site Registration (First Floor Hall)
Room 6 Room 7
08:00-10:00 TrustCom 2020 Invited Talks -1 TrustCom 2020 Invited Talks -2
10:00-10:20 Coffee/Tea Break
10:20-12:20 TrustCom 2020 Invited Talks -1 TrustCom 2020 Invited Talks -2
12:00-13:30 Lunch @ Guangdong Hotel
13:30-15:30 TrustCom 2020 Invited Talks -3 TrustCom 2020 Invited Talks -4
15:30-15:50 Coffee/Tea Break
15:50-18:30 TrustCom 2020 Invited Talks -3 TrustCom 2020 Invited Talks -4
18:30-20:30 Reception @Guangdong Hotel
December 30 (Wednesday)
08:30-20:00 On-Site Registration (First Floor Hall)
Multi-function Hall （Room 1）
Opening Ceremony
08:30-08:50
Chair: Prof. Hanpin Wang, Guangzhou University, China
Keynote 1: AI in Bioinformatics and Medicine: Challenges and Opportunities, Prof. Yi Pan
08:50-09:40
Chair: Prof. Weizhi Meng, Technical University of Denmark, Denmark
Keynote 2: Towards the Practical Blockchain System: Challenges and Practices, Prof. Hai Jin
09:40-10:30
Chair: Prof. Weizhi Meng, Technical University of Denmark, Denmark
10:30-10:40 Coffee/Tea Break
Keynote 3: Some Initial Work on Enabling Cloud, Edge and IoT with Knowledge Processing for Smart City, Prof. Weijia Jia
10:40-11:30
Chair: Prof. Yuangen Wang, Guangzhou University, China
Keynote 4: Lightweight Short-term Photovoltaic Power Prediction for Edge Computing, Prof. Albert Y. Zomaya
11:30-12:20
Chair: Prof. Yuangen Wang, Guangzhou University, China
12 :20-13:30 Lunch @ Guangdong Hotel
Room 2 Room 3 Room 4 Room 5
BigDataSE-1, Pass4IoT-1,
13:30-15:30 Panel I TrustCom-ST-1-1 iSCI-1
SmartITC-1
15:30-15:50 Coffee/Tea Break
TrustCom-PT-1,
15:50-18:00 Panel I TrustCom-TT-1 IWCSS-1
TrustCom-F&AT-1
3
December 30 (Wednesday)
Room 6 Room 7 Room 8 Room 9 Room 10
13:30-15:30 TrustCom-ST-2-1 TrustCom-ETT-2-1 IWCSS-2-1 WiP-2-1 C4W-2-1
15:30-15:50 Coffee/Tea Break
15:50-18:00 TrustCom-ST-2-2 TrustCom-ETT-2-2 IWCSS-2-2 EUC-2 iSCI-2
December 30 (Wednesday)
Room 11 Room 12
13:30-15:30 TrustCom-ETT-3-1 WiP-3-1, EUC-3-1
15:30-15:50 Coffee/Tea Break
15:50-18:00 TrustCom-ST-3-1, PASS4IoT-3 IWCSS-3-1, iSCI-3
18 :00-20 :00 Dinner @Guangdong Hotel
4
IEEE TrustCom/BigDataSE/CSE/EUC/iSCI 2020
Program at a Glance (Day 3-4)
December 31 (Thursday)
Time Multi-function Hall （Room 1）
Keynote 5: Cyber-Physical-Social Systems: System Design and Data Analytics, Prof. Laurence T. Yang
08:30-09:20
Chair: Prof. Fengwei Zhang, Southern University of Science and Technology, China
Keynote 6: A Novel LSTM-Like Architecture and its Applications in Simultaneous Learning of Time-Related Information using
9:20-10:10 Variations of Broad Learning Systems, Prof. C. L. Philip Chen
Chair: Prof. Fengwei Zhang, Southern University of Science and Technology, China
10:10-10:30 Coffee/Tea Break
Keynote 7: Edge Computing: Current Status, Trend, and the Future, Prof. Jiannong Cao
10:30-11:20
Chair: Prof. Bin Wang, Central South University, China
Keynote 8: Online Anomaly Prediction and Detection in Future Intelligent Internet, Prof. Geyong Min
11:20-12:10
Chair: Prof. Bin Wang, Central South University, China
12:10-13:30 Lunch @ Guangdong Hotel
Room 2 Room 3 Room 4
13 :30-15 :30 Panel II TrustCom-ST-1-2 TrustCom-ETT-1, WiP-1
15 :30-15 :50 Coffee/Tea Break
15 :50-18 :00 Panel II TrustCom-ST-1-3, C4W-1 CSE-1, AEIT-1, BlockChainSys-1
December 31 (Thursday)
Room 6 Room 7 Room 8 Room 9 Room 10
13 :30-15 :30 TrustCom-ST-2-3 TrustCom-F&AT-2-1 IWCSS-2-3 C4W-2-2 CSE-2-1
15 :30-15 :50 Coffee/Tea Break
TrustCom-F&AT-2-2, CSE-2-2,
15 :50-18 :00 TrustCom-ST-2-4 IWCSS-2-4 WiP-2-2
TrustCom-TT-2 MLTrustCom-2
December 31 (Thursday)
Room 11 Room 12
13 :30-15 :30 TrustCom-ETT-3-2 IWCSS-3-2
15 :30-15 :50 Coffee/Tea Break
15 :50-18 :60 TrustCom-ST-3-2, BlockchainSys-3 WiP-3-2, CSE-3
18 :00-21 :00 Banquet @Guangdong Hotel
5
January 1 (Friday)
Room 6 Room 7 Room 8 Room 9 Room 10
08 :00-10 :00 TrustCom-ST-2-5 BigDataSE-2-1 IWCSS-2-5 WiP-2-3 AEIT-2-1
10 :00-10 :20 Coffee/Tea Break
SmartITC-2,
10 :20-12 :20 TrustCom-PT-2 BlockchainSys-2 BigDataSE-2-2 AEIT-2-2
PASS4IoT-2
January 1 (Friday)
Room 11 Room 12 Room 13
TrustCom-PT-3, TrustCom-F&AT-3,
08 :00-10 :00 C4W-3
MLTrustCom-3 SmartITC-3
10 :00-10 :20 Coffee/Tea Break
10 :20-12 :20 TrustCom-TT-3 BigDataSE-3
Lunch @ Guangdong Hotel
12 :20-13 :30
Conference Closing
6
Quick Guide to Meeting Rooms
Room Number Room Name Floor
Multi-function Hall
Room 1 3F
(多功能厅)
Zhujiang Hall
Room 2 3F
(珠江厅)
Dongjiang Hall
Room 3 3F
(东江厅)
Dinghu Hall
Room 4 3F
(鼎湖厅)
Xiqiao Hall
Room 5 3F
(西樵厅)
Room 6 VR 6
Room 7 VR 7
Room 8 VR 8
Room 9 VR 9
Room 10 VR 10
Room 11 VR 11
Room 12 VR 12
Room 13 VR 13
7
`IEEE TrustCom/BigDataSE/CSE/EUC/iSCI 2020
Program Preview
Keynotes
Keynote 1: Prof. Yi Pan, Georgia State University, USA
AI in Bioinformatics and Medicine: Challenges and Opportunities
Keynote 2: Prof. Hai Jin, IEEE Fellow and CCF Fellow, Huazhong University of Science and
Technology, China
Towards the Practical Blockchain System: Challenges and Practices
Keynote 3: Prof. Weijia Jia, IEEE Fellow, Chair Professor at Beijing Normal University (Zhuhai) and
VP for Research of United International College
Some Initial Work on Enabling Cloud, Edge and IoT with Knowledge Processing for Smart City
Keynote 4: Prof. Albert Y. Zomaya, AAAS Fellow and IEEE Fellow, University of Sydney, Australia
Lightweight Short-term Photovoltaic Power Prediction for Edge Computing
Keynote 5: Prof. Laurence T. Yang, IEEE Fellow, St Francis Xavier University, Canada
Cyber-Physical-Social Systems: System Design and Data Analytics
Keynote 6: Prof. C. L. Philip Chen, FIEEE, FAAAS, South China University of Technology, China
A Novel LSTM-Like Architecture and its Applications in Simultaneous Learning of Time-Related
Information using Variations of Broad Learning Systems
Keynote 7: Prof. Jiannong Cao, IEEE Fellow, The Hong Kong Polytechnic University, Hong Kong
Edge Computing: Current Status, Trend, and the Future
Keynote 8: Prof. Geyong Min, University of Exeter, U.K.
Online Anomaly Prediction and Detection in Future Intelligent Internet
Invited Talks for IEEE TrustCom 2020 Conference and Workshops
08:00-12:20, December 29 (Tuesday)
Session TrustCom 2020 Invited Talks -1, Room 6, Chair: Prof. Xiaofei Xing, Guangzhou University, China
Session TrustCom 2020 Invited Talks -2, Room 7, Chair: Prof. Tao Peng, Guangzhou University, China
13:30-18:30, December 29 (Tuesday)
Session TrustCom 2020 Invited Talks -3, Room 6, Chair: Prof. Guojun Wang, Guangzhou University,
China
Session TrustCom 2020 Invited Talks -4, Room 7, Chair: Prof. Shuhong Chen, Guangzhou University,
China
Panels
Panel I: Advances in Cyber Engineering (Language: Chinese)
Chairs: Prof. Guojun Wang, Guangzhou University, China
Prof. Maobin Tang, Guangzhou University, China
8
Panellists: Zhigang Chen, Xuandong Li, Deqing Zou, Qiong Huang, Debiao He, Jianbin Li, and Liming
Fang
Panel II: Advances in Software Engineering (Language: Chinese)
Chairs: Prof. Hanpin Wang, Guangzhou University, China
Prof. Ying Gao, Guangzhou University, China
Panellists: Zhong Chen, Xinjun Mao, Liusheng Huang, Yong Tang, Jigang Wu, and Fengwei Zhang
Paper Sessions
A. TrustCom-1 ~ TrustCom-3
The 19th IEEE International Conference on Trust, Security and Privacy in Computing and
Communications (TrustCom 2020)
B. WiP-1 ~ WiP-3
The Work-in-Progress (WiP) Track of the 19th IEEE International Conference on Trust, Security and
Privacy in Computing and Communications (TrustCom 2020)
C. C4W-1 ~ C4W-3
The 11th International Workshop on Collaborative Computing with Cloud and Client (C4W 2020)
D. AEIT -1 ~ AEIT -2
The 10th International Workshop on Assistive Engineering and Information Technology (AEIT 2020)
E. PASS4IoT-1 ~ PASS4IoT-3
The 5th International Workshop on Privacy, Data Assurance, Security Solutions in the Internet of
Things (PASS4IoT 2020)
F. IWCSS-1 ~ IWCSS-3
The 4th International Workshop on Cyberspace Security (IWCSS 2020)
G. BlockchainSys -1 ~ BlockchainSys -3
The 3rd International Workshop on Blockchain Systems and Applications (BlockchainSys 2020)
H. MLTrustCom -2 ~ MLTrustCom -3
The 2020 International Workshop on Machine Learning for Trust, Security and Privacy in Computing
and Communications (MLTrustCom 2020)
I. SmartITC -1 ~ SmartITC -3
The 2020 International Workshop on Smart Technologies for Intelligent Transportation and
Communications (SmartITC 2020)
J. BigDataSE -1 ~ BigDataSE -3
The 14th IEEE International Conference on Big Data Science and Engineering (BigDataSE 2020)
K. CSE-1 ~ CSE-3
The 23rd IEEE International Conference on Computational Science and Engineering (CSE 2020)
L. EUC-2 ~ EUC-3
The 18th IEEE International Conference on Embedded and Ubiquitous Computing (EUC 2020)
M. iSCI-1 ~ iSCI-3
The 8th IEEE International Conference on Smart City and Informatization (iSCI 2020)
9
Keynote 1: AI in Bioinformatics and Medicine: Challenges and
Opportunities
Speaker: Prof. Yi Pan, Georgia State University, USA
Chair: Prof. Weizhi Meng, Technical University of Denmark, Denmark
About the Keynote Speaker
Dr. Yi Pan is currently a Regents’ Professor and has served as Chair of Computer
Science Department at Georgia State University from January 2005 to August 2020.
He has also served as an Interim Associate Dean and Chair of Biology Department
during 2013-2017. Dr. Pan joined Georgia State University in 2000, was promoted
to full professor in 2004, named a Distinguished University Professor in 2013 and
designated a Regents' Professor (the highest recognition given to a faculty member
by the University System of Georgia) in 2015. Dr. Pan received his B.Eng. and
M.Eng. degrees in computer engineering from Tsinghua University, China, in 1982
and 1984, respectively, and his Ph.D. degree in computer science from the University of Pittsburgh,
USA, in 1991. His profile has been featured as a distinguished alumnus in both Tsinghua Alumni
Newsletter and University of Pittsburgh CS Alumni Newsletter. Dr. Pan's current research interests
mainly include bioinformatics and health informatics using big data analytics, cloud computing, and
machine learning technologies. Dr. Pan has published more than 450 papers including over 250 journal
papers with more than 100 papers published in IEEE/ACM Transactions/Journals. In addition, he has
edited/authored 43 books. His work has been cited more than 14,400 times based on Google Scholar
and his current h-index is 74. Dr. Pan has served as an editor-in-chief or editorial board member for 20
journals including 7 IEEE Transactions. Currently, he is serving as an Associate Editor-in-Chief of
IEEE/ACM Transactions on Computational Biology and Bioinformatics. He is the recipient of many
awards including one IEEE Transactions Best Paper Award, five IEEE and other international
conference or journal Best Paper Awards, 4 IBM Faculty Awards, 2 JSPS Senior Invitation Fellowships,
IEEE BIBE Outstanding Achievement Award, IEEE Outstanding Leadership Award, NSF Research
Opportunity Award, and AFOSR Summer Faculty Research Fellowship. He has organized numerous
international conferences and delivered keynote speeches at over 60 international conferences around
the world.
Abstract:
Artificial Intelligence (AI) is the science of mimicking human intelligences and behaviors. Machine
Learning (ML), a subset of AI, trains a machine how to use algorithms or statistics to find hidden
insights and learn automatically from data. Deep learning (DL) is one of machine learning methods
where we use deep neural networks with advanced algorithms such as auto-encoding or convolution
to recognize patterns in data. AI has become very successful recently due to the availability of huge
data and powerful supercomputers. Many applications such as speech and face recognition, image
classification, natural language processing, bioinformatics, health informatics such as disease
prediction and detection suddenly took great leaps due to the advance of AI. Although various AI
architectures and novel algorithms have been invented for many bio and health applications, better
explainability, increasing prediction accuracy and speeding up the training process are still challenging
tasks among others. In this talk, I will outline recent developments in AI research for bioinformatics
and health informatics. The topics discussed include proposing more effective architectures,
10intelligently freezing layers, gradient amplification, effectively handling high dimensional data,
designing encoding schemes, mathematical proofs, optimization of hyper-parameters, effective use of
prior knowledge, embedding logic and reasoning during training, result explanation and hardware
support. These challenges create a huge number of opportunities for people in both computer science
and health care. In this talk, some of our solutions and preliminary results in these areas will be
presented and future research directions will also be identified.
11Keynote 2: Towards the Practical Blockchain System: Challenges and
Practices
Speaker: Prof. Hai Jin, IEEE Fellow and CCF Fellow, Huazhong University of Science and Technology, China
Chair: Prof. Weizhi Meng, Technical University of Denmark, Denmark
About the Keynote Speaker
Hai Jin is a Cheung Kung Scholars Chair Professor of computer science and
engineering at Huazhong University of Science and Technology (HUST) in China.
Jin received his PhD in computer engineering from HUST in 1994. In 1996, he was
awarded a German Academic Exchange Service fellowship to visit the Technical
University of Chemnitz in Germany. Jin worked at The University of Hong Kong
between 1998 and 2000, and as a visiting scholar at the University of Southern
California between 1999 and 2000. He was awarded Excellent Youth Award from
the National Science Foundation of China in 2001. Jin is the chief scientist of
National 973 Basic Research Program Project of Virtualization Technology of
Computing System, and Cloud Security. Jin is a Fellow of IEEE, Fellow of CCF, and a life member of
the ACM. He has co-authored more than 20 books and published over 900 research papers. His
research interests include computer architecture, virtualization technology, cluster computing and
cloud computing, peer-to-peer computing, network storage, and network security.
Abstract:
Blockchain is the fascinating distributed ledger technology, which holds out the promise of
disintermediation, transparency, and openness. An increasing number of businesses, academics and
even governments are starting to view blockchain systems as the cornerstone of trust the Web 3.0 era
(next generation value Internet). This presentation will first trace the source and the current
development status of blockchain systems in various application areas. Secondly, a roadmap of the
major theoretical and practical challenging issues faced by these blockchain systems will be laid out.
Finally, I will give a glimpse of harnessing the super-abundant opportunities of blockchain systems in
the future landscape.
12Keynote 3: Some Initial Work on Enabling Cloud, Edge and IoT with
Knowledge Processing for Smart City
Speaker: Prof. Weijia Jia, IEEE Fellow, Chair Professor at Beijing Normal University (Zhuhai) and VP for
Research of United International College
Chair: Prof. Yuangen Wang, Guangzhou University, China
About the Keynote Speaker
Weijia Jia is currently a Chair Professor, Director of BNU-UIC Institute of Artificial
Intelligence and Future Networks, Beijing Normal University (Zhuhai) and VP for
Research of United International College. Prior to joining UIC, he has been the
Chair Professor and the Deputy Director of State Key Laboratory of Internet of
Things for Smart City at the University of Macau and the Zhiyuan Chair Professor
at Shanghai Jiaotong University, China. He received BSc/MSc from Center South
University, China in 82/84 and Master of Applied Sci./PhD from Polytechnic
Faculty of Mons, Belgium in 92/93, respectively, all in computer science. From 93-
95, he joined German National Research Center for Information Science (GMD) in Bonn (St.
Augustine) as a research fellow. From 95-13, he worked in City University of Hong Kong as a professor.
His contributions have been recognized as optimal network routing and deployment; vertex cover;
anycast and QoS routing, and sensors networking; knowledge relation extractions; NLP and edge
computing. He has over 500 publications in the prestigious international journals/conferences and
research books and book chapters. He has received the best product awards from the International
Science & Tech. Expo (Shenzhen) in 2011/2012 and the 1st Prize of Scientific Research Awards from
the Ministry of Education of China in 2017 (list 2). He has served as area editor for various prestigious
international journals, chair and PC member/keynote speaker for many top international conferences.
He is the Fellow of IEEE and the Distinguished Member of CCF.
Abstract:
Cloud, edge and IoT are key parts of the up-to-date networks technologies for smart city while
providing QoS subject to resource constraint. In this talk, I will introduce the AI, Cloud, edge and IoT
technologies for the development of the ecosystem of smart city, in particular the knowledge graph
with multi-modal representations of knowledge triplet in cloud, edge and IoT for the smart city
respectively. I will focus on the multi-modal of knowledge processing from the perspectives of Cloud,
edge and IoT for the data sensing, acquisition, dimensionality reduction, and their vector expressions,
feature vector representations and multiple relation extractions with heterogeneity/isomorphism
information alignment. I particularly focus on establishing the overlapped relationships extractions in
the domains of multimedia and NLP. I will also introduce our recent work on multi-modal/multi-task
collaborative representations for edge computing with dynamic feature aggregations, logical
connection among tasks and efficient scheduling of edge/IoT tasks subject to resource constraints.
13Keynote 4: Lightweight Short-term Photovoltaic Power Prediction for
Edge Computing
Speaker: Prof. Albert Y. Zomaya, AAAS Fellow and IEEE Fellow, University of Sydney, Australia
Chair: Prof. Yuangen Wang, Guangzhou University, China
About the Keynote Speaker
Albert Y. ZOMAYA is currently the Chair Professor of High Performance
Computing & Networking in the School of Computer Science, University of
Sydney. He is also the Director of the Centre for Distributed and High Performance
Computing. He published more than 600 scientific papers and articles and is author,
co-author or editor of more than 25 books.
He is the Founding Editor in Chief of the IEEE Transactions on Sustainable
Computing and the Editor in Chief of the ACM Computing Surveys and previously
he served as Editor in Chief for the IEEE Transactions on Computers (2011-2014). He delivered more
than 190 keynote addresses, invited seminars, and media briefings and has been actively involved, in
a variety of capacities, in the organization of more than 700 conferences.
Professor Zomaya is the recipient of many awards, such as, the IEEE Computer Society Technical
Achievement Award (2014), the ACM MSWIM Reginald A. Fessenden Award (2017), and the New
South Wales Premier’s Prize of Excellence in Engineering and Information and Communications
Technology (2019). He is a Chartered Engineer, a Fellow of AAAS, IEEE, IET (UK), an Elected
Member of Academia Europaea, and an IEEE Computer Society’s Golden Core member. Professor
Zomaya’s research interests lie in parallel and distributed computing, networking, and complex
systems.
Abstract:
To meet the needs for energy savings in Internet of Things (IoT) systems, solar energy has been
increasingly exploited to serve as a green and renewable source to allow systems to better operate in
an energy-efficient way. In this respect, accurate photovoltaics (PV) power output prediction is a
prerequisite for any energy saving scheme employed in these systems. In this talk, I am going to discuss
a unified training framework combined with the LightGBM algorithm to obtain a prediction model,
which can provide short-term predictions of PV power output. Compared with the training in a single
powerful machine, our proposed framework is more energy-efficient and fits into devices with limited
computation and storage capabilities. The experimental results show that our proposed framework is
superior to other benchmark machine learning algorithms.
14Keynote 5: Cyber-Physical-Social Systems: System Design and Data
Analytics
Speaker: Prof. Laurence T. Yang, IEEE Fellow, St Francis Xavier University, Canada
Chair: Prof. Fengwei Zhang, Southern University of Science and Technology, China
About the Keynote Speaker
Laurence T. Yang got his BE in Computer Science and Technology and BSc in
Applied Physics both from Tsinghua University, China and Ph.D in Computer
Science from University of Victoria, Canada. He is a professor and W.F. James
Research Chair at St. Francis Xavier University, Canada. His research includes
parallel, distributed and cloud computing, embedded and ubiquitous/pervasive
computing, and big data. He has published 200+ papers in the above areas on top
IEEE/ACM Transactions/Journals including 6 and 25 papers as top 0.1% and top 1%
highly-cited ESI papers, respectively.
His recent honours and awards include IEEE Sensor Council Technical Achievement Award (2020),
IEEE Canada C. C. Gotlieb Computer Medal (2020), Fellow of Institute of Electrical and Electronics
Engineers (2020), IEEE TCCPS Most Influential Paper Award on Cyber-Physical Systems (2020),
IEEE SCSTC Most Influential Paper Award on Smart Computing (2019), IEEE TCBD Best Journal
Paper Award on Big Data (2019), Clarivate Analytics (Web of Science Group) Highly Cited Researcher
(2019-2020), Fellow of Engineering Institute of Canada (2019), AMiner Most Influential Scholar
Award for Internet of Things (2018), IEEE TCCPS Distinguished Leadership Award on Cyber-Physical
Systems (2018), IEEE SCSTC Life-Career Achievement Award on Smart Computing (2018), Fellow
of Canadian cademy of Engineering (2017), IEEE System Journal Best Paper Award (2017), IEEE
TCSC Award for Excellence in Scalable Computing (2017), Elsevier JCSS Journal Most Cited Paper
Award (2017) and the PROSE Award on Engineering and Technology (2010).
Abstract:
The Cyber-Physical-Social Systems (CPSS) are the integration of computation, communication and
control with the physical world, human knowledge and sociocultural elements. It is a novel emerging
computing paradigm and has attracted wide concerns from both industry and academia in recent years.
Currently, CPSS are still in their infancy stage.
Our first ongoing research is to study effective and efficient approaches for CPSS modeling and general
system design automation methods, as well as methods analyzing and/or improving their power and
energy, security, trust and reliability features. Once the CPSS have been designed, Our second ongoing
research is focused on the Big Data-as-a-Service framework, which includes data representation,
dimensionality reduction, incremental and distributed processing, security and privacy, deep learning,
clustering, prediction and proactive services, aiming at representing and processing big data generated
from CPSS, providing more valued smart services for human and refining the previously designed
CPSS.
This talk will present our latest research on these two directions. Corresponding case studies in some
applications such as smart traffics will be shown to demonstrate the feasibility and flexibility of the
proposed system design methodology and analytic framework.
15Keynote 6: A Novel LSTM-Like Architecture and its Applications in
Simultaneous Learning of Time-Related Information using Variations
of Broad Learning Systems
Speaker: Prof. C. L. Philip Chen, FIEEE, FAAAS, South China University of Technology, China
Chair: Prof. Fengwei Zhang, Southern University of Science and Technology, China
About the Keynote Speaker
C. L. Philip Chen (S’88–M’88–SM’94–F’07) is the Chair Professor and Dean of
the College of Computer Science and Engineering, South China University of
Technology and is a Chair Professor of the Faculty of Science and Technology,
University of Macau, where he was the former Dean (2010-2017). He is a Fellow
of IEEE, AAAS, IAPR, CAA, and HKIE; a member of Academia Europaea (AE),
European Academy of Sciences and Arts (EASA). He received IEEE Norbert
Wiener Award in 2018 for his contribution in systems and cybernetics, and machine
learnings. He was a recipient of the 2016 Outstanding Electrical and Computer
Engineers Award from his alma mater, Purdue University. He received IEEE Tran. On Neural Networks
and Learning Systems best transactions paper award two times for his papers in 2014 and 2018;
Franklin Taylor best conference award in IEEE Int’l Conf. on SMC 2019. He is a highly cited
researcher by Clarivate Analytics in 2018 and 2019.
His current research interests include cybernetics, systems, and computational intelligence. Currently,
he is the Editor-in-Chief of the IEEE Transactions on Cybernetics. He was the IEEE Systems, Man,
and Cybernetics Society President from 2012 to 2013, the Editor-in-Chief of the IEEE Transactions on
Systems, Man, and Cybernetics: Systems (2014-2019), an Associate Editor of the IEEE Transactions
on AI, IEEE Trans on SMC: Systems, and IEEE Transactions on Fuzzy Systems. He received Macau
FDCT Natural Science Award three times, Guaungdong Province Scientific and Technology
Advancement Award in first-class in 2019.
Abstract:
A long-short term memory (LSTM)-like architectures, Gated Broad Learning Systems (GBLS), will
be discussed along with the learning algorithms. This architecture is a kind of Recurrent Broad
Learning Systems – a variation of BLS. Recurrent BLS and Gated BLS and associated learning
algorithms possess three advantages: 1) higher accuracy due to the simultaneous learning of multiple
information, even compared to deep LSTM that extracts deeper but single information only; 2)
significantly faster training time due to the noniterative learning in BLS, compared to LSTM; and 3)
easy integration with other discriminant information for further improvement. The proposed methods
have been evaluated over 13 real-world datasets from various types of text classification. Compared
to RBLS, GBLS has an extra forget gate to control the flow of information (similar to LSTM) to further
improve the accuracy on text classification. From the experimental results, the proposed methods
achieve higher accuracies than that of LSTM while taking significantly less training time on most
evaluated datasets, especially when the LSTM is in deep architecture.
16Keynote 7: Edge Computing: Current Status, Trend, and the Future
Speaker: Prof. Jiannong Cao, IEEE Fellow, The Hong Kong Polytechnic University, Hong Kong
Chair: Prof. Bin Wang, Central South University, China
About the Keynote Speaker
Dr. Cao is the Otto Poon Charitable Foundation Professor in Data Science and the
Chair Professor of Distributed and Mobile Computing in the Department of
Computing at The Hong Kong Polytechnic University. He is the director of the
Internet and Mobile Computing Lab and the associate director of University’s
Research Facility in Big Data Analytics. He served the department head from 2011
to 2017.
Dr. Cao’s research interests include parallel and distributed computing, wireless
networking and mobile computing, big data and machine learning, and cloud and
edge computing. He published 5 co-authored and 9 co-edited books, and over 500 papers in major
international journals and conference proceedings. He also obtained 13 patents. Dr. Cao received many
awards for his outstanding research achievements. He is a member of Academia Europaea, a fellow of
IEEE and a distinguished member of ACM. In 2017, he received the Overseas Outstanding
Contribution Award from China Computer Federation.
Abstract:
In the past decade, we witness the emerging applications in industrial internet, connected healthcare,
supply chains and other areas where the scale of the systems and the data being generated continuously
increases, with higher demand on mobility, realtime and reliability. It will be at very high cost to send
all the data to a centralized server, as done in cloud computing, for processing and decision-making.
Edge computing is an emerging paradigm where the computation tasks are moved from centralized
cloud to edge nodes which are closer to data sources. It facilitates the evolution of IoT from
instrumentation and interconnection to intelligence. In this talk, I will describe the current status, the
trend, and the future development of edge computing. I will share our vision of future service-oriented
collaborative edge computing, with the design of a framework that supports cross-node resource
management, distributed intelligence and advanced edge computing applications.
17Keynote 8: Online Anomaly Prediction and Detection in Future
Intelligent Internet
Speaker: Prof. Geyong Min, University of Exeter, U.K.
Chair: Prof. Bin Wang, Central South University, China
About the Keynote Speaker
Professor Geyong Min is a Chair in High Performance Computing and Networking.
His research interests include Computer Networks, Cloud and Edge Computing,
Mobile and Ubiquitous Computing, Systems Modelling and Performance
Engineering. His recent research has been supported by European Horizon-2020,
UK EPSRC, Royal Society, Royal Academy of Engineering, and industrial partners.
He has published more than 200 research papers in leading international journals
including IEEE/ACM Transactions on Networking, IEEE Journal on Selected Areas
in Communications, IEEE Transactions on Computers, IEEE Transactions on
Parallel and Distributed Systems, and IEEE Transactions on Wireless Communications, and at
reputable international conferences, such as SIGCOMM-IMC, INFOCOM, and ICDCS. He is an
Associated Editor of several international journals, e.g., IEEE Transactions on Computers, and IEEE
Transactions on Cloud Computing. He served as the General Chair or Program Chair of a number of
international conferences in the area of Information and Communications Technologies.
Abstract:
Future Internet will integrate heterogeneous wireless access technologies and effective artificial
intelligence tools to provide smart, high-speed, reliable, and ubiquitous wireless communications. A
grand challenge in such a complex system is: a single failure of devices or malicious attack can trigger
a large number of alarms, leading to massive and redundant alarm information with high complexity
and correlations. To address this challenge, this talk will present a new method for data modelling and
processing, namely Support Vector Data Description (SVDD), aiming to find a hypersphere (closed
boundary) around the known dataset that can enclose all the training data with the minimum volume.
The ultimate objective is to accurately predict and quickly detect anomaly behaviors from massive
alarm information, which is very important for reducing the network operational expenditure and
enhancing the intelligence and Quality-of-Service of future Internet. An open and distributed platform
for network big data processing will then be presented to demonstrate its application for anomaly
prediction and fault detection.
18Session TrustCom 2020 Invited Talks -1
Chair: Prof. Xiaofei Xing, Guangzhou University, China
08:00-12:20, December 29 (Tuesday) Room 6
Invited Speaker 1: Prof. Md Zakirul Alam Bhuiyan, Fordham
University, NYC, NY
Title: Dependability in Privacy Protection in IoT-Cloud Platform
Email Addresses: mbhuiyan3 AT fordham.edu, zakirulalam AT
gmail.com
Abstract: Businesses, governments, and individuals depend more and
more on data protection in the edge/cloud-integrated IoT platform. As data
collection becomes broader and easier through automated data collection,
sensors, and the IoT, concerns with data privacy during data collection are drastically increasing. There
are many data collection algorithms and protocols and their privacy is also addressed to some extent,
however, it is still challenging to tell the rate of data privacy preservation together with efficient
application performance when we need high trustworthiness in data privacy. If it is not possible to
guarantee high trustworthiness with a privacy protocol or algorithm, data transmission and data
reception at the aggregation site remains untrustworthy so that low-quality, untrustworthy, or
meaningless data reception for aggregation can be possible. In some cases, it is also seen that data
privacy protected by existing protocols is itself suspect due to both internal or external attacks at the
data transmission process. In this talk, we will stress the privacy trustworthiness aspects of data
collection and processing show how untrustworthy concerns may appear during the data transmission.
We will then discuss particular techniques of how we can deal with data privacy trustworthiness.
Short-Bio: A Md Zakirul Alam Bhuiyan, PhD, is currently an Assistant Professor of the Department
of Computer and Information Sciences at Fordham University, NY, USA, the Founding Director of
Fordham Dependable and Secure System Lab (DependSys). Earlier, he worked as an Assistant
Professor at Temple University. His research focuses on cybersecurity, data-driven dependability, and
IoT/CPS Applications. His work (including 45+ JCR Q1 papers) in these areas published in top-tier
venues, such as IEEE/ACM transactions. Several works of Dr. Bhuiyan have been recognized as “ESI
Highly Cited Papers” and two works have been recognized as the “Hot Papers” in the Computer
Science field. He has received numerous awards, including the Outstanding Faculty Award, IEEE
TCSC Early Career Researcher, the IEEE Outstanding Leadership Award, and IEEE Service Award.
He has served as an organizer, general chair, program chair, workshop chair, and TPC member of
various international conferences, including IEEE (INFOCOM, ICCCN, COMSAC). He is a senior
member of IEEE and a member of ACM.
19Invited Speaker 2: Prof. Saqib Ali, University of Agriculture, Faisalabad,
Pakistan
Title: Blockchain and IoT based Textile Manufacturing Traceability
System in Industry 4.0
Email Addresses: saqibali AT gzhu.edu.cn, saqib AT uaf.edu.pk
Abstract: Growth towards Industry 4.0 has a significant impact on the textile
manufacturing industry. In this emerging technology, the business and
engineering processes are interconnected. The product traceability system is
playing a vital role in each sector. Unfortunately, the traditional systems in textile manufacturing
industries faced a lot of challenges due to in-house process and supply chain complexity. These
systems do not provide a means for reliable and rapid response to backtrack data throughout the textile
processes of the product. Blockchain and Internet of Things (IoT) based processes have the capacity
to overcome these challenges while deploying over the traditional product traceability system. The
blockchain and IoT based system provides many benefits such as communication between product
processes, reduce risk, improve quality, continuous involvement of a worker, product fault traceability,
increase supply chain visibility, customer’s reliability, and trust. In this talk, we focused on a
Blockchain and IoT based product traceability system in textile manufacturing. This system facilitates
all stakeholders like raw material suppliers, yarn manufacturers, customers, and consumers to track
and monitor the quality of their products in a complex supply chain. This system will help textile
manufacturers to improve the efficiency and quality of their products. The customer’s reliability and
trust-ability will boost the manufacturer due to automated data insertion through IoT and decentralized
traceability using blockchain technology.
Short-Bio: Saqib Ali is working as an Assistant Professor in the Department of Computer Science,
University of Agriculture, Faisalabad, Pakistan. He holds a Ph.D. in Computer Science from Universiti
Teknologi Malaysia. Currently, he is pursuing his Post Post-Doctorate studies at Guangzhou
University of China where his topic of research is Industrial Control Systems using Advance Machine
Learning techniques and Blockchain technologies. Also, he is a part of PingER project led by the
SLAC National Accelerator Laboratory, Stanford, USA in collaboration with PERN, MYREN,
CERNET, and Guangzhou University. Over the last year, his research is inclined towards Intelligent
Control Systems using IoTs and Blockchain technologies, Big Data Engineering, and Real-Time
Stream Analytics in Cyber-Physical Systems and Robotics.
20Invited Speaker 3: Prof. Valentina E. Balas, Aurel Vlaicu University of
Arad, Romania
Title: Next Generation of Computing Technologies and AI Hardware
Email Addresses: balas AT drbalas.ro, valentina.balas AT uav.ro
Abstract: The lecture is introducing new research in designing brain-
inspiring nanotechnologies for the next generation of computing
technologies. We focus on our recent research on the challenges and
opportunities to develop nano-architecture reliable and with low power
consumption. Also, we introduce a short historic of Artificial Intelligence,
his rapid rise to Deep Learning and continuing with the new trends of AI hardware.
Short-Bio: Dr. Balas is the director of Intelligent Systems Research Centre in Aurel Vlaicu University
of Arad and Director of the Department of International Relations, Programs and Projects in the same
university.
She served as General Chair of the International Workshop Soft Computing and Applications (SOFA)
in nine editions organized in the interval 2005-2020 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.
Now she is 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).
Dr. Balas was past Vice-president (responsible with 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 and recipient of the
"Tudor Tanasescu" Prize from the Romanian Academy for contributions in the field of soft computing
methods (2019).
21Invited Speaker 4: Prof. Aniello Castiglione, University of Naples
Parthenope, Italy
Title: Remote or not Remote: This is the Question? On the Security of
Collaboration Services during the COVID-19 Pandemic
Email Addresses: castiglione AT ieee.org, castiglione AT acm.org,
castiglione AT computer.org
Abstract: In these days, due to the emergency for the COVID-19 pandemic
crisis, as part of the measures adopted by Governments around the world, the use of collaboration
services for smart working, meetings, study groups and any other activity become very common and
widespread. It is clear that all the activities that are made online using the collaboration services
strongly recall the need of Security and Privacy. In fact, those collaboration services are used for
several tasks, managing public, private or classified information. Recently, the NSA published a draft
document that gives recommendations on the use of collaboration applications by US Government
people classifying them according to the presence of several security features, such as the existence of
end-to-end encryption, the use of multi-factor authentication, the availability of the source codes, and
so on. Starting from the NSA document some of the most widespread collaborative applications were
analyzed. The analysis was oriented in checking the overall security of such tools both from the
adopted cryptographic protocols and from the point of view of the service availability (in terms of
number of different IP addresses and their geographic distribution).
The assessment showed that almost all the most adopted collaboration services are vulnerable by
serious flaws such as allow an attacker to steal sensitive information belonging to the users (such as
the login/password used for accessing those services), intercept and modify all the exchanged message
and, last but not least, alter the functionalities/features that are granted to a user letting him/her to
acquire additional privileges without the permission of his/her organization. The presented
methodology can be easily implemented by not expert people and can also be adopted to assess all the
collaboration services that are (and will be) used all around the world.
Short-Bio: Aniello Castiglione received the Ph.D. degree in Computer Science from the University of
Salerno, Italy. He is currently with the Department of Science and Technology, University of Naples
Parthenope, Italy. Previously, he was Adjunct Professor at the University of Salerno, Italy, and at the
University of Naples ‘‘Federico II’’, Italy. He authored around 220 papers in international journals and
conferences. Considering his journal papers, more than 70 of them are ranked Q1 in Scopus/Scimago
classification and more than 50 of them are ranked Q1 in the Clarivate Analytics/ISI-WoS
classification. The international academic profile of Dr. Castiglione is spread among his 86
international co-authors who belong to 75 different institutions located in 18 countries. He served in
the organization (mainly as the program chair and a TPC member) in around 230 international
conferences (some of them are ranked A+/A/A- in the CORE, LiveSHINE, and Microsoft Academic
international classifications). Currently, he is the Editor-in-Chief for the Special Issues for the Journal
of Ambient Intelligence and Humanized Computing (Springer). He served as the Managing Editor for
two ISI-ranked international journals and as a Reviewer in around 110 international journals. In
addition, served as a Guest Editor for around 30 Special Issues and served as an Editor on more than
10 Editorial Boards of international journals such as IEEE Transactions on Sustainable Computing,
IEEE Access, IET Image Processing (IET), Journal of Ambient Intelligence and Humanized
Computing (Springer), Sustainability (MDPI), Smart Cities (MDPI), Future Internet (MDPI). One of
his papers (published in the IEEE Transactions on Dependable and Secure Computing) was selected
as “Featured Article” in the “IEEE Cybersecurity Initiative” in 2014. In 2018, another paper (published
on the IEEE Cloud Computing) was selected as the Featured Article in the "IEEE Cloud Computing
22Initiative". His current research interests include Information Forensics, Digital Forensics, Security
and Privacy on Cloud, Communication Networks, Applied Cryptography, and Sustainable Computing.
He is a member of IEEE and ACM.
23Invited Speaker 5: Prof. Kim-Kwang Raymond Choo, University of
Texas at San Antonio, USA
Title: Internet of Things (IoT) Forensics: Challenges and Opportunities
Email Addresses: raymond.choo AT fulbrightmail.org
Abstract: Internet of Things (IoT) devices are becoming commonplace in
our society, due to their widespread applications (e.g., environmental
monitoring, smart cities, healthcare, surveillance, and battlefields such as
Internet of Battlefield Things). Such devices are also generally capable of capturing a broad range of
information, including digital artefacts that can facilitate a digital investigation during a cyber security
incident (e.g., data breach). While IoT devices are potential evidence acquisition sources, there are a
number of challenges associated with IoT forensics and investigations as discussed in this presentation.
We also identify a number of opportunities, which hopefully will help to shape future research agenda
on IoT forensics. For example, we posit the importance of having a digital forensic black-box,
conceptually similar to the cockpit voice recorder (also known as a flight recorder) on aircrafts, to
facilitate digital investigations.
Short-Bio: Kim-Kwang Raymond Choo received the Ph.D. in Information Security in 2006 from
Queensland University of Technology, Australia, and currently holds the Cloud Technology Endowed
Professorship at The University of Texas at San Antonio (UTSA), U.S. He has the opportunity to apply
his research knowledge and provide expert opinion on policy developments. For example recently in
2020, he was engaged as an external paid expert to provide expert advice to a company on U.S.
Department of Energy SBIR/STTR Phase I proposal, and to provide expert insights in writings to
inform North Atlantic Treaty Organization (NATO) Allied Command Transformation (ACT)
Innovation Hub’s Warfighting 2040 report. In 2015 he and his team won the Digital Forensics
Research Challenge organized by Germany's University of Erlangen-Nuremberg. He is the recipient
of the 2019 IEEE Technical Committee on Scalable Computing Award for Excellence in Scalable
Computing (Middle Career Researcher), 2018 UTSA College of Business Col. Jean Piccione and Lt.
Col. Philip Piccione Endowed Research Award for Tenured Faculty, British Computer Society's 2019
Wilkes Award Runner-up, 2019 EURASIP JWCN Best Paper Award, Korea Information Processing
Society's JIPS Survey Paper Award (Gold) 2019, IEEE Blockchain 2019 Outstanding Paper Award,
Inscrypt 2019 Best Student Paper Award, IEEE TrustCom 2018 Best Paper Award, ESORICS 2015
Best Research Paper Award, 2014 Highly Commended Award by the Australia New Zealand Policing
Advisory Agency, Fulbright Scholarship in 2009, 2008 Australia Day Achievement Medallion, and
British Computer Society's Wilkes Award in 2008.
24Invited Speaker 6: Prof. Scott Fowler, Linköping University,
Sweden
Title: Implementing of Industry 4.0 correlated digital technology for
the Construction Industry
Email Addresses: scott.fowler AT liu.se
Abstract: Increasing complexity in onsite construction projects coupled
with the need for higher productivity is leading to increased interest in
the potential use of Industry 4.0 technologies. The Fourth Industrial
Revolution (Industry 4.0) has been reforming the construction industry and bringing it into an
intelligent construction era. Emerging technologies, such as the Digital Twins, Internet of Things, big
data, cloud computing, Machine Learning, UAV, and industrial connectivity have started to become a
significant role in the building life cycle. Considering the various special characteristics of the
construction industry and the high heterogeneity of these technologies, their integration in the
construction industry poses a significant challenge to an industry that has traditionally been rather slow
to adopt the latest technologies and innovations. Despite the challenge, the construction industry knows
it will need to quickly adapt and evolve to embrace new technologies which are challenging since it
involves in-depth investigations and innovations to upgrade and align conventional capabilities.
Construction firms that develop a closer relationship with ICT companies can asset knowledge
consistently increases over the life cycle of the project and it is much easier to spot potential errors or
discrepancies both before and during each stage of the project, significantly reducing the risk of
mistakes and/or incidents, minimizing abortive costs and increasing profitability. The talk will
summarize the Industry 4.0 related technologies involved in the construction industry based on an
analysis of the characteristics of the industry.
Short-Bio: Dr. Scott Fowler received a B.Sc. from Minot State University, the USA in 1998, an M.Sc.
from the University of North Dakota, the USA in 2001, and a Ph.D. from Wayne State University, the
USA in 2006, all degrees in Computer Science. During 2006 – 2010, he was a Research Fellow in the
Adaptive Communications Networks Research Group at Aston University, UK and Sony Ericsson
R&D lab, UK, where the research focused on multiple services in Next Generation Networks (NGNs)
in both wireless and wired, and the project team was composed of multi-disciplinary/multi-institutional
partners from industry and academia. Since 2010, he has been an universitetslektor (Associate
Professor (US)) at Linköping University, Sweden, as a member of Communications and Transport
Systems (CTS) a division at the Department of Science and Technology (ITN) at LiU. Dr. Fowler's
research interests include Quality of Service (QoS), Quality of Experience (QoE), Computer Networks
(wired, wireless), Energy Management, Cloud Computing, Internet of Things, Optimization, Machine
Learning, Network Analytics of Systems, Data Science and Security. Agencies and industries that have
been funding and/or supporting his research are: European Union Framework 7, Excellence Center at
Linköping - Lund in information Technology (ELLIIT), Vinnova, Ericsson, and Ascom. Dr. Fowler is
a Senior Member of IEEE, Senior Member of ACM, and has served on several IEEE
conferences/workshops as TPC to Chair, including Symposium Chair for ICC. He is also a Special
Interest Groups coordinator for IEEE Communications Software (CommSoft) Technical Committee
from 2012-2017 and IEEE Communications Switching and Routing Technical Committee (CSR)
Technical Committee since 2017.
25Session TrustCom 2020 Invited Talks -2
Chair: Prof. Tao Peng, Guangzhou University, China
08:00-12:20, December 29 (Tuesday) Room 7
Invited Speaker 7: Prof. Oana Geman, University of Suceava,
Romania
Title: Epidemiologic Platform for COVID-19 using Integrated Modeling
and GIS
Email Addresses: oana.geman AT usm.ro
Abstract: COVID-19 Pandemic has a very serious impact on the health,
economy by slowing it down. Paradoxically, at the same time, it is
accelerating conversion processes towards a 4.0 Economy and Industry. The
most important immediate priority is to develop a vaccine, diagnostic tools prediction, and
epidemiological solution for modeling and treatments for COVID-19. To avoid duplicated efforts, we
will need to share best practices and clinical test results to develop an effective medical intervention
and epidemiologic model to halt the pandemic. The solution proposed by us is in line with Commission
Recommendation EU 2020/518 from April 2020, on a common set of tools for the use of technology
and data to combat and emerge from the COVID-19 pandemic, in particular as regards mobile
applications and the use of anonymized mobility data. The platform has a mathematical model for the
spread of COVID-19 infection depending on the location of the outbreaks so that the allocation of
resources and the geographical limitation of certain areas can be parameterized according to the
number and location of the real-time identified outbreaks.
Short-Bio: Dr. Oana Geman is Medical Bioengineer and PhD in Electronics and Telecommunication
(Title of Doctoral Thesis: “Contributions To Knowledge-based Systems Using Nonlinear Analysis,
With Medical Applications;” 2005) and a post-doctoral researcher in Computer Science (2012). She is
currently an Associate Professor at the Human and Health Development Department at University of
Suceava, Romania and obtained Habilitation in Electronics and Telecommunication Field. Within the
past five years she published 10 books, has published over 85 articles (62 articles in ISI Web of Science
journals, 15 articles in ISI indexed conference volumes as main author, and 8 papers in Q1and Q2
Journals, with FI over 30), and her various works have been cited over 760 times, and H-index is 15.
She served as Chair of many Internationals Conferences or Organizer, Session Chair and member in
Program or Technical Committees and a Member IEEE. She has been a director or a member in 10
national and international grants. Her current research interests include: non-invasive measurements
of biomedical signals, wireless sensors, signal processing, and processing information by way of
Artificial Intelligence such as nonlinear dynamics analysis, stochastic networks and neuro-fuzzy
methods, classification and prediction, Data-Mining, Deep Learning, Intelligent Systems,
Bioinformatics and Biostatistics and Biomedical Applications. She is a reviewer of many top journals,
including IEEE Transactions, IEEE ACCESS, IOT Journal, Sensors, and Symmetry etc.
26Invited Speaker 8: Prof. Richard Hill, University of Huddersfield,
United Kingdom
Title: Research Challenges for the Industrial Adoption of Cyber-Physical
Systems
Email Addresses: TBD.
Abstract: Interest in the ‘ digitalisation ’ of industry, specifically
manufacturing, is driving the development of innovative technologies that
make the exchange of data, and the inference of knowledge increasingly
accessible. Large organisations are able to rapidly acquire and evaluate Cyber-Physical Systems
technology, enabling new business models to be created. However, significant challenges exist with
regard to the design, operation and evaluation of industrial CPSs in terms of their accuracy, calibration,
robustness and ability to fail safely. Traditionally, such systems would have been designed using
formal approaches, but the scale of CPS adoption is such that there is less reliance on the established
methods of validation and verification. This talk explores some significant challenges for the CPS and
associated software development research communities.
Short-Bio: Professor Richard Hill is Head of the Department of Computer Science and Director of the
Centre for Industrial Analytics (CIndA) at the University of Huddersfield, UK. Richard is an
experienced researcher in the field of distributed systems, cloud computing, and edge analytics, and
has in excess of 200 publications in the areas of Big Data, predictive analytics, the Internet of Things,
Cyber Physical Systems and Industry 4.0. He is a Chartered Engineer (BEng, FIET) and has over 20
years’ experience of defence and automotive manufacturing industries and the UK Public Sector.
27Invited Speaker 9: Prof. Wenbin Jiang, Huazhong University of
Science and Technology, China
Title: Fine-Grained Memory Optimizations for Many-Core Based Deep
Learning Systems
Email Addresses: wenbinjiang AT hust.edu.cn
Abstract: Many-Core systems, such as GPUs, have emerged as the
mainstream for the acceleration of neural network training processes.
However, they usually have limited physical memory, meaning that it is
hard to train large-scale network models. Many methods for memory optimization have been proposed
to decrease the memory consumption of deep learning systems, and to mitigate the increasing scale of
these networks; however, these optimizations come at the cost of obvious drops in time performance.
We propose some memory optimization strategies that realize both better memory efficiency and better
time performance. For example, a fast layer-type-specific method for memory optimization is
presented, based on the new finding that a single memory optimization often shows dramatic
differences in time performance for different types of layers. Moreover, a new memory reuse method
is presented in which greater attention is paid to multi-type intermediate data such as convolutional
workspaces and cuDNN handle data. Experiments show that our proposed methods can significantly
increase the scale of extra-deep network models on a single GPU with lower performance loss. It can
even outperforms the state-of-the-art work of SuperNeurons with about 30% capacity improvement.
Short-Bio: Wenbin Jiang is a Professor at School of Computer Science and Technology of Huazhong
University of Science and Technology (HUST). He received his Ph.D. degree from HUST in 2004. He
was a visiting scholar at Aizu University in 2006, at UCLA (University of California, Los Angeles) in
2014, and at NUS (National University of Singapore) in 2017. His research interests include parallel
and distributed computing, deep learning systems, and computer networking. His papers are published
in prestigious international conferences and journals (PPoPP/NASSDAV/TACO/ TOIT). His research
has been supported by the National Science & Technology Pillar Program of China, National Key
Basic Research Program of China, the National Natural Science Foundation of China, etc. He is also
supported by the talent program of Huazhong Outstanding Scholar. He has got the first prize of
Teaching Achievement of Hubei Province. He is a member of Pervasive Computing Technical
Committee of CCF, and a member of IEEE and ACM.
28You can also read
