Prof.
Xindong Wu
IEEE/AAAS Fellow
Director of the Key
Laboratory of Knowledge Engineering with Big Data (Hefei
University of Technology), Ministry of Education, China
Speech Title: CHACE-KO: A Connected, Hybrid,
Accommodating, Contained, and Evolving Knowledge-Ocean
Abstract: A knowledge ocean aims for problem solving with multi-model knowledge
at all times and all over the world, synergizing knowledge graphs with large
language models, and performing bidirectional reasoning driven by both data and
knowledge. We have constructed such a large knowledge ocean, entitled CHACE-KO
(a Connected, Hybrid, Accommodating, Contained, and Evolving Knowledge-Ocean)
that contains the largest knowledge graph in the world with 490 million entities
and 2.257 billion relations (https://ko.zhonghuapu.com/EN). In this talk, we
will present each of the CHACE dimensions of the CHACE-KO design, and illustrate
how "big", "dynamic" and "sparkling" applications are implemented by these CHACE
characteristics and the HAO intelligence that integrates human intelligence,
artificial intelligence and organizational intelligence.
Biography:
Xindong Wu is Director and Professor of the Key
Laboratory of Knowledge Engineering with Big Data
(the Ministry of Education of China), Hefei
University of Technology, China. He is also a Senior
Research Scientist at Zhejiang Lab, China. His
research interests include big data analytics, data
mining and knowledge engineering. He received his
Bachelor's and Master's degrees in Computer Science
from the Hefei University of Technology, China, and
his Ph.D. degree in Artificial Intelligence from the
University of Edinburgh, Britain. He is a Foreign
Member of the Russian Academy of Engineering, and a
Fellow of IEEE and the AAAS (American Association
for the Advancement of Science).
Dr. Wu is the Steering Committee Chair of the IEEE
International Conference on Data Mining (ICDM), and
the Editor in-Chief of Knowledge and Information
Systems (KAIS, by Springer). He was the
Editor-in-Chief of the IEEE Transactions on
Knowledge and Data Engineering (TKDE) between 2005
and 2008 and Co-Editor-in-Chief of the ACM
Transactions on Knowledge Discovery from Data
Engineering between 2017 and 2020. He served as a
program committee chair/co-chair for ICDM 2003 (the
3rd IEEE International Conference on Data Mining),
KDD 2007 (the 13th ACM SIGKDD International
Conference on Knowledge Discovery and Data Mining),
CIKM 2010 (the 19th ACM Conference on Information
and Knowledge Management), and ICBK 2017 (the 8th
IEEE International Conference on Big Knowledge). One
of his completed projects is Knowledge Engineering
With Big Data (BigKE), which was a 54-month,
45-million RMB, 15-institution national grand
project, as described in detail at
https://ieeexplore.ieee.org/abstract/document/7948800
.
Prof.
Michele Della Ventura
Professor. Dr., Music Academy 'Studio Musica', Italy
Biography:
Michele Della Ventura, professor of Music
Technology, is a learning expert, researcher
and instructional designer. His research
interests include correlation between music
and mathematics (with a particular emphasis
on artificial intelligence research in the
field of computer-aided analysis of tonal
music), intelligent systems and the
effective use of digital technologies for
learning in schools. He continues to
research into technology to support dyslexic
learners, with particular emphasis on the
pedagogy underlying the use of social media
and Web 2.0 technologies.
He is the author of several articles
presented at many conferences and published
in international science magazines and high
school textbooks (also featured at the
International Book Salon of Turin in 2012
and 2018).
He proofreads articles and is a member of
scientific committees in International
Conferences and International Journals.
He was invited as keynote speaker to
International Conferences in Italy, Austria,
Canada, China, Czech Republic, France,
Germany, Hong Kong, Hungary, Ireland, Japan,
Norway, Poland, Portugal, Romania,
Singapore, Spain, UK, USA (Baltimora,
Boston, Las Vegas, New York, Washington).
He teaches Music technologies, Informatics
and Music Informatics in University courses.
Prof. Hui Yu
Professor. Dr., University of Glasgow, the United Kingdom
Speech Title: Facial Sensing for Human-Machine Interaction
Abstract:
With the increasing demand of machine intelligence
across a wide range of application scenarios,
human-machine interaction (HMI) emerges as another
essential communication, whereby
facial-expression-aware is one of the principal
features for natural interaction. The principal
branch of my research has been driven by the
understanding of mechanism of emotion and facial
expression combining knowledge of creative
technologies with multiple disciplines, such as
visual and cognitive computing, as well as machine
learning. Particularly, biometric data precisely
record the facial muscle activity or brain activity
closely related to facial movements and the internal
emotional states. These multiple sensing channels
would help provide an insight into the emotion and
perception of facial expression, to develop widely
accessible HMI solutions able to track facial
motions and recognise affective states in a highly
efficient and precise manner. This talk will discuss
the development of visual capture of facial
expression processing. This talk will also discuss
research about the development and challenges of
image/video clustering as well as our recent
development on this topic.
Biography: Hui Yu is a Professor with the University of Glasgow. He leads the Visual and Cognitive Computing Group at the university. His research interests lie in visual and cognitive computing as well as machine learning with applications to 4D facial expression modelling and analysis, human-machine interaction, intelligent vehicle, and video analysis. Professor Yu’s research work has led to several awards and successful collaboration with worldwide institutions and industries. He is the Associate Vice President of IEEE Systems, Man, and Cybernetics Society and a Scientific Advisor for some high-tech companies in the UK. Prof. Yu is the PI on grants from a diverse range of funding sources including the EPSRC, EU FP7, RAEng, Royal Society, Innovate UK and Industry. He has been awarded Industrial Fellowship by the Royal Academy of Engineering. He serves as an Associated Editor for IEEE Transactions on Human-Machine Systems, IEEE Transactions on Computational Social Systems, IEEE Transactions on Intelligent Vehicles and IEEE/CAA Journal of Automatica Sinica.
Dr. Adela Lau
The University of Hong Kong, China
Speech Title: Using AI and Data Science in Metaverse for Virtual Entrepreneurship
Abstract: To improve the competitiveness of the business, metaverse is a novel method for virtual business to advertise or sell the products in a 3D virtual store. It allows user with immerse experience for online shopping with the use of the metaverse tools such as VR goggle or hand gloves. However, the existing researches in metaverse development did not consider how to add AI and data science on the top of the meta layer to crease business intelligence and insights. Therefore, this talk will present the future technologies of metaverse development and how they can be integrated into existing metaverse platform to create collective intelligence.
Biography: Dr Adela Lau is a Lecturer of Data Science at Department of Statistics and Actuarial Science of University of Hong Kong. Dr Lau published over 40 journal and conference papers and funded over 30 research and industrial collaboration and consultancy projects in the area of machine learning, business intelligence, text analysis, network analysis, social media and big data analytics, AI and Mixed Reality in metaverse, intelligence applications, risk management, information system adoption, ontology/taxonomy building, business process re-engineering, portal design, knowledge management, e-learning, public/community health studies, healthcare systems and nursing clinical quality control & assessment. She gained several awards including NANDA Foundation Research Grant Award (USA), Faculty Merit Award in Services (HK), and Inaugural Teaching and Learning Showcase Award (HK). She was the former director of Center for Business Development at Madonna University in USA, and the co-director of the Center for Integrative Digital Health at Hong Kong Polytechnic University (PolyU) and leaded the IT team for healthcare product innovation. Dr Lau was an active committee member of Knowledge Management Research Center at PolyU and Data Science Center at Hong Kong University of Science and Technology (HKUST), in which she initiated and developed industrial applied-research consultancy projects. She was also the UG coordinator of the Risk Management and Business Intelligence Program at HKUST, and was responsible to lead, execute, and coordinate the program works including curriculum design, enrichment programs, and administration across three schools of business, science, and engineering.