Prof. Victor Chang
Teesside University, UK
Keynote topic: The Unique AI-based Data Science and Analytics for research: Summary, demonstrations and contributions
This keynote presents the latest research outputs for AI-based Data Science and Analytics services and methods that can be adopted and analyzed in multiple disciplines including healthcare, finance, data center computing, social networks, and weather studies. In particular, research outputs from three different disciplines will be at the center of attention. First, the health informatics service allows us to understand more about tumors, genes and proteins, as well as interpret part of how our human body can function. This includes the study of malignant tumors and genes that are prone to certain types of cancers. The latest research on coronavirus analysis and predictive modeling can be explained. Second, it is financial deep learning, risk modeling and financial computation and algorithms. We can identify the correlation between the current and the past stock movement from the best matching scenarios. Various techniques and results will be discussed in detail. Third, weather analysis of four countries: Kazakhstan, South Korea, the UK and Algeria with different dates and times between August and November 2020 will be presented. Results can show the combined AI and Data Science can compute and visualize weather studies, particularly focusing on temperature distributions in these four countries. Other examples also include social networks and other latest research will be presented. The summary of research contributions in multiple disciplines can justify the significance of AI-based Data Science and Analytics services, demonstrations and contributions.
Prof. Victor Chang is currently a Full Professor of Data Science and Information Systems at the School of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough, UK, since September 2019. He leads Artificial Intelligence and Information Systems Research Groups at Teesside University. He was a Senior Associate Professor, Director of Ph.D. (June 2016- May 2018), Director of MRes (Sep 2017 - Feb 2019) and Interim Director of BSc IMIS (Aug 2018- Feb 2019) at International Business School Suzhou (IBSS), Xi’an Jiaotong-Liverpool University (XJTLU), Suzhou, China, between June 2016 and August 2019. He was also a very active and contributing key member at Research Institute of Big Data Analytics (RIBDA), XJTLU. He was an Honorary Associate Professor at University of Liverpool. Previously he was a Senior Lecturer at Leeds Beckett University, UK, between Sep 2012 and May 2016. Within 4 years, he completed Ph.D. (CS, Southampton) and PGCert (Higher Education, Fellow, Greenwich) while working for several projects at the same time. Before becoming an academic, he has achieved 97% on average in 27 IT certifications. He won a European Award on Cloud Migration in 2011, IEEE Outstanding Service Award in 2015, best papers in 2012, 2015 and 2018, the 2016 European special award, Outstanding Young Scientist 2017 and INSTICC Service Award 2017-2020. He is a visiting scholar/Ph.D. examiner at several universities, an Editor-in-Chief of IJOCI & OJBD journals, former Editor of FGCS, Associate Editor of TII, Editorial Member of Information Fusion, founding chair of two international workshops and founding Conference Chair of IoTBDS and COMPLEXIS since Year 2016. He is the founding Conference Chair for FEMIB since Year 2019 and IIoTBDSC since Year 2020. He published 3 books as sole authors and the editor of 2 books on Cloud Computing and related technologies. He gave 22 keynotes at international conferences. Hi is ranked the joint first in Data Analytics between 2010 and 2019 and is among top 2% scientists in the world for 2017, 2019 and entire career. He is widely regarded as one of the most active and influential young scientist and expert in IoT/Data Science/Cloud/security/AI/IS, as he has experience to develop 10 different services for multiple disciplines.
Prof. Wenfeng Wang
Shanghai Institute of Technology, China
Speech Title: Research on occluded face recognition model in 3D visualization scene
Occluded face recognition in 3D visualization scene is based on occluded face recognition and 3D visualization scene as tool face recognition technology. By fusing the image with face in complex two-dimensional scene with the 3D model of the scene, the face image in 3D visualization scene is obtained and recognized. In this new epidemic, similar occluded face recognition technology has played a huge role in crowd control in public places with a large number of people. This paper first introduces the research significance and background of 3D visualization scene and occlusion face recognition, as well as the research status at home and abroad. Then the experimental platform is introduced, and the program code used in face recognition is explained, and the main libraries used are explained. After that, the algorithm model and formula derivation used in 3D video fusion are explained. Finally, combined with 3D fusion and occlusion face recognition, occlusion face recognition in 3D visualization scene is completed.
A full professor in Shanghai Institute of Technology and the director of Research Institute of Intelligent Engineering and Data Applications, School of Electronic and Electrical Engineering, Shanghai Institute of Technology. An Editorial Member of Scientific reports - a SCI journal published by Nature and a reviewer of many SCI journals,including some top journals - Water Research,Science China-Information Sciences, Science of the Total Environment,Environmental Pollution,IEEE Transactions on Automation Science and Engineering and etc. The leader of a CAS “Light of West China” Program (2014-2018) and a key tallent in Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences (2018-2019).A keynote speaker of 2019 2nd Americas Conference on Medical Imaging.
December 11-13, 2020
December 8, 2020
Notification of Acceptance:
December 11, 2020
Tel: 027-87153536 / +86-18271938662
Organizing Chair: firstname.lastname@example.org