Keynote speaker I
Prof. Cristina Botella
Clinical Psychology, Universitat Jaume I, Instituto Salud Carlos III, Spain
Title: Using ICT devices for improving the Clinical Psychology field Cristina Botella Ph.D. Universitat Jaume I (Spain)
Abstract: At the moment, it is possible to state that the use of different ICT tools in the field of Clinical Psychology is already well established. Several reviews and meta-analyses have shown that Virtual Reality techniques have proven to be effective in improving psychological treatments. The same can be said about Internet-based CBT treatment programs, numerous meta-analyses have supported their effectiveness. Each of these approaches has a number of advantages and disadvantages; however, they are two completely separate areas of work. This talk will analyze the challenges and opportunities offered by each of these research fields with respect to Clinical Psychology and will argue for the urgent need to converge.
Bio.: Dr. Cristina Botella is a Full Professor of Clinical Psychology at Jaume I University (Spain) since 1992. Her main line of research is the psychopathology and treatment of various psychological disorders, and the use of ICTs to promote health and wellbeing. She has been principal investigator in more than 50 research projects, and she has published over 300 papers in national and international journals. Prof. Botella is funder and director of the Psychology and Technology Laboratory, LabPsiTec, (www.labpsitec.es) which is pioneering the worldwide adaptation of various applications based on ICTs including treatment of various psychological disorders using Virtual Reality, Augmented Reality and the Internet. Dr. Botella is part of the Editorial Board of more than 20 scientific journals and serves as a referee for more than 40 international scientific organizations.
Keynote Speaker II
Prof. Ian Robert McAndrew
Capitol Technology University, Maryland, USA
Speech Title: The role of Artificial Intelligence and Quantum Computing is Vision Systems for Unmanned Vehicles in Hostile Conditions
Abstract: vision systems are developing rapidly and have added greatly to many applications. Drones (unmanned vehicles) are changing their role in military applications and this research discusses how and why they need changing to offer real applications needed for drones. In particular how swarm drones need additional support for vision systems to be robust.
Bio: Ph.D. in Mechanical Engineering; M.Sc. in Manufacturing MA in Education; Pg.D. in Education Training; B.A. (Hons) in Mechanical Engineering; B.A. in Production Engineering A Fellow of the Royal Aeronautical Society and a Member of the Institute of Electrical Engineers. Dr. McAndrew spent 12 years in the industry as a designer before entering academia. He has over 25 years of teaching experience in the UK, Europe, Middle East and Far East. He has supervised many PhD students and published extensively for over 20 years. He is the author of several books and Editor of several international Journals. Currently, he is a full professor at Capitol Technology University. His research interests are in Aerodynamics and cybersecurity of aviation systems, which he has published 60 peer-reviewed journals and conferences. He has presented at many Conferences and believes these are critical research meetings for those that are new to research and the experienced to mentor the next generation.
Keynote Speaker III
Prof. ZHANG, Dapeng David, Presidential Chair Professor
Chinese Univ Hong Kong (SZ); Emeritus Prof., Hong Kong Polytech University China
Title: Palmprint Authentication: Research and Development
Abstract:
Automatic personal authentication using biometrics information is becoming more essential in applications of public security, access control, forensics, banking, etc. Many kinds of biometrics authentication techniques have been developed based on different characteristics. This presentation will introduce our research related to palmprint authentication, including 2D/3D and multispectral palmprint systems. Some new developments, such as touch/touchless palmprint systems, and their applications are also explored. Various experiments could be given to illustrate the effectiveness of palmprint authentication.
Bio.:
David Zhang graduated in Computer Science from Peking University. He received his MSc in 1982 and his PhD in 1985 in both Computer Science from the Harbin Institute of Technology (HIT), respectively. From 1986 to 1988 he was a Postdoctoral Fellow at Tsinghua University and then an Associate Professor at the Academia Sinica, Beijing. In 1994 he received his second PhD in Electrical and Computer Engineering from the University of Waterloo, Ontario, Canada. He has been a Chair Professor at the Hong Kong Polytechnic University where he is the Founding Director of Biometrics Research Centre (UGC/CRC) supported by the Hong Kong SAR Government since 2005. Currently he is Presidential Chair Professor in Chinese University of Hong Kong (Shenzhen). He is both Founder and Editor-in-Chief, International Journal of Image & Graphics (IJIG) and Springer International Series on Biometrics (KISB); and Organizer, the first International Conference on Biometrics Authentication (ICBA). Over past 30 years, he have been working on pattern recognition, image processing and biometrics, where many research results have been awarded and some created directions, including medical biometrics and computerized TCM, are famous in the world. So far, he has published over 20 monographs, 400 international journal papers and 40 patents from USA/Japan/HK/China. He has been continuously listed as a Highly Cited Researchers in Engineering by Clarivate Analytics during 2014-2020. He is also ranked about 80 with H-Index 116 at Top 1,000 Scientists for international Computer Science and Electronics. Professor Zhang has been selected as a Fellow of the Royal Society of Canada in 2020. He also is a Croucher Senior Research Fellow, Distinguished Speaker of the IEEE Computer Society, and an IEEE Life Fellow and an IAPR Fellow.
Keynote Speaker Ⅳ
Prof. Zhihan Lv
Qingdao University, China
Title: Towards Virtual Reality
Abstract:
Virtual reality technology is a computer simulation system that can create and experience a virtual world. It uses a computer to generate a simulation environment that immerses users into the environment. Virtual reality technology is the use of real-life data, electronic signals generated by computer technology, combined with various output devices to make it into a phenomenon that people can feel, these phenomena can be real objects in reality It can also be a substance that we can't see with the naked eye, which is expressed through a three-dimensional model. Because these phenomena are not what we can see directly, but the real world simulated by computer technology, it is called virtual reality. In my research, I studied the application of virtual reality in geographic informatics, molecular biology, and neurorehabilitation, and developed some augmented reality interaction technologies. Finally, I introduced the research of Hash geocoding and blockchain in virtual reality geographic information system.
Bio.:
Dr. Zhihan Lv, ACM Distinguished Speaker, IEEE Senior Member and British Computer Society Fellow. He received joint PhD. degree from Ocean University of China and the University of Paris. He has served as a research engineer at the French National Research Center in France, a postdoctoral fellow at Umeå University in Sweden, a experienced researcher at the FIVAN Foundation in Spain, a postdoctoral fellow at University College London in UK, a postdoctor at the University of Barcelona in Spain, and an research assistant professor at the Chinese Academy of Sciences. He was a Marie Curie Fellow in European Union's Seventh Framework Program LANPERCEPT. He has published more than 270 high-quality papers in virtual reality, Internet of Things, big data and other fields, in which 43 papers were published in the top journal IEEE/ACM Transactions.
Research in recent years has been published in IEEE TII, IEEE TITS, IEEE TFS, IEEE TSMC, IEEE TETC, IEEE TBD, IEEE JSAC, IEEE JSTSP, IEEE IOTJ, IEEE COMMAG, IEEE Network, ACM TOMM, ACM TOIT, ACM TIST, and conferences such as ACM MM, ACM CHI, ACM Siggraph Asia, ICCV, IEEE Virtual Reality. Published more than ten highly cited papers and one hot paper.
He won the "Best idea" award in the UMINOVA academic business competition in Sweden, the grand prize in the "Challenge Cup" entrepreneurial plan competition in China, the "Chunhui Cup" award in the innovation and entrepreneurship competition for Chinese overseas students, the third prize in the China "Challenge Cup" extracurricular academic technology competition, the third prize of Shandong Province Graduate Student Outstanding Scientific and Technological Innovation Achievement Award, the third prize of Shandong Province Higher Education Institution Humanities and Social Science Outstanding Achievement Award, and the 2020 Qingdao University Outstanding Graduate Supervisor Award.
Dr. Zhihan Lv served as editorial board member of journals, including Plos one, IEEE Access, IET Image Processing, KSII Transactions on Internet and Information Systems, and Neurocomputing. Served as the Lead Guest Editor of several well-known journals, including IEEE Transactions on Industrial Informatics, IEEE Network, IEEE Transactions on Intelligent Transportation Systems, IEEE Sensors, IEEE Consumer Electronics Magazine, IEEE Communications Standards Magazine, IEEE Journal of Biomedical and Health Informatics, Future Generation Computer Systems, Neurocomputing and Applications, Neurocomputing, etc., organized more than 40 special issues. Served as the vice chair and TPC members of ACM IUI 2015-2021, IEEE INFOCOM 2020 workshop, ACM MobiCom 2020 workshop, IEEE VTC2017-Fall, IEEE CHASE Workshop 2016, 2017, IEEE/CIC WIN Workshop 2016, ISAIR2021. In 2018, he won the IEEE Access Outstanding Associate Editor Award.
Dr. Zhihan Lv has reviewed more than 260 manuscripts for high-level journals and conferences, including IEEE TMM, ACM TOMM, IEEE TII, IEEE TBD, IEEE TMC, IEEE TLT, IEEE TETC, IEEE TC, IEEE TVCG, IEEE TITS, IEEE/ACM TCBB, ACM TOIT, IEEE Network, IEEE MultiMedia, IEEE IOTJ and other journals and ACM MUM, ACM CHI, ACM DIS, IEEE EuroVis, ACM UIST, ACM MobileHCI, ACM CHIPLAY, ACM CSCW, ACM SUI, ACM ITS, IEEE VAST, IEEE VR, ACM IUI, IEEE 3DUI, ACM TVX, ACM Creativity & Cognition, ACM EICS, ACM IDC, IEEE ICSIPA, GI, IEEE ITSC, IEEE Sensors, ACM ACI, ACM VRST, ACM ISS, ACM HRI and other conferences. He is the reviewer of the Swiss National Natural Science Foundation.
Keynote SpeakerⅤ
James M. Heller
Title: IP Protection Strategies for AI-based Software Innovations: A European, U.S. Comparison
Abstract:
Artificial intelligence (AI) has entered most of the business sectors of world economies, driving companies’ revenues, and contributing to the digital capabilities crucial to compete. Consequently, companies are increasingly considering how to protect the value of the investments in specific technologies at the heart of AI. Still, there is much controversy surrounding the national and international IP protection of algorithms and frameworks. Although copyright and patents are the most common intellectual property mechanisms applied to the legal protection of algorithms, trade secrets, and database protection should not be underestimated. The article relies on qualitative research methods such as comparative legal research and case law analysis. From a comparative legal standpoint, the article seeks to provide a basic legal comparison between European and U.S. approaches to the IP protection of AI. Evidence from this suggests that the best approach to AI-based software protection is the adoption of a mixed-method IP strategy, consolidating and benefiting from different mechanisms of IP protection. Thus, the article takes a new look at the software IP strategy debate by exploring significant and evolving issues of the IP protection of AI-based software inventions and discussing strategies of patent, copyright, trade secret, and database IP protection.
Bio.:
James M Heller is a lecturer and researcher at the State University of New York (Empire State College), and partner of Wood & Lee, LLP. His law practice focuses on intellectual property, technology and IT, media and telecommunications law with extensive experience in innovation industries. He currently prefers cross-disciplinary and international comparative research.
James studied at 11th-ranked-globally University of Sydney Law School, where he won the Allens Arthur Robinson award and Pennsylvania State University (Political Science and English Rhetoric). In addition to his native English, James speaks Spanish and is learning Mandarin.
Invited speaker
Dr. Debnath Bhattacharyya, Full-Professor,
Department of Computer Science and Engineering,
Koneru Lakshmaiah Education Foundation,
Vaddeswaram, Guntur-522502, India
Title: Unsupervised learning
Abstract:
Unsupervised learning is previously unidentified patterns in a data set without labels and with a minimum or no of human supervision. Compare to supervised learning that usually makes use of labeled data, unsupervised learning, also known as probability modeling. It can be used in ML and AI as well. Clustering and Cluster analysis are the prime components of Unsupervised Learning. Here we consider and discuss available clustering algorithms from nearest neighbor to density based clustering.
Unsupervised means - Absence of teacher, exploratory analysis and clustering. Cluster is a collection of data objects, Similar to one another within the same cluster and Dissimilar to the objects in other clusters. Cluster analysis means grouping a set of data objects into clusters. Clustering is unsupervised classification where no predefined classes are available.
Typical applications of clustering / unsupervised learning can be Pattern Recognition; Spatial Data Analysis like create thematic maps in GIS by clustering feature spaces detect spatial clusters and explains them in spatial data mining; Image Processing; Economic Science (especially market research); WWW; Document classification; Cluster Weblog data to discover groups of similar access patterns.
Bio.:
Prof. (Dr.) Debnath Bhattacharyya is associated as the Professor with Computer Science and Engineering Department, K.L. University, Andhra Pradesh, India. Dr. Bhattacharyya is presently an Invited International Professor of Lincolon University College, KL, Malaysia. He is also working as a Visiting Professor, MPCTM, Gwalior India, in the Department of Computer Science and Engineering. He is the former Foreign Professor, Department of Multimedia Engineering, Hannam University, South Korea.
Dr. Bhattacharyya received his Ph.D. (Tech., Computer Science and Engineering) from the University of Calcutta, Kolkata. He received his M.Tech (Computer Science and Engineering) from West Bengal University of Technology, Kolkata, India.
Dr. Bhattacharyya is the Member of ACM, ACM SIGKDD, IEEE, Life Member of CSI, India, Senior Member of IACSIT, Singapore and Senior Member of IAENG, Hong Kong.
He is the Editor of Many International Journals (indexed by Scopus, SCI, and Web of Science). He visited various Foreign Countries for presenting lectures, address/working as International Professor in Universities.
He Published 174 Scopus Indexed Papers and 128 SCI / Web of Science Papers.
His Research interests include Security Engineering, Pattern Recognition, Biometric Authentication, Multimodal Biometric Authentication, Data Mining and Image Processing. In addition, he is serving as a reviewer of various International Journals of Springer, Elsevier, IEEE, etc., and International Conferences. He published 200+ Research Papers in International Journals and Conferences. He also published 6 text books for Computer Science and Engineering, so far.