Keynote Speaker Ⅰ
Prof. Guoqiang Zhong
Ocean University of China
Biography: Guoqiang Zhong received his PhD degree in Pattern Recognition and Intelligent Systems from Institute of Automation, Chinese Academy of Sciences (CASIA), Beijing, China, in 2011. Between October 2011 and July 2013, he was a Postdoctoral Fellow with the Synchromedia Laboratory for Multimedia Communication in Telepresence, University of Quebec, Montreal, Canada. Between March 2014 and December 2020, he was an associate professor at Department of Computer Science and Technology, Ocean University of China, Qingdao, China. Since January 2021, he has been a full professor at Department of Computer Science and Technology, Ocean University of China. He has published 4 books, 4 book chapters and more than 100 technical papers in the areas of artificial intelligence, pattern recognition, machine learning and computer vision. His research interests include pattern recognition, machine learning and computer vision. He is an associate editor of Cognitive Computation, and has served as Chair/PC member/reviewer for many international conferences and top journals, such as IEEE TNNLS, IEEE TKDE, IEEE TCSVT, Pattern Recognition, Knowledge-Based Systems, Neurocomputing, ACM TKDD, AAAI, AISTATS, ICPR, IJCNN, ICONIP and ICDAR. He has been awarded outstanding reviewer by several journals, such as Pattern Recognition, Knowledge-Based Systems, Neurocomputing and Cognitive Systems Research. He has won the Best Paper Award of BICS2019 and the APNNS Young Researcher Award. He is a senior member of CCF, CAAI and CSIG, member of ACM, IEEE, IAPR and APNNS, professional committee member of CCF-CF, CAAI-PR, CAA-PRMI and CSIG-DIAR, and trustee of Shandong Association of Artificial Intelligence.
Talk Title: Automatic Design of Deep Neural Networks
Abstract: Deep neural networks (DNNs) have been widely used in many applications, such as pattern recognition and computer vision. However, design of DNNs needs expertise to deal with lots of hyperparameters and select a proper structure from many possible configurations. Hence, the architecture design of DNNs is transferring from hand-crafted to automatic methods. In this talk, I will present some novel automatic design methods of DNNs, including DNA Computing Inspired Deep Networks Design, Automatic Design of Deep Networks with Neural Blocks, AutoML for DenseNet Compression, Differentiable Light-Weight Architecture Search, and Generative Neural Architecture Search. These methods comprehensively present the state-of-the-art of the neural architecture search area.
Keynote Speaker Ⅱ
Prof. Huiyu Zhou
University of Leicester
Biography: Prof. Huiyu Zhou received a Bachelor of Engineering degree in Radio Technology from Huazhong University of Science and Technology of China, and a Master of Science degree in Biomedical Engineering from University of Dundee of United Kingdom, respectively. He was awarded a Doctor of Philosophy degree in Computer Vision from Heriot-Watt University, Edinburgh, United Kingdom. Prof. Zhou currently is a Full Professor at School of Computing and Mathematical Sciences, University of Leicester, United Kingdom. He has published over 400 peer-reviewed papers in the field. He was the recipient of "CVIU 2012 Most Cited Paper Award", “MIUA 2020 Best Paper Award”, “ICPRAM 2016 Best Paper Award” and was nominated for “ICPRAM 2017 Best Student Paper Award” and "MBEC 2006 Nightingale Prize". Dr. Zhou serves as the Editor-in-Chief of Recent Advances in Electrical & Electronic Engineering and Associate Editor of IEEE Transaction on Human-Machine Systems, IEEE Journal of Biomedical and Health Informatics, Pattern Recognition, PeerJ Computer Science, Security and Safety, Scientific Reports, Machine Intelligence Research, International Journal of Image and Graphics and IEEE Access, and Area Chair of IJCAI, ICRA and BMVC. He is one of the Technical Committee of IEEE Cognitive and Development Systems, Information Assurance & Intelligent Multimedia-Mobile Communication in IEEE SMC Society, Robotics Task Force and Biometrics Task Force of the Intelligent Systems Applications Technical Committee, IEEE Computational Intelligence Society. He has given over 100 invited talks at international conferences, industry and universities, and has served as a chair for 70 international conferences and workshops. His research work has been or is being supported by UK EPSRC, AHRC, ESRC, STFC, MRC, EU, Royal Society, Leverhulme Trust, Puffin Trust, Alzheimer’s Research UK, Invest NI and industry.
Talk Title: Transform image understanding with artificial intelligence
Abstract: There are many questions to answer in image interpretation and understanding. Uncertainty in image analysis needs strong and powerful modelling tools to describe the objects in the images. Artificial intelligence (AI) plays a very important role in the design of a robust tool for image representation. Using some examples from his own research work on uncertainty analysis, he will explore how AI can stimulate new concepts or development of dealing with complicated problems and lead to novel adventures through these applications.
Keynote Speaker Ⅲ
Prof. Dinesh Manocha
A Fellow of AAAI, AAAS, ACM, IEEE
University of Maryland at College Park
Biography: Dinesh Manocha is a Distinguished University Professor of the University of Maryland, where he is the Paul Chrisman Iribe Professor of Computer Science and Professor of Electrical and Computer Engineering. He is also the Phi Delta Theta/Matthew Mason Distinguished Professor Emeritus of Computer Science at the University of North Carolina at Chapel Hill. Manocha’s research focuses on AI and robotics, computer graphics, augmented/virtual reality, and scientific computing. He co-leads a major research group UMD GAMMA with more than 35 members on geometric and simulation algorithms with applications to computer graphics, robotics and virtual environments. His group has won 17 best paper awards at leading conferences and developed a number of software technologies that are licensed to more than 60 commercial vendors. A Fellow of AAAI, AAAS, ACM, IEEE and Sloan Foundation, Manocha is a member of ACM SIGGRAPH Academy Class, and Bézier Award recipient from Solid Modeling Association. He received the Distinguished Alumni Award from IIT Delhi and the Distinguished Career in Computer Science Award from Washington Academy of Sciences. He was also the co-founder of Impulsonic, a developer of physics-based audio simulation technologies, which was acquired by Valve Inc in November 2016.
Talk Title: Designing Digital Humans that Look, Move, Express, and Feel Like Us!
Abstract:The creation of intelligent virtual agents (IVAs)or digital humans is vital for many virtual and augmented reality systems. As the world increasingly uses digital and virtual platforms for every day communication and interactions, there is a heightened need to create human-like virtual avatars and agents endowed with social and emotional intelligence. Interactions between humans and virtual agents are being used in different areas including, VR, games and story-telling, computer-aided design, social robotics, and healthcare. Designing and building intelligent agents that can communicate and connect with people is necessary but not sufficient. Researchers must also consider how these IVAs will inspire trust and desire among humans. Knowing the perceived affective states and social-psychological constructs (such as behavior, emotions, psychology, motivations, and beliefs) of humans in such scenarios allows the agents to make more informed decisions and navigate and interact in a socially intelligent manner.
In this talk, I will give an overview of our recent work on simulating intelligent, interactive, and immersive human-like agents who can also learn, understand and be sentient to the world around the musing a combination of emotive gestures, gaits, clothing, and expressions. Designing and building intelligent agents that can communicate and connect with people is necessary but not sufficient. Our works build on recent developments in computer graphics, vision, physics-based simulation along with research in social-psychology (such as behavior, emotions, psychology, motivations, and beliefs). I will demonstrate their applications to AR/VR, games, virtual try-on, and robotics.
ECCSIT Past Speaker
Prof. Dr. phil. nat. Rolf Drechsler
University of Bremen/DFKI, Germany
德国不来梅大学