Keynote Speakers
![](/ncaa2021/photos/GuanrongChen.jpg)
Guanrong Chen
City University of Hong Kong
Professor Chen is a Chair Professor at the City University of Hong Kong. He was elected IEEE Fellow in 1997, conferred Honorary Doctor Degrees by the Saint Petersburg State University, Russia in 2011 and by the University of Normandy, France in 2014. He is a Member of the Academy of Europe and a Fellow of The World Academy of Sciences. In the last decade, he has been a Highly Cited Researcher in Engineering according to Clarivate Web of Science.
Keynote Title
Pinning Control and Robust Controllability of Complex Networks --- A Machine Learning Approach
Keynote Abstract
In this talk, we briefly introduce the basic idea and general strategy of pinning control for complex dynamical networks, and study the network controllability. Then, we discuss the robustness of the network controllability against malicious destructive attacks. Finally, we describe a machine learning approach to optimizing the network structure toward strongest controllability robustness.
![](/ncaa2021/photos/Fei-YueWang.png)
Fei-Yue Wang
Chinese Academy of Sciences
Fei-Yue Wang (S'87–M'89–SM'94–F'03) received his Ph.D. degree in computer and systems engineering from the Rensselaer Polytechnic Institute, Troy, NY, USA, in 1990. He joined The University of Arizona in 1990 and became a Professor and the Director of the Robotics and Automation Laboratory and the Program in Advanced Research for Complex Systems. In 1999, he founded the Intelligent Control and Systems Engineering Center at the Institute of Automation, Chinese Academy of Sciences (CAS), Beijing, China, under the support of the Outstanding Chinese Talents Program from the State Planning Council, and in 2002, was appointed as the Director of the Key Laboratory of Complex Systems and Intelligence Science, CAS. In 2011, he became the State Specially Appointed Expert and the Director of the State Key Laboratory for Management and Control of Complex Systems. His current research focuses on methods and applications for parallel intelligence, social computing, and knowledge automation. He is a fellow of INCOSE, IFAC, ASME, and AAAS. In 2007, he received the National Prize in Natural Sciences of China and became an Outstanding Scientist of ACM for his work in intelligent control and social computing. He received the IEEE ITS Outstanding Application and Research Awards in 2009 and 2011, respectively. In 2014, he received the IEEE SMC Society Norbert Wiener Award. Since 1997, he has been serving as the General or Program Chair of over 30 IEEE, INFORMS, IFAC, ACM, and ASME conferences. He was the President of the IEEE ITS Society from 2005 to 2007, the Chinese Association for Science and Technology, USA, in 2005, the American Zhu Kezhen Education Foundation from 2007 to 2008, the Vice President of the ACM China Council from 2010 to 2011, the Vice President and the Secretary General of the Chinese Association of Automation from 2008-2018. He was the Founding Editor-in-Chief (EiC) of the International Journal of Intelligent Control and Systems from 1995 to 2000, the IEEE ITS Magazine from 2006 to 2007, the IEEE/CAA JOURNAL OF AUTOMATICA SINICA from 2014-2017, and the China's Journal of Command and Control from 2015-2020. He was the EiC of the IEEE Intelligent Systems from 2009 to 2012, the IEEE TRANSACTIONS ON Intelligent Transportation Systems from 2009 to 2016, and is the EiC of the IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS since 2017, and the Founding EiC of China's Journal of Intelligent Science and Technology since 2019. Currently, he is the President of CAA's Supervision Council, and Vice President of IEEE Systems, Man, and Cybernetics Society.
Keynote Title
Neural Computing and Logical Computing: Explainable AI or TRUE DAO Intelligence?
Keynote Abstract
![](/ncaa2021/photos/JianLi.png)
Jian Li
Springer Nature Group
Jian Li is an assistant editor at Springer Nature Group. She is responsible for the computer science conference proceedings publications now. Jian Li got her Master Degree in Control Science and Technology from Beijing Institute of Technology and joined the Springer editorial team after graduation in 2012. During the past 9 year, Jian Li has got solid experience in academic publishing, including book, conference proceedings and journal publishing. From 2020, Jian Li is forced on the evaluation work of conference proceedings projects from China and Southeast Asia in Lecture Notes of Computer Science (LNCS) and Communications in Computer and Information Science (CCIS) series.
Keynote Title
Academic book publishing and conference proceedings publishing
Keynote Abstract
This talk presents the importance of academic publishing for scholars. It focuses on introducing the evaluation and publication process of book and conference proceedings in Springer. Meanwhile, the talk will also summary the recent publication model and publication tools, which will help the scholars on the future work.
![](/ncaa2021/photos/HanliWang.png)
Hanli Wang
Tongji University
Hanli Wang received the B.S. and M.S. degrees in Electrical Engineering from Zhejiang University, Hangzhou, China, in 2001 and 2004, respectively, and the Ph.D. degree in Computer Science from City University of Hong Kong, Kowloon, Hong Kong, in 2007. From 2007 to 2008, he was a Research Fellow with the Department of Computer Science, City University of Hong Kong. From 2007 to 2008, he was also a Visiting Scholar with Stanford University, Palo Alto, CA. From 2008 to 2009, he was a Research Engineer with Precoad, Inc., Menlo Park, CA. From 2009 to 2010, he was an Alexander von Humboldt Research Fellow in University of Hagen, Hagen, Germany. Since 2010, he has been a full Professor with the Department of Computer Science and Technology, Tongji University, Shanghai, China. His research interests include multimedia signal processing, computer vision, and machine learning. He has published more than 160 research papers in these research fields. His personal website is at https://mic.tongji.edu.cn.
Keynote Title
Re-expressing Vision: Translating Image and Video into Language
Keynote Abstract
Translating an image or a video automatically into natural language is interesting, promising, but challenging. The task is to summarize the visual content of image or video and re-express it with decent words, suitable grammars, sentence patterns and human habits. Nowadays, the encoding-decoding pipeline is the most commonly used framework to achieve this goal. In particular, the convolutional neural network is used as the encoder to extract semantics of images or videos, while the recurrent neural network is employed as the decoder to generate word sequence. In this talk, the literature on image and video description is firstly reviewed, then the preliminary research advances are introduced, including visual captioning, visual storytelling, visual dense captioning, visual sentiment captioning, and the more complex visual paragraph description.
![](/ncaa2021/photos/Guanghui (Richard) Wang.png)
Guanghui (Richard) Wang
Ryerson University
Dr. Richard Wang is currently an Associate Professor in the Department of Computer Science at Ryerson University. He is also the director of the Computer Vision and Intelligent Systems Laboratory. From 2014 to 2020, he was with the University of Kansas, USA, as an Assistant Professor and then Associate Professor. He has authored one book and published over 140 papers in peer-reviewed journals and conferences. His research interests include computer vision, machine learning, and intelligent systems.
Keynote Title
Vision-Based Perception and Learning for Intelligent Systems
Keynote Abstract
Making computers see and understand the world is one of the most important tasks of intelligent systems. In this talk, we will present some research results on vision-based perception and learning conducted in the Computer Vision Laboratory at Ryerson University. The topics range from classical geometry-based algorithms to convolutional neural networks (CNNs) based visual perceptions, including image classification, object detection, depth estimation, and image-to-image translation.