2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT 2023)


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Prof. ChuankaiLiu

Beijing Aerospace Control Center, China

Bio:Dr. Liu Chuankai is mainly engaged in scientific research related to remote operation of extraterrestrial celestial surface survey, and has completed the processing of remote sensing image data of "Chang'e-2", "Chang'e-3" and "Chang'e-4 "The research and development of lunar surface visual positioning software and the pre-study of key technologies for manned lunar exploration and subsequent deep space exploration remote operation were completed. He has received two Provincial and Ministerial Science and Technology Progress Awards, published one monograph, published more than 30 papers, more than 20 SCI/EI retrieved papers, applied for 14 national invention patents, and authorized five. He has presided over 2 National Natural Science Foundation of China, 1 National Defense Equipment Pre-Research Foundation, and 1 key project of the unit; as the main backbone, he participated in 1 manned spaceflight pre-research project, 1 National Natural Science Foundation of China project, and 1 key technology research project of Lunar Exploration Phase II measurement and control system.


Prof. Zhaohui Yang

Zhejiang University, China

Bio:Zhaohui Yang is currently a ZJU Young Professor with the Zhejiang Key Laboratory of Information Processing Communication and Networking, College of Information Science and Electronic Engineering, Zhejiang University, and also a Research Scientist with Zhejiang Laboratory. He received the Ph.D. degree from Southeast University, Nanjing, China, in 2018. From 2018 to 2020, he was a Post-Doctoral Research Associate at the Center for Telecommunications Research, Department of Informatics, King’s College London, U.K. From 2020 to 2022, he was a Research Fellow at the Department of Electronic and Electrical Engineering, University College London, U.K. His research interests include federated learning, joint communication, sensing, and computation, and semantic communication. He has received from the IEEE Communication Society two paper awards including the 2023 IEEE Communications Society Marconi Paper Award and 2023 Young Author Best Paper Award. He was the Co-Chair for international workshops with more than ten times including IEEE ICC, IEEE GLOBECOM, IEEE WCNC, IEEE PIMRC, and IEEE INFOCOM. He is an Associate Editor for the IEEE Transactions on Machine Learning in Communications and Networking, IEEE Communications Letters, IET Communications, and EURASIP Journal on Wireless Communications and Networking. He has served as a Guest Editor for several journals including IEEE Journal on Selected Areas in Communications.

Title:Intelligent Integrated Communication and Computation System

Abstract:Traditional wireless communication networks are facing crucial problems such as high power consumption, separate optimization of communication and computataion resources, and lack of joint communication and computing design for large scenarios. Aiming at the opportunities brought by the integration of communication and computation, it is urgent to study and develop new communication theory methods to reduce the performance gap between communication and computation theoretical theory and the overall performance of the network. The main contents of this talk include the theoretical model of the integrated communication and computation system, the design of the data-oriented intelligent integrated communication and computation system design, and the model-oriented intelligent integrated communication and computation system design.


Prof. Xinguo YU

National EngineeringResearch Center for E-Learning, Central China Normal University, China     

Bio:Dr. Yu Xinguo is the dean of CCNU Wollongong Joint Institute and a professor of National Engineering Research Center for E-Learning at Central China Normal University, Wuhan, China. He is a senior member of both IEEE and ACM, and an adjunct professor of University of Wollongong, Australia. He is the chair of Hubei Society of Artificial Intelligence in Research and Education. He received B.Sc. degree in Mathematics from Wuhan University of Technology, M. Eng degree from Huazhong University of Science and Technology, another M. Eng. degree from Nanyang Technological University, Singapore and Ph.D. degree in Computer Science from National University of Singapore. His current research mainly focuses on intelligent educational technology, AI4Research, educational robotics, and machine learning. He has published over 170 research papers. He is Associate Editor and Guest Editors for several international journals. He was keynote speakers, general chairs, or program chairs for more than 30 international conferences.  

Title:Perception Intelligence and Problem-Solving Intelligence of Artificial Intelligence 

Abstract:Artificial Intelligence is growing the problem-solving intelligence at the fast pace based on it has accumulated a great ability in mimicking the functions of human perception organs. Perception Intelligence is the ability of sensing the world such as vision, hearing, sensing. Artificial Intelligence is developing problem-solving intelligence in various approaches, being the ability of mimicking the thinking. For example, GPT brings another wow growth in problem-solving intelligence, which has achieved the promising results in solving some math problems. Some other approaches also achieved great progress in solving some math problems. Artificial Intelligence has achieved great results in AI4Research. 


Assoc. Prof. Zhengdong Zhou 

Nanjing University of Aeronautics and Astronautics, China

Bio:Zhengdong Zhou is currently an associate professor with the State Key Laboratory of Mechanics and Control for Aerospace Structures, & College of Aerospace Engineering, Nanjing University of Aeronautics and Astronautics. He received his Ph.D. degree from Southeast University, Nanjing, China, in 2005 and 2002,respectively. His research interests include advanced X-ray imaging, signal and image processing, machine learning, computer vision and graphics, computer-aided manufacturing, brain-computer interface, virtual/augmented reality, digital twin, intelligent nondestructive testing and analysis, computer-aided diagnosis and treatment, etc. As the first instructor, he has guided the teams to obtain 2 Silver Awards in the 2022 and 2020 China International "Internet +" College Students Innovation and Entrepreneurship Competition, respectively. He has published more than 50 academic papers and applied for/authorized more than 20 patents, including 1 PCT international invention patent. He has been approved for more than 10 software copyrights, and he has contributed to two books:

1. Zhengdong Zhou. Photon Counting Computed Tomography: Clinical Applications, Image Reconstruction and Material Discrimination, Chapter 10, pp 199-217, Publisher, Springer, 2023, Website:Photon Counting Computed Tomography: Clinical Applications, Image Reconstruction and Material Discrimination | SpringerLink.

2.Zhengdong Zhou. Advanced X-Ray Radiation Detection: Medical Imaging and Industrial Applications, Chapter 10, pp 219-238, Publisher, Springer, 2022, Website:Advanced X-Ray Radiation Detection: | SpringerLink.

Title:Development and evaluation of BCI for operating VR flight simulator based on desktop VR equipment

Abstract:Advancement of brain-computer interface (BCI) has shown its applications in various scenarios, including flight control. Flight simulator is a crucial part for aircraft design or experiment. Desktop virtual reality (VR)-based flight is a perfect choice for overcoming existing problems in head-mounted VR flight simulations, such as dizziness and isolation, which make interaction and sharing very difficult. In this paper, a BCI based on the steady-state visual evoked potential paradigm and a VR flight simulator were developed and integrated. The performance of the developed system was evaluated quantitatively for comparative studies. Experimental results show that the developed system is very convenient and suitable for VR flight simulations. The average operating accuracies with plane and VR visual stimuli are 81.6% and 86.8%, respectively. The VR visual stimuli can improve the average operating accuracy by 5.2% compared with the plane visual stimuli.