Keynote Speaker


Prof. Juyang Weng, IEEE Life Fellow
Brain-Mind Institute and GENISAMA, USA

Biography: Prof. Juyang Weng received the BS degree from Fudan University, in 1982, M. Sc. and PhD degrees from the University of Illinois at Urbana-Champaign, in 1985 and 1989, respectively, all in computer science. He is a former faculty member of Department of Computer Science and Engineering, faculty member of the Cognitive Science Program, and faculty member of the Neuroscience Program at Michigan State University, East Lansing.  He was a visiting professor at the Computer Science School of Fudan University, Nov. 2003 - March 2014, and did sabbatical research at MIT, at Media Lab Fall 1999 – Spring 2000; and at Department of Brain and Cognitive Science Fall 2006-Spring 2007 and taught BCS9.915/EECS6.887 Computational Cognitive and Neural Development during Spring 2007. Since the work of Cresceptron (ICCV 1993) the first deep learning neural networks for 3D world without post-selection misconduct, he expanded his research interests in biologically inspired systems to developmental learning, including perception, cognition, behaviors, motivation, machine thinking, and conscious learning models.  He has published over 300 research articles on related subjects, including task muddiness, intelligence metrics, brain-mind architectures, emergent Turing machines, autonomous programing for general purposes (APFGP), Post-Selection flaws in “deep learning”, vision, audition, touch, attention, detection, recognition, autonomous navigation, and natural language understanding. He published with T. S. Huang and N. Ahuja a research monograph titled Motion and Structure from Image Sequences. He authored a book titled Natural and Artificial Intelligence: Computational Introduction to Computational Brain-Mind. Dr. Weng is an Editor-in-Chief of the International Journal of Humanoid Robotics, the Editor-in-Chief of the Brain-Mind Magazine, and an associate editor of the IEEE Transactions on Autonomous Mental Development (now Cognitive and Developmental Systems).  With others’ support, he initiated the series of International Conference on Development and Learning (ICDL), the IEEE Transactions on Autonomous Mental Development, the Brain-Mind Institute, and the startup GENISAMA LLC. He was an associate editor of the IEEE Transactions on Pattern Recognition and Machine Intelligence and the IEEE Transactions on Image Processing.

Title of Speech: Training and Test Protocols for Conscious Learning Robots
This is a theoretical talk. The algorithm for conscious learning has been recently published (Weng AIEE 2022). Developmental scales for human children are well developed. Such scales need to be adapted to testing conscious learning robots. Without such adaptations, future conscious robots lack a standard, even if the theory and algorithm for conscious learning are implemented and refined in the future. This talk discusses such an adaptation, but does not include actual experimental results. It first proposes that an open skull will not allow a conscious brain because the open skull allows a conscious homunculus (human) who takes over the job of consciousness. That is why the currently popular “open skull” machine learning protocols will not produce conscious robots. Then, the talk borrows some of the milestones from human mental development measured in terms of  human mental ages. The author hopes that independent laboratories will conduct tests using the milestones suggested here, so as to see whether the new protocol is suited for measuring robotic consciousness. Due to space limitations, this talk does not explain conscious learning. The reader should first read (Weng AIEE 2022) before attending this talk.  For four aspects of transfer across milestones, the reader should read J. Weng, Natural and Artificial Intelligence, 2nd edition, BMI Press, 2019, especially, Sec. 10.3.


Prof. Youfu Li, IEEE Fellow
City University of Hong Kong

Biography: You-Fu Li received the PhD degree in robotics from the Department of Engineering Science, University of Oxford in 1993. From 1993 to 1995 he was a research staff in the Department of Computer Science at the University of Wales, Aberystwyth, UK. He joined City University of Hong Kong in 1995 and is currently professor in the Department of Mechanical Engineering. His research interests include robot sensing, robot vision, and visual tracking. In these areas, he has published over 400 papers including over 180 SCI listed journal papers. Dr Li has received many awards in robot sensing and vision including IEEESensors Journal Best Paper Awardby IEEESensors Council, Second Prize of Natural Science Research Award by the Ministry of Education, China. He has served as an Associate Editor for IEEE Transactions on Automation Science and Engineering (T-ASE), Associate Editor and Guest Editor for IEEE  Robotics and Automation Magazine (RAM), and Editor for CEBIEEE International Conference on Robotics and Automation (ICRA). He is a fellow of IEEE.


Prof. Xiaoya Hu
Huazhong University of Science and Technology, China

Biography: Xiaoya Hu received the B.S. degree in power engineering in 1995, the M.S. degree and the Ph.D. degree in control theory and control engineering, respectively in 2002 and 2006 from Huazhong University of Science and Technology, Wuhan, China. She was a visiting scholar of Colorado State University, USA, from 2012 to 2013 and Ryerson University, Canada, from 2019 to 2020. Her research interests include industrial communication networks, industrial artificial intelligence, and security of industrial internet and industrial control systems. She is an IEEE Senior member. Presently, she is a professor with the Laboratory of Industrial Internet and System safety cybersecurity, Huazhong University of Science and Technology. The laboratory has been engaged in the research on safety and security of industrial control systems and has undertaken more than 20 projects of the National Natural Science Foundation, National Key Research and Development Plan and etc., including a National major scientific instrument development project, a key project of the national natural science foundation. Also, the laboratory has participated in developing a number of national standards about safety and security of industrial control systems.


Invited Speaker

Prof. Te Li
Dalian University of Technology, China

Biography: Te Li received the Ph.D degree in 2016 from Shenyang Institute of Automation, Chinese Academy of Sciences. He is a visiting professor of University of Toronto, Canada, from 2023 to 2024. He is an associate professor, doctoral tutor at the School of Mechanical Engineering, Dalian University of Technology, China. He is a senior member of China Mechanical Engineering Society, and IEEE member. His research interests include bionic robotics, special robot, and robotic intelligent manufacturing. He has undertaken more than 15 projects from National Natural Science Fund, National Key R&D Program, State Key Laboratory of Robotics and enterprise contracts. He has received several prizes, including first prize of Dalian Science and Technology Progress Award, third prizes of Liaoning Provincial Natural Science Academic Achievements.

Prof. Haibo Liu
Dalian University of Technology, China

Biography: Haibo Liu, is professor and Ph.D. supervisor of school of mechanical engineering at Dalian University of Technology (DUT), China. He received his B.Eng. and Ph.D. degrees in Mechanical and Electrical Engineering from DLUT, in 2006 and 2012, respectively. He is IEEE member, ASME member, senior member of Chinese Society of Mechanical Engineering. He has served as the Guest Editor of the Frontiers in Mechanical Engineering, Frontiers in Materials and China Measurement & Testing Technology, and deputy secretary general of the SAC/TC22 International Standardization Working Committee.
His main research interests include, Measurement-machining integrated manufacturing, On-machine measurement, Phase-change fixturing based adaptive machining, Industrial-robot aided manufacturing. He has published over 80 peer-reviewed SCI/EI journal papers like International Journal of Machine Tools and Manufacture, International Journal of Mechanical Sciences, and IEEE/ASME Transactions on Mechatronic, and over 100 authorized or pending patents. He holds over 20 major projects, including National Natural Science Foundation of China, the sub-project of the Science Challenge Project, the sub-projects of the National Key Research and Development Program and National Science and Technology Major Project of China, etc. He is the recipient of the 1st prize for Liaoning Science and Technology Progress Award (twice), the 1st prize for Science and Technology Progress Award of China Machinery Industry Federation. He was awarded the Young Changjiang Scholars Program of the Ministry of Education in 2022 and the Liaoning Provincial Outstanding Youth Fund Program in 2020.

Assoc. Prof. Chuxiong Hu
Tsinghua University, China

Biography: Chuxiong Hu (S'09-M'11-SM'17) received his B.S. and Ph.D. degrees in Mechatronic Control Engineering from Zhejiang University, Hangzhou, China, in 2005 and 2010, respectively.
He is currently an Associate Professor (tenured) at Department of Mechanical Engineering, Tsinghua University, Beijing, China. From 2007 to 2008, he was a Visiting Scholar in mechanical engineering with Purdue University, West Lafayette, USA. In 2018, he was a Visiting Scholar in mechanical engineering with University of California, Berkeley, CA, USA. His research interests include precision motion control, high-performance multiaxis contouring control, precision mechatronic systems, intelligent learning, adaptive robust control, neural networks, iterative learning control, and robot.
Prof. Hu was the recipient of the Best Student Paper Finalist at the 2011 American Control Conference, the 2012 Best Mechatronics Paper Award from the ASME Dynamic Systems and Control Division, the 2013 National 100 Excellent Doctoral Dissertations Nomination Award of China, the 2016 Best Paper in Automation Award, the 2018 Best Paper in AI Award from the IEEE International Conference on Information and Automation, 2022 Best Paper in Theory from the IEEE/ASME International Conference on Mechatronic, Embedded Systems and Applications, and the 2023 Best Paper from the IEEE Conference on Industrial Electronics & Application. He is now an Associate Editor for the IEEE Transactions on Industrial Informatics and a Technical Editor for the IEEE/ASME Transactions on Mechatronics.