Professor Shiqiang Zhu is a distinguished PhD advisor and a State Council Special Allowance Expert. He graduated from Zhejiang University with a PhD in Mechatronics Control. He currently is leading Zhejiang Lab as its President, and serves as Vice President and Dean of the Robotics Institute at Zhejiang University. He has been recognized as a distinguished expert by the Zhejiang High-Level Talent Support Program. In addition, he is Vice Chairman of the China Artificial Intelligence Industry Alliance, President of the Zhejiang Robot Association, Deputy Director of the Zhejiang Manufacturing Strategy Advisory Committee, a member of the general expert panel for a national key research and development program on intelligent robotics. With long years of exploration in the field of intelligent science and technology, he has carried out in-depth research in areas such as intelligent home service robots, exoskeleton robots, machine vision, high-performance multi-axis motion controllers, and ocean electronics engineering and intelligent systems, and has achieved a number of significant outcomes.

Hai Jin is a Chair Professor of computer science and engineering at Huazhong University of Science and Technology (HUST) in China, and the Director of HUST-ZJ Lab Joint Research Center for Graph Computing. Jin received his PhD in computer engineering from HUST in 1994. In 1996, he was awarded a German Academic Exchange Service fellowship to visit the Technical University of Chemnitz in Germany. Jin worked at The University of Hong Kong between 1998 and 2000, and as a visiting scholar at the University of Southern California between 1999 and 2000. He was awarded Excellent Youth Award from the National Science Foundation of China in 2001. Jin is a Fellow of IEEE, Fellow of CCF, and a life member of the ACM. He has co-authored more than 20 books and published over 900 research papers. His research interests include computer architecture, parallel and distributed computing, big data processing, data storage, and system security.

Since age 15 or so, the main goal of Professor Jürgen Schmidhuber has been to build a self-improving Artificial Intelligence (AI) smarter than himself, then retire. The media have often called him the “father of modern AI”.  His lab’s Deep Learning Neural Networks based on ideas published in the “Annus Mirabilis” 1990-1991 have revolutionized machine learning. By the mid 2010s, they were on 3 billion devices, and used billions of times per day through users of the world’s most valuable public companies, e.g., for greatly improved (CTC-LSTM-based) speech recognition on all Android phones, greatly improved machine translation through Google Translate and Facebook (over 4 billion LSTM-based translations per day), Apple’s Siri and Quicktype on all iPhones, the answers of Amazon’s Alexa, and numerous other applications. In 2011, his team was the first to win official computer vision contests through deep neural nets, with superhuman performance. In 2012, they had the first deep neural network to win a medical imaging contest (on cancer detection). All of this attracted enormous interest from industry. His research group also established the fields of mathematically rigorous universal AI and recursive self-improvement in meta-learning machines that learn to learn (since 1987). In 1990, he introduced unsupervised adversarial neural networks that fight each other in a minimax game to achieve artificial curiosity (GANs are a special case). In 1991, he introduced very deep learning through unsupervised pre-training, and neural fast weight programmers formally equivalent to what’s now called linear Transformers. His formal theory of creativity & curiosity & fun explains art, science, music, and humor. He also generalized algorithmic information theory and the many-worlds theory of physics, and introduced the concept of Low-Complexity Art, the information age’s extreme form of minimal art. He is recipient of numerous awards, author of over 350 peer-reviewed papers, and Chief Scientist of the company NNAISENSE, which aims at building the first practical general purpose AI. He is a frequent keynote speaker, and advising various governments on AI strategies.

Dr. Yulia Sandamirskaya leads the Applications Research team of the Neuromorphic Computing Lab at Intel. Her team in Munich develops spiking neuronal network based algorithms for neuromorphic hardware to demonstrate the potential of neuromorphic computing in real-world applications. She has 15 years of research experience in the fields of neural dynamics, embodied cognition, and autonomous robotics. She led a research group “Neuromorphic Cognitive Robots” at the Institute of Neuroinformatics of the University of Zurich and ETH Zurich, Switzerland and the “Autonomous learning” group at the Institute for Neural Computation at the Ruhr-University Bochum, Germany. She chaired the European Society for Artificial Cognitive Systems (EUCog) and coordinated a networking project NEUROTECH, shaping and supporting the neuromorphic computing technology community in Europe.

Dr. Yaochu Jin is an Alexander von Humboldt Professor for Artificial Intelligence endowed by the Germany Federal Minister of Education and Research, Faculty of Technology, Bielefeld University, Germany. He is also a Distinguished Chair in Computational Intelligence, Department of Computer Science, University of Surrey, Guildford, U.K. He was a “Finland Distinguished Professor” of University of Jyväskylä, Finland, “Changjiang Distinguished Visiting Professor”, Northeastern University, China, and “Distinguished Visiting Scholar”, University of Technology Sydney, Australia. His main research interests include evolutionary optimization, evolutionary learning, trustworthy machine learning, and evolutionary developmental systems. Prof Jin is presently the Editor-in-Chief of the IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS and the Editor-in-Chief of Complex & Intelligent Systems. He is a Member of Academia Europaea and Fellow of IEEE.

Wei D. Lu is a Professor in the Electrical Engineering and Computer Science department at the University of Michigan. He received B.S. in physics from Tsinghua University, Beijing, China, in 1996, and Ph.D. in physics from Rice University, Houston, TX in 2003. From 2003 to 2005, he was a postdoctoral research fellow at Harvard University, Cambridge, MA. He joined the faculty of the University of Michigan in 2005. His research interest includes resistive-random access memory (RRAM), memristor-based logic circuits, neuromorphic computing systems, aggressively scaled transistor devices, and electrical transport in low-dimensional systems. To date Prof. Lu has published over 200 journal and conference articles with 30,000 citations and h-factor of 79. He is a recipient of the NSF CAREER award, an IEEE Fellow, and co-founder of Crossbar Inc, and MemryX Inc.

Andrew Adamatzky is Professor of Unconventional Computing and Director of the Unconventional Computing Laboratory, Department of Computer Science, University of the West of England, Bristol, UK. He does research in molecular computing, fungal computing, reaction-diffusion computing, collision-based computing, cellular automata, slime mould computing, massive parallel computation, applied mathematics, complexity, nature-inspired optimisation, collective intelligence and robotics, bionics, computational psychology, non-linear science, novel hardware, and future and emergent computation. He authored seven books, mostly notable are `Reaction-Diffusion Computing’, `Dynamics of Crow Minds’, `Physarum Machines’, and edited twenty-two books in computing, most notable are `Collision Based Computing’, `Game of Life Cellular Automata’, `Memristor Networks’; he also produced a series of influential artworks published in the atlas `Silence of Slime Mould’. He is founding editor-in-chief of ‘Journal of Cellular Automata’ and “Journal of Unconventional Computing’ and editor-in-chief of “Journal Parallel, Emergent, Distributed Systems’ and ‘Parallel Processing Letters’.

Professor Guangwen Yang is director of the National Supercomputing Center in Wuxi, and head of the Intelligent Computing Center of Zhejiang Lab. His research interests include high performance computing, parallel algorithms for numerical applications, and high-performance machine learning method. He has published over 200 high-quality articles, and has been awarded the ACM Gordon Bell Prize (2016, 2017), and the IEEE FPL Most Significant Paper Award in 25 Years, etc.

Zhi Jin is a Full Professor of Software Engineering at Peking University. She is the Vice Director of the Key Laboratory of High Confidence Software Technologies, Peking University, Ministry of Education of China. She is/was principal investigator of more than 10 national competitive grants, including the chief scientist of a national basic research project (973 project) of the Ministry of Science and Technology of China. She serves frequently as PC members for many well-known conferences like ICSE, FSE and RE. She is executive Editor-in-Chief of Chinese Journal of Software (2013- ), Associate Editor of IEEE TSE (2018- ) and IEEE TR (2019- ). She also serves in the Editorial Board of JCST (2010- ) REJ (2014- ) and ESEM (2020- ). She is a standing board member of China Computer Federation (CCF), the chair of CCF Technical Committee of System Software and was elected to CCF fellow.

Jincang Zhang is Distinguished Professor in condensed matter and materials physics, and executive-dean of Materials Genome Institute, Shanghai University. He was awarded a Ph.D. degree in Materials Science and Engineering from Toyama University of Japan. He currently works as the Director of SHU-ZJ Lab Joint Research Center for Computational Materials Science. He has taken a special interest in materials design by machine learning in artificial intelligence and experimental technology. He developed high-throughput experimental methods, such as PLD, OMBE and XRD et al, for functional thin film and bulk material, including magnetic, ferroelectric, multiferroic, spintronic, superconducting materials and their devices applications. So far, he has more than 500 publications and more than 20 patents.

Michael Lee is the Editor of Science Robotics. Prior to joining Science Robotics, Michael was a co-founding editor of Nature Electronics. He started his editorial career at Nature Communications as an associate editor handling applied physics and engineering research. Before becoming an editor Michael conducted research at the Paul Scherrer Institute (Switzerland) and University of Oxford (UK).