128 active or rapidly developed research frontiers in the world in 2023 are selected in the report "2023 Research Frontier" and the report "2023 Research Frontier Heat Index" jointly released by the Chinese Academy of Sciences, the Institute of Science and Technology Strategic Consulting, the Documentation and Information Center of the Chinese Academy of Sciences, and Clarivate Analytics on 28th November 2023. They also studied and judged the development trend and key issues of related disciplines.
Our Dean, Professor C.L. Philip Chen, pioneered the "Broad learning system" and won the second place in the forefront of hot topics in the field of information science in 2023!
First proposed "Broad learning system" to achieve edge intelligent learning. The Broad learning system, as a new learning method, has shown significant advantages in horizontal expansion and incremental learning compared to traditional deep learning networks. This system does not require frequent updates of network connection weights when processing data in open environments, mainly due to the design and optimization of its shallow network structure. This structure focuses on expanding the number of neurons and performing incremental calculations to improve the overall accuracy of the system. In addition, when facing the increase of data flow, broad learning does not need to readjust the network structure, which greatly increases its flexibility and efficiency.
In practical applications, especially in the intelligent learning field of edge computing, "Broad Learning System" shows its great potential. For example, in intelligent driving systems, the current approach is to calculate decisions in the cloud (such as how to accelerate, brake, etc.), and then transmit these decisions to the car for execution. But when cars encounter unprecedented complex situations, relying solely on existing experience to make judgments may not be accurate enough. If edge computing can make real-time decision analysis, it will be able to make more accurate judgments in complex environments. Cloud based computing and learning can be updated offline without affecting real-time decision-making. This is the key value of "Broad Learning System" in the intelligent learning field of edge computing.
Personal Profile
Dr. C.L. Philip Chen, National Distinguished Expert, Dean and Chair Professor of the School of Computer Science at South China University of Technology. Professor Chen is the Vice Chairman of the China Association of Automation, Director of the Health Intelligence and Digital Parallel Human Engineering Center of the Ministry of Education, Director of the Guangdong Key Laboratory of Computational Intelligence and Cyberspace Information, Co-chairman of the Guangdong Artificial Intelligence Industry Association, and Deputy Director of the Pazhou Laboratory. He is an IEEE Fellow, AAAS Fellow, IAPR Fellow, Academia Europaea, European Academy of Sciences and Arts, Chinese Association for Automation (CAA) Fellow, Chinese Association for Artificial Intelligence (CAAI) Fellow, and Hong Kong Institute of Engineers (HKIE) Fellow. Professor Chen has previously served as Editor-in-Chief of two top SCI jourals: IEEE Trans. on Cybernetics (2020-2021) and IEEE Trans. on Systems, Man, and Cybernetics: Systems (2014-2019). He was also former President of IEEE SMC Society (2012-2013) and editorial board member of domestic journals CAAI Trans. on AI, Chinese Science, and Journal of Automation.
In 2018, Professor Chen was awarded the highest academic Wiener Award in IEEE Systems Science Control Theory, the 2021 IEEE Joseph Wohl Lifetime Achievement Award, and the Outstanding Contribution Award in Artificial Intelligence by Wu Wenjun from the Chinese Society of Artificial Intelligence. Professor Chen's research focuses mainly on intelligent systems and control, computational intelligence, hybrid intelligence, and data science. He is a globally highly cited scientist at Clarivate Analytics for five consecutive years from 2018 to 2022 (in computer science in 2018, and in engineering and computer science in 2018-2022).
