The Young Researchers Forum provides a platform for emerging leaders in computational intelligence, machine learning, brain-inspired computing, and nature-inspired optimization to share forward-looking perspectives on the future of AI. As the field moves rapidly toward integrating large-scale models, neuromorphic architectures, interpretable systems, and data-efficient learning, early- and mid-career researchers are at the forefront of driving these transformations.
This interactive session will explore how new paradigms, e.g., neuro-symbolic reasoning, bio-inspired algorithms, cross-domain transfer, and embodied intelligence, are reshaping both fundamental research and practical applications. Discussions will address the latest challenges and opportunities in reproducibility, ethical AI, and open science, as well as strategies for building impactful collaborations in an increasingly interdisciplinary landscape. Attendees will gain first-hand insights into the directions that will shape the next decade of machine intelligence and nature-inspired computing.
Moderator:
Ran Cheng, The Hong Kong Polytechnic University, Hong Kong SAR, China
Panelists:
Jing Liang, Zhengzhou University, China
Yu Qi, Zhejiang University, China
Chao Qian, Nanjing University, China
Yujie Wu, The Hong Kong Polytechnic University, Hong Kong SAR, China
Junchi Yan, Shanghai Jiao Tong University, China
Jing Liang
Zhengzhou University, China
Biography
Jing Liang received the B.E. degree from the Harbin Institute of Technology, Harbin, China, in 2003, and the Ph.D. degree from Nanyang Technological University, Singapore, in 2009. She is currently a Professor with the School of Electrical Engineering, Zhengzhou University, Zhengzhou, China. Her main research interests are evolutionary computation, swarm intelligence, multiobjective optimization, and neural network. Dr. Liang serves as an Associate Editor for IEEE Transactions on Evolutionary Computation and Swarm and Evolutionary Computation.
Yu Qi
Zhejiang University, China
Biography
Yu Qi is a tenure-track professor and doctoral supervisor at the Frontier Science Center for Brain and Brain-Computer Fusion, Zhejiang University. She was graduated from the School of Computer Science and Technology, Zhejiang University, with a Ph.D. in Engineering, and visited the University of Florida as a visiting student. The main research directions include brain-computer interface, artificial intelligence, and brain-like computing. She has proposed a series of innovative methods and systems for the dynamic modeling of brain information. In 2015, she established a prototype system for epilepsy warning-suppression diagnosis and treatment. In 2019, she completed the first domestic clinical volunteer invasive brain-computer interface research as a key member. She has published more than 30 high-level academic papers and undertaken a number of national-level projects. She is the young editor of Cyborg and Bionic Systems, the editor of Frontiers in Neuroscience, the program committee member of top artificial intelligence conferences NeurIPS, IJCAI, and ICML, and the reviewer of top journals such as TNNLS, TBME, and TNSRE.
Chao Qian
Nanjing University, China
Biography
Chao Qian received B.Sc. and Ph.D. degrees in the Department of Computer Science and Technology from Nanjing University in 2009 and 2015, respectively, under the supervision of Prof. Zhi-Hua Zhou. After finishing PhD, he became an associate researcher in the School of Computer Science and Technology, University of Science and Technology of China, until 2019, when he returned to Nanjing University as an associate professor in the School of Artificial Intelligence. In 2024, he became a full professor. He visited the University of the Basque Country (Spain) and the University of Birmingham (UK). He is also a member of LAMDA Group.
Yujie Wu
The Hong Kong Polytechnic University, Hong Kong SAR, China
Biography
Dr. Yujie Wu is an Assistant Professor at The Hong Kong Polytechnic University (PolyU). Prior to this, he was a postdoctoral researcher collaborating with Prof. Wolfgang Maass, a pioneer in brain-inspired computing, at Graz University of Technology (2021–2024). He received his Ph.D. from Tsinghua University under the supervision of Prof. Luping Shi and Prof. Jun Zhu (2016-2021). His recent works have been published in prestigious journals and top AI conferences, including Nature, Science Robotics, Nature Computational Science, Nature Communications, TNNLs and AAAI. He is featured as the World's Top 2% Scientists by Stanford University and three of his publications have been selected as ESI Top 1% Highly Cited Papers. The Tianjic chip project he participated in was recognized as one of the Top 10 Sci-tech Achievements in China in 2019.
Ran Cheng
Moderator
The Hong Kong Polytechnic University, Hong Kong SAR, China
Biography
Ran Cheng is currently an Associate Professor (Presidential Young Scholar) with the Department of Data Science & Artificial Intelligence and Department of Computing at The Hong Kong Polytechnic University (PolyU). Previously, he was an Associate Professor with the Department of Computer Science and Engineering at Southern University of Science and Technology (SUSTech). He received the BSc degree from Northeastern University (China) in 2010 and the PhD degree from the University of Surrey (UK) in 2016. Between 2010 and 2012, he spent a cherished period at Zhejiang University as a postgraduate student. His research philosophy is centered on benefiting humanity by bridging nature and technology. Within the broad domain of Artificial Intelligence (AI), my research focuses on advancing Computational Intelligence (CI) to tackle modeling and optimization challenges in complex systems. Ran Cheng primary research interests include Evolutionary Computation and Representation Learning, with an emphasis on developing efficient and scalable computational methods leveraging modern hardware acceleration. As a representative effort, he initiated the EvoX project, aiming at bridging traditional EC methodologies with advanced GPU computing infrastructures. He is the founding chair of IEEE Computational Intelligence Society (CIS) Shenzhen Chapter. He is serving as an Associate Editor/Editorial Board Member for several journals, including: ACM Transactions on Evolutionary Learning and Optimization, IEEE Transactions on Evolutionary Computation, IEEE Transactions on Emerging Topics in Computational Intelligence, IEEE Transactions on Cognitive and Developmental Systems, IEEE Transactions on Artificial Intelligence, etc. He is the recipient of the IEEE Transactions on Evolutionary Computation Outstanding Paper Awards (2018, 2021), the IEEE CIS Outstanding PhD Dissertation Award (2019), the IEEE Computational Intelligence Magazine Outstanding Paper Award (2020), and the IEEE CIS Outstanding Early Career Award (2025). He has been featured among the World’s Top 2% Scientists (2020–2024) and the Clarivate Highly Cited Researchers (2023, 2024). He is a Senior Member of IEEE.
