梁静，1981年6月出生，河南兰考人。郑州大学电气工程学院院长、教授、博士生导师，国家自然科学基金优秀青年基金获得者，河南省优化与智能控制技术工程研究中心主任，第三届河南省青年科技工作者协会会长，国际SCI一区期刊IEEE Transaction on Evolutionary Computation和Swarm and Evolutionary Computation的Associate Editor，第六届中国科技工作者协会委员，河南省侨联青年委员会副会长，河南欧美同学会理事。 梁静教授长期从事群体智能优化算法设计及其应用方面的教学与科学研究，是进化计算领域的专家。她先后主持国家自然科学基金优秀青年基金项目、国家自然科学基金面上项目、国家自然科学基金青年项目、国家博士后特别资助项目、河南省教育厅创新人才等项目。发表学术论文130余篇，Google Citation被引用总次数11760次，h指数为36，获国家发明专利2项、授权软件著作权5项。科研成果先后获得教育部自然科学二等奖，河南省科学进步二等奖，河南省教育厅科技成果一等奖等奖项。梁静教授还获得国际学术组织和河南省颁发的一系列奖励和荣誉称号，如2014 IEEE CIS Outstanding PhD Dissertation Award获得者、河南省高层次人才、河南省青年五四奖章、河南省青年科技奖、中原计划-中原青年拔尖人才等。

Website: https://www.zzu.edu.cn/info/1367/18543.htm

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.

Website: https://person.zju.edu.cn/en/yuqi

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.

Website: https://www.lamda.nju.edu.cn/qianc/

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.

Website: https://yjwu17.github.io/

Website: https://en.zhiyuan.sjtu.edu.cn/en/faculty/451/detail

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.

Website: https://chengran.tech/