题目：Why Do We Need Theoretical Research of Evolutionary Algorithms?
主讲人：Chao Qian,Associate Professor, University of Birmingham, UK
主持人：Dr. Yi Mei（Senior Lecturer, Victoria University of Wellington, NZ)
时间：2023年9月18日16:00-17:00（北京时间）
讲座语言：英文
主办单位：IEEE Taskforce on Evolutionary Scheduling and Combinatorial Optimisation (https://homepages.ecs.vuw.ac.nz/~yimei/ieee-tf-esco/)
Zoom link:https://vuw.zoom.us/j/95256532265
报告摘要：Most researchers in the area of evolutionary computation focus on empirical studies. However, theoretical research is definitely very important to this area. In this talk, I will introduce: What are theories of evolutionary algorithms? How can theories help us? Why is theoretical research necessary? Is there any limitation for theoretical research? Finally, I will also give some guidance about how to do theoretical research of evolutionary algorithms.
报告人简介：Chao Qian is an Associate Professor in the School of Artificial Intelligence, Nanjing University, China. He received the BSc and PhD degrees in the Department of Computer Science and Technology from Nanjing University. After finishing his PhD in 2015, 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.His research interests are mainly theoretical analysis of evolutionary algorithms (EAs), design of safe and efficient EAs, evolutionary learning, and application of EAs to solve real-world complex problems. He has published one book “Evolutionary Learning: Advances in Theories and Algorithms”, and over 40 papers in top-tier journals (AIJ, ECJ, TEvC, Algorithmica, TCS) and conferences (AAAI, IJCAI, NeurIPS, ICLR). He has won the ACM GECCO 2011 Best Theory Paper Award, the IDEAL 2016 Best Paper Award, and the IEEE CEC 2021 Best Student Paper Award Nomination. He is an associate editor of IEEE Transactions on Evolutionary Computation, a young associate editor of Science China Information Sciences, an editorial board member of the Memetic Computing journal, and was a guest editor of Theoretical Computer Science. He is a member of IEEE Computational Intelligence Society (CIS) Evolutionary Computation Technical Committee, and was the chair of IEEE CIS Task Force on Theoretical Foundations of Bio-inspired Computation. He has regularly given tutorials and co-chaired special sessions at leading evolutionary computation conferences (CEC, GECCO, PPSN), and has been invited to give an Early Career Spotlight Talk "Towards Theoretically Grounded Evolutionary Learning" at IJCAI 2022. He will be a Program Co-Chair of the 22nd Pacific Rim International Conference on Artificial Intelligence (PRICAI 2025).
钱超教授简介：钱超，南京大学人工智能学院副教授。先后在南京大学计算机科学与技术系获得学士和博士学位。2015年博士毕业后，他成为中国科学技术大学计算机科学与技术学院副研究员，直到2019年回到南京大学。他的研究兴趣主要是进化算法（EAs）的理论分析、安全高效的EAs设计、进化学习以及应用EAs解决现实世界的复杂问题。他出版了一本专著《进化学习》（Evolutionary Learning： 在顶级期刊（AIJ、ECJ、TEvC、Algorithmica、TCS）和会议（AAAI、IJCAI、NeurIPS、ICLR）上发表了40多篇论文。他曾获ACM GECCO 2011最佳理论论文奖、IDEAL 2016最佳论文奖和IEEE CEC 2021最佳学生论文奖提名。他是《IEEE Transactions on Evolutionary Computation》副主编、《中国科学信息科学》青年副主编、《Memetic Computing》杂志编委，曾任《Theoretical Computer Science》客座编辑。他是IEEE计算智能学会（CIS）进化计算技术委员会成员，曾任IEEE CIS生物启发计算理论基础工作组主席。他经常在主要的进化计算会议（CEC、GECCO、PPSN）上发表演讲并共同主持特别会议，还受邀在IJCAI 2022上发表题为"Towards Theoretically Grounded Evolutionary Learning "的早期职业聚焦演讲。他将担任第22届环太平洋国际人工智能会议（PRICAI 2025）的项目联合主席。
