2025
IEEE ROSENBLATT AWARD
Sponsored by the IEEE Computational Intelligence Society
“For contributions to evolutionary optimization of complex systems.”
Yaochu Jin pioneered the research on developing evolutionary algorithms for solving real-world optimization problems, including data-driven surrogate-assisted evolutionary optimization and evolutionary multi-objective optimization. His work addressed key challenges in evolutionary algorithms by introducing surrogate models, which significantly reduced computational costs and allowed evolutionary algorithms to be applied to a large class of real-world optimization problems, such as aerodynamic optimization. Jin has continued to make innovative contributions to multi-objective machine learning, including communication-efficient federated learning and federated neural architecture search, which are having a significant impact on AI research. In 2021, Jin published the first book on data-driven evolutionary optimization, solidifying his status as a leader in this field.
An IEEE Fellow, Jin is Chair Professor of Artificial Intelligence, School of Engineering, Westlake University, Hangzhou, Zhejiang, People’s Republic of China.