报 告 人：金耀初 院士

工作单位：比勒费尔德大学（德国）

报告题目：数据驱动优化：从最优性到可信度

报告时间：2023年5月21日（周日）14:30-15:30

报告链接：Teams Link

https://teams.microsoft.com/l/meetup-join/19%3aB4gmRcUATAMA2iJqi-xXvtfPFfTbxVJPxSW_pcAPBao1%40thread.tacv2/1638719716825?context=%7b%22Tid%22%3a%2222804ebb-30d5-47df-942f-f3a3722f0225%22%2c%22Oid%22%3a%2216a60c03-ad7a-4b85-a403-8ebd947e010c%22%7d

内容摘要：

  数据驱动优化已经广泛应用于现实生活中，从工程优化、药物设计到深度神经结构搜索等。本报告将首先简要回顾数据驱动优化的相关内容，随后将介绍一些高效解决高维多目标优化问题的贝叶斯进化优化算法，这些优化算法利用了机器学习、贝叶斯优化和进化算法之间的协同作用。之后，本报告将讨论数据驱动优化中的安全和隐私问题，以及最近提出的安全和隐私保护的联邦数据驱动优化的思想。最后，将以讨论数据驱动优化中的公平性和偏好性结束本次报告。

个人简介：

  金耀初院士目前是由德国联邦教育和研究部、德国比勒费尔德大学技术学院资助的亚历山大·冯·洪堡人工智能教授，也是英国萨里大学计算机科学系计算智能杰出教授，芬兰捷瓦斯基拉大学“长江杰出访问教授”，澳大利亚悉尼理工大学“杰出访问学者”以及欧洲科学院院士及IEEE会士。金耀初院士现任《Complex & Intelligent Systems》期刊主编，曾任IEEE杰出讲师，IEEE计算智能协会技术活动副主席，以及IEEE《Transactions on Cognitive and Developmental Systems》主编。自2019至2021年，金耀初院士在科学网络组织中连续获评“高被引研究者”。

【编辑：王健】

英文版：

Academic Report Notice of Yaochu Jin : Data-Driven Optimization: From Optimality to Trustworthiness

Speaker: Academician  Yaochu Jin

Title: Data-Driven Optimization: From Optimality to Trustworthiness

Time: 14:30 pm, May 21, 2023 (Sunday)

Link: https://teams.microsoft.com/l/meetup-join/19%3aB4gmRcUATAMA2iJqi-xXvtfPFfTbxVJPxSW_pcAPBao1%40thread.tacv2/1638719716825?context=%7b%22Tid%22%3a%2222804ebb-30d5-47df-942f-f3a3722f0225%22%2c%22Oid%22%3a%2216a60c03-ad7a-4b85-a403-8ebd947e010c%22%7d

Abstract:

    Data-driven optimization has found abundant real-world applications, ranging from engineering optimization, drug design, to deep neural architecture search. After a brief review of data-driven optimization, this talk presents a few computationally efficient Bayesian evolutionary optimization algorithms for high-dimensional multi-objective optimization problems that exploit the synergies between machine learning, Bayesian optimization, and evolutionary algorithms. Then, we discuss security and privacy concerns in data-driven optimization and introduce recently developed ideas for secure and privacy-preserving federated data-driven optimization. We will conclude the talk with discussing fairness and preferences in data-driven optimization. 

Personal Introduction:

    Yaochu Jin is presently an Alexander von Humboldt Professor for Artificial Intelligence endowed by the German Federal Ministry of Education and Research, with the Faculty of Technology, Bielefeld University, Germany. He is also a Distinguished Chair in Computational Intelligence, Department of Computer Science, University of Surrey, Guildford, U.K. He was a “Finland Distinguished Professor”, University of Jyväskylä, Finland, “Changjiang Distinguished Visiting Professor”, Northeastern University, China, and “Distinguished Visiting Scholar”, University of Technology Sydney, Australia. Prof Jin is presently the Editor-in-Chief of Complex & Intelligent Systems. He was an IEEE Distinguished Lecturer, the Vice President for Technical Activities of the IEEE Computational Intelligence Society, and the Editor-in-Chief of the IEEE Transactions on Cognitive and Developmental Systems. He was named by the Web of Science as “a Highly Cited Researcher” from 2019 to 2021 consecutively. He is a Member of Academia Europaea and Fellow of IEEE. 

                                                                                                                         [Editor: Jian Wang]