报告人：Professor Witold Pedrycz, University of Alberta, Edmonton, Canada (加拿大阿尔伯塔大学)

报告时间：2024年05月28日10:00-11:00

报告地点：Zoom在线会议

会议ID: 281 001 9605

参会密码: HNU2024

报告摘要:The objective of this talk is to identify the challenges and develop a unique and comprehensive setting of data-knowledge environment in the realization of the development of ML models. We review some existing directions including concepts arising under the name of physics informed ML. We investigate the representative topologies of ML models identifying data and knowledge functional modules and interactions among them. We also elaborate on the central role of information granularity in this area.

该报告将分享在实现ML模型开发的过程中开发独特而全面的数据知识环境。并讨论一些现有的方向，包括以物理信息ML的名义出现的概念。我们研究了识别数据和知识功能模块及其之间交互的ML模型的代表性拓扑。还详细阐述了信息粒度在这一领域的核心作用。

报告人简介:Witold Pedrycz (IEEE Life Fellow) is Professor in the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada. He is also with the Systems Research Institute of the Polish Academy of Sciences, Warsaw, Poland. Dr. Pedrycz is a foreign member of the Polish Academy of Sciences and a Fellow of the Royal Society of Canada. He is a recipient of  several awards including Norbert Wiener award from the IEEE Systems, Man, and Cybernetics Society, IEEE Canada Computer Engineering Medal, a Cajastur Prize for Soft Computing from the European Centre for Soft Computing, a Killam Prize, a Fuzzy Pioneer Award from the IEEE Computational Intelligence Society, and 2019 Meritorious Service Award from the IEEE Systems Man and Cybernetics Society.

Witold Pedrycz（IEEE终身会士）是加拿大埃德蒙顿阿尔伯塔大学电气与计算机工程系教授。他还任职于波兰科学院系统研究所。Pedrycz博士是加拿大皇家学会院士。他曾获得多项奖项，包括IEEE系统、人与控制论学会颁发的Norbert Wiener奖、IEEE加拿大计算机工程奖章、欧洲软计算中心颁发的Cajastur 软计算奖、IEEE计算智能学会颁发的Killam奖、模糊先锋奖以及IEEE系统人与控制论学会颁发的2019年杰出服务奖。

邀请人：李肯立

联系人：李梦泉