题  目：From Nature-inspired Computation to Machine Learning

主讲人：李晓东（Xiaodong Li）

时  间：2025年11月28日16:30-18:30

地  点：腾讯会议（829-692-969）

主讲人简介：

李晓东，1988年本科毕业于西安电子科技大学，1997年获新西兰奥塔哥大学人工智能专业博士学位。现任澳大利亚墨尔本皇家理工大学计算机学院教授。研究领域包括人工智能，进化算法，机器学习，数据挖掘，粒子群优化，多目标优化，小生境算法，复杂系统筹。获 2013年 ACM SIGEVO Impact Award 和2017年 IEEE CIS IEEE Transactions on Evolutionary Computation Outstanding Paper Award。电气电子工程师学会会士（IEEE Fellow）。 根据Google Scholar, 标志影响力的H指数是66，论文引用超2万多次。

内容简介：

Nature-inspired computation and machine learning are two research areas (in Artificial Intelligence) with rising popularity in the past two decades.  In this presentation, I will talk about my research experience revolving around these two themes since my time doing PhD until more recently, spanning almost three decades.  What started as curiosities and fascination of how nature does computation have gradually evolved into research ideas for designing algorithms in tackling challenging optimization problems.  I will touch on the following topics: particle swarm optimization, niching methods, large-scale optimization, preference modelling for multi-criteria decision making, hybridized methods such as meta-heuristics with mathematical programming, and machine learning for handling large-scale combinatorial optimization problems.