演讲时间：2022年8月11日 （周四）9:30—11:30                参加方式：腾讯会议 822 434 657 

演讲摘要：Revealing complicated behaviors from time series constitutes a fundamental problem of continuing interest and it has attracted a great deal of attention from a wide variety of fields on account of its significant importance. The past decade has witnessed a rapid development of complex network studies, which allow to characterize many types of systems in nature and technology that contain a large number of components interacting with each other in a complicated manner. Recently, the complex network and deep learning have been incorporated into the analysis of time series and fruitful achievements have been obtained. Complex network and deep learning analysis of time series open up new venues to address interdisciplinary challenges in multiphase flow, brain-computer interface, and rehabilitation engineering. Some novel methodologies and their applications in this research area will be introduced.

演讲者简介：高忠科，天津大学电气自动化与信息工程学院教授、博士生导师，国家优秀青年科学基金获得者，天津市杰出青年科学基金获得者，全球高被引科学家，中国高被引学者，天津市中青年科技创新领军人才。主要研究方向为复杂网络多源信息融合理论、新型传感器技术、脑机融合与混合智能等，已在IEEE Transactions on Neural Networks and Learning Systems、IEEE Transactions on Industrial Informatics、IEEE Transactions on Systems, Man, and Cybernetics: Systems等国际期刊上发表SCI检索论文130余篇；在德国Springer出版社出版英文学术专著一部；第一发明人中国发明专利76项。主持国家级省部级项目10余项。获2021年强国青年科学家提名，2018年和2019年2次获得英国皇家物理学会(IOP)高被引中国作者奖，入选“全球顶尖前10万科学家”榜单。 

演讲者-高忠科教授