【大数据与脑机智能高精尖中心学术报告】:美国宾州州立大学Zhenhui (Jessie)Li教授学术报告-北航医工交叉创新研究院
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【大数据与脑机智能高精尖中心学术报告】:美国宾州州立大学Zhenhui (Jessie)Li教授学术报告

发布时间:2018-06-22 11:47   点击次数:

主讲人:美国宾州州立大学Zhenhui (Jessie) Li教授

时间:2018年6月27日上午10:00

地点:新主楼G510

主办单位:大数据科学与脑机智能高精尖创新中心

题目Title: Mining Mobility Data forIntelligent Transportation

主讲人简介Bio:

 

Dr. Zhenhui (Jessie) Li is a tenuredassociate professor of Information Sciences and Technology at the PennsylvaniaState University. She is Haile family early career endowed professor. Prior tojoining Penn State, she received her PhD degree in Computer Science fromUniversity of Illinois Urbana-Champaign in 2012, where she was a member of datamining research group. Her research has been focused on mining spatial-temporaldata with applications in transportation, ecology, environment, social science,and urban computing. She is a passionate interdisciplinary researcher and hasbeen actively collaborating with cross-domain researchers. She has received NSFCAREER award, junior fac ulty excellence in research, and George J. McMurtryjunior faculty excellence in teaching and learning award. She is currentlytaking sabbatical leave (2018-2019) at Hangzhou to conduct city brain research.To learn more, please visit her homepage: https://faculty.ist.psu.edu/jessieli

报告摘要Abstract:

Large-scale mobility data can be collected frommobile phones, car navigation systems, road surveillance cameras, and loopsensors. Turning such raw data into knowledge can provide insights about ourcity and empower the city to be more intelligent.

In this talk, I would like to share newdata mining and machine learning technologies to address challenges in traveldemand prediction (in collaboration with Didi Chuxing) and intelligent trafficsignal control through reinforcement learning (using real surveillance cameradata).

In addition, I would like to share citybrain open research initiative. We are looking for researchers and students whoare interested in city related research problems to join us at Hangzhou toconduct city brain research together.