2020年06月24日
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关于举办澳大利亚昆士兰大学阴红志博士学术报告的通知

时间:2020-06-24 08:28:25  

 

各位老师:您好!  

我院邀请澳大利亚昆士兰大学人工智能学院副教授阴红志博士将于626日周五10点在腾讯会议线上做专题学术报告

报告题目:Network embedding-based Geo-social Recommendation 报告人:阴红志博士,澳大利亚 昆士兰大学 人工智能学院副教授

报告时间:2020626日(周五)上午10:0011:00

报告地点:https://meeting.tencent.com/s/69qdn0MMO0X8

或腾讯会议号 ID284 143 183

Dr Hongzhi Yin is a senior lecturer (equivalent to Associate Professor in North America) with the University of Queensland and the winner of Australian Discovery Early Career Researcher Award (澳洲优青equivalent to NSF CAREER award in North America). He received his doctoral degree from Peking University in July 2014, and his PhD Thesis won the highly competitive Distinguished Doctor Degree Thesis Award of Peking University.

His current main research interests include recommender system, social media analytics and mining, network embedding and mining, time series data and sequence data mining and learning, chatbots, federated learning, topic models, deep learning and smart transportation.

 

He has published 130+ papers, including 18 Highly Cited Papers (Top 1%), 60+ CCF A and 40+ CCF B, 60+ CORE A* and 45+ CORE A, such as KDD (x11), ICDE (x16), VLDB (x4), SIGIR (x6), ACM TOIS (x7), IEEE TKDE (x5), IJCAI (x4), AAAI (x3), VLDB Journal (x2), ICDM (x3), ACM Multimedia (x2), WWW (x3), CIKM (x6), SIGMOD and WSDM. He is the leading author (first author or corresponding author) for 80+ of them. He has won 5 Best Paper Awards such as ICDE'19 Best Paper Award and 21st ACM Annual Best of Computing Article as the first author.

He has received ARC Discovery Early Career Researcher Award (DECRA) within his first year of obtaining his PhD, ARC Discovery Project 2019 (Sole CI) as an early-career researcher, UQ Foundation Research Excellence Award 2019 as the first winner of this award in School of ITEE since the establishment of this award 20 years ago.

He is currently serving as Associate Editor for IEEE Journal of Social Computing, Editorial Board of Young Scientists for Journal of Computer Science and Technology (JCST), Guest Editor of Information Systems, World Wide Web and JCST.

He is currently directing the RSBDI (Responsible and Sustainable Big Data Intelligence) Lab. RSBDI Lab aims and strives to develop socially responsible and environmentally sustainable data mining and machine learning techniques with theoretical backbones to better discover actionable patterns and intelligence from large-scale, networked, dynamic and sparse data. The research of RSBDI Lab is directly motivated by, and contributes to, applications in E-commerce and marketing, social informatics, biomedical and health informatics, urban transportation and information security. His research has also been attracting media coverage, such as UQ News, Faculty News of EAIT, Computing Reviews, 360 News.

                                           通信与信息工程学院

       2020624


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