Partial List of Speakers

Jie Tang
Tsinghua University,

Talk: The Little Mu that Learns!

I am a Full Professor and the Associate Chair of the Department of Computer Science and Technology of Tsinghua University. I obtained my Ph.D. in DCST of Tsinghua University in 2006. My research interests include artificial intelligencedata mining, social networks machine learning and knowledge graph, with an emphasis on designing new algorithms for mining social and knowledge networks.

I have been visiting scholar at Cornell University (working with Prof. John Hopcroft and Jon Kleinberg), University of Southampton (working with Dame Wendy Hall), KU Leuven (working with Marie-Francine Moens), University of Illinois at Urbana-Champaign (short term, working with Jiawei Han), Chinese University of Hong Kong (working with Jeffrey Yu), and Hong Kong University of Science and Technology (working with Qiong Luo). During my graduate career, I have been an intern at NLC group of Microsoft Research Asia from 2004 to 2005. I also have attended the internship program of IBM China Research Lab in 2004.

I have published more than 200 journal/conference papers and hold 20 patents. I served as PC Co-Chair of CIKM’16WSDM’15, Associate General Chair of KDD’18, and Acting Editor-in-Chief of ACM TKDD, Editors of IEEE TKDEIEEE TBD, and ACM TIST. I am leading the project AMiner.org for academic social network analysis and mining, which has attracted more than 10 million independent IP accesses from 220 countries/regions in the world. I was honored with the UK Royal Society-Newton Advanced Fellowship AwardCCF Young Scientist AwardNSFC for Distinguished Young Scholar, and KDD’18 Service Award.

I am looking for highly-motivated students to work with me on the exciting area of social network, data mining, and machine learning. I also have a few open Postdoctoral Positions to investigate underlying theory and algorithms in data mining, social networks, machine learning, and knowledge graph.


Talk Abstract
“小木”机器人是清华大学与学堂在线联合研发的一个人工智能应用,定位于个性化的“学习伴侣/书僮”,旨在帮助学习者提高学习效率和积极性,同时减轻教师和助教的负担。“小木”基于先进的人工智能和自然语言处理技术,利用学堂在线海量的优质内容资源,结合互联网上专业知识库,构建了庞大的知识图谱体系,并以此为基础,提供答疑、导航、推荐、提问、社交等服务。基于AI技术的“小木”机器人可以理解用户关于课程的疑难知识点的问题,并以文字、图片以及视频等形式进行解答;另外,从课程体系结构里面抽取知识概念以及知识概念之间的相互关系,为用户可视化地展示知识点的先修/后继关系;用户可以点击感兴趣的知识点以让小木进行疑难解惑;同时在用户观看课程视频的时候,会主动提问相关知识点,及时地让用户在学习中巩固易错、易混淆的知识点。唐杰形象地把“小木”形容成中国古代读书人身边的书僮,可以帮忙“找资料”,除此之外,“书僮”贴心地理解用户,“小木”还能进行用户行为的建模,标签分析,自动识别并挖掘课堂的重要知识点等等。现在还在尝试将积极心理学引入“小木”,提高学习者的学习效率和积极性。基于AI技术的“小木”机器人在用户学习一门课程学习过程中可以智适应学习,能够根据用户的喜好,来为用户定制化地推荐一些课程帮助学习者高效学习。
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