| Jie Tang is a Tenured associate professor and also serves as the vice-Chair of the Department of Computer Science and Technology at Tsinghua University. He has been visiting scholar at Cornell University, Hong Kong University of Science and Technology, and Southampton University. His interests include social network analysis, data mining, and machine learning. He has published more than 200 journal/conference papers and holds 20 patents. His papers have been cited by more than 10,000 times (Google Scholar). He served as PC Co-Chair of CIKM’16, WSDM’15, Associate General Chair of KDD’18, and Acting Editor-in-Chief of ACM TKDD, Editors of IEEE TKDE/TBD and ACM TIST. He leads the project AMiner.org for academic social network analysis and mining, which has attracted more than 8 million independent IP accesses from 220 countries/regions in the world. He was honored with the UK Royal Society-Newton Advanced Fellowship Award, CCF Young Scientist Award, and NSFC Distinguished Young Scholar. |
| Massive open online courses (MOOCs) boomed in recent years and have attracted millions of users worldwide. For example XuetangX.com, a platform similar to Coursear and edX, is offering thousands of courses to more than 10,000,000 registered users. However the completion ratio is always very low. I will introduce how we leverage users’ implicit feedback, e.g., user clicks, to help improve learning effectiveness. |
