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Prof. Tianrui Li, Southwest Jiaotong University, China

Prof. Tianrui Li, Southwest Jiaotong University, China
 

Tianrui Li received his  B.S. degree, M.S. degree and P h.D. degree from the Southwest  Jiaotong University, China  in 1992, 1995 and 2002 respect ively. He was a Post-Doctoral  Researcher at Belgian Nuclear  Research Centre (SCK • CEN),  Belgium from 2005-2006, a visiting professor at Hasselt  University, Belgium in 2008, t he University of Technology, Sydney, Australia in 2009 and the University of Regina, Canad a in 2014. And, he is presentl y a Professor and the Director  of the Key Lab of Cloud Computing and Intelligent  Technique of Sichuan Province,  Southwest Jiaotong  University, China. Since 2000,  he has co-edited 6 books, 10 special issues of internationa l journals, 15 proceedings,  received 5 Chinese invention  patents and published over 240 research papers (e.g., IEEE  TKDE, IEEE TEC, IEEE TFS, IEEE TIFS, IEEE ASLP, IEEE TIE, IEEE TC, IEEE TVT) in refereed journals  and conferences (e.g., KDD,  IJCAI, UbiComp). 3 papers  were ESI Hot Papers and 12 papers was ESI Highly Cited  Papers. His Google H-index is 32. He serves as the area editor of International Journal of Computational Intell igence Systems (SCI), editor  of Knowledge-based Systems ( SCI) and Information Fusion ( SCI), etc. He is an IRSS fellow, a  distinguished member of CCF,  a senior member of ACM, IEEE,  CAAI, ACM SIGKDD member,  Chair of IEEE CIS Chengdu  Chapter (2013-2018), Treasurer of ACM  SIGKDD China Chapter and CCF  YOCSEF Chengdu Chair (2013-2014). Over fifty graduate  students (including 8 Post- Docs, 13 Doctors) have been  trained. Their employment  units include Microsoft  Research Asia, Sichuan  University, Baidu, Alibaba,  Tencent and Huawei. They have  received 2 "Si Shi Yang Hua"  Medals, Best Papers/ Dissertation Awards 13 times,  Champion of Sina Weibo Interaction-prediction at Tianchi Big Data Competition (Bonus  200,000 RMB), Second Place of  Social Influence Analysis  Contest of IJCAI-2016  Competitions. 
 

Speech Title: Data-Driven Intelligence:Challenges and our Solutions
 

Abstract: Data-Driven Intelligence has become a hot research  topic in the area of information science. This talk aims to outline the challenges on Data-Driven Intelligence. Then our solutions for Data-Driven Intelligence are provided, which cover the following aspects. 1) A hierarchical entropy-based approach is demonstrated to evaluate the effectiveness of data collection, the first step of Data-Driven Intelligence.   2) A multi-view-based method is illustrated for filling missing data, the preprocessing step on Data-Driven Intelligence. 3) A  unified framework is outlined for Parallel Large-scale Feature Selection to manage Big Data with high dimension. 4) A MapReduce-based parallel method together with three parallel strategies are presented for computing rough set approximations, which is a fundamental part in rough set-based data analysis similar to frequent pattern mining in association rules. 5)  Incremental learning-based approaches are shown for updating approximations and knowledge in dynamic data environments,  e.g., the variation of  objects, attributes or attribute values, which  improve the computational efficiency by using previously acquired learning results to facilitate knowledge maintenance without  re-implementing the original data mining algorithm. 6) A deep-learning-based model to deal with multiple different sources of data is developed.
 
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2018 10th International Conference on Machine Learning and Computing (ICMLC 2018) 

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