演讲人：Jun Huan, Ph.D.
Department of Electrical Engineering and Computer Science,University of Kansas时 间：2013 年 7 月 4 日星期四上午 10 点地 点：张江校区软件楼 102 第二会议室联系人：肖仰华（shawyh@fudan.edu.cn）Abstract: Graphs are widely used modeling tools that capture objects and their relation. Graph modeled data are found in diverse application areas including bioinformatics, cheminformatics, social networks, wireless sensor networks among many others. In this talk we will present our recent work on graph kernel functions and graph similarity search in the context of big data, focusing on scalable algorithmic approaches for graph data. Applications of graph modeling techniques in bioinformatics and social network analysis will be touched at the end.Bio:Dr. Jun (Luke) Huan is an Associate Professor in the Department of Electrical Engineering and Computer Science at the University of Kansas. He directs the Bioinformatics and Computational Life Sciences Laboratory at KU Information and Telecommunication Technology Center (ITTC) and the Cheminformatics core at KU Specialized Chemistry Center. Dr. Huan holds courtesy appointments at the KU Bioinformatics Center, the KU Bioengineering Program, and a visiting professorship from GlaxoSmithKline plc.. Dr. Huan received his Ph.D. in Computer Science from the University of North Carolina at Chapel Hill. Before joining KU in 2006, he worked at Argonne National Laboratory and GlaxoSmithKline plc.. Dr. Huan was a recipient of the National Science Foundation Faculty Early Career Development Award in 2009. He has published more than 80 peer-reviewed papers in leading conferences and journals, including Nature Biotechnology. His group won the Best Student Paper Award at IEEE International Conference on Data Mining in 2011 and the Best Paper Award (runner-up) at ACM International Conference on Information and Knowledge Management in 2009. Dr. Huan served on the program committees of prestigious international conferences including ACM SIGKDD, ACM CIKM, ICML, IEEE ICDE, IEEE ICDM, and IEEE BigData.
