Lei Shi

Lei Shi is an Associate Professor in the State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences. He holds B.S. (2003), M.S. (2006) and Ph.D. (2008) degrees from Department of Computer Science and Technology, Tsinghua University. His research interests span visual analytics, data mining and networked systems, with a focus on large-scale, dynamic and heterogeneous networks and graphs. He has published more than 60 papers in graph-related venues, including IEEE TVCG, TKDE, TC, VIS, ICDM, ICDE, ACM SIGCOMM and CSCW. He is the recipient of IBM Research Accomplishment Award on “Visual Analytics'' and the IEEE VAST Challenge Award twice in 2010 and 2012. He organized several workshops at ACM BCB, IEEE ICDM, IEEE ICCCN, etc.

Hanghang Tong

Hanghang Tong is currently an Assistant Professor at School of Computing, Informatics and Decision Systems Engineering at Arizona State University. Before that, he was an Assistant Professor at Computer Science Department, City College, City University of New York, a research staff member at IBM T. J. Watson Research Center and a postdoctoral fellow at Carnegie Mellon University. He received his M.Sc and Ph.D. degree from Carnegie Mellon University in 2008 and 2009, both majored in Machine Learning. His research interest is in large scale data mining for graphs and multimedia. He has received several awards, including a “best of time” award (ICDM 2015 10-Year Highest Impact Paper award), 4 best paper awards (TUP 2014, CIKM 2012, SDM 2008, and ICDM 2006) and 4 “bests of conference”. He has published over 100 refereed articles and holds more than 20 patents. He has served as a program committee member in top data mining, databases, and artificial intelligence venues (e.g., SIGKDD, SIGMOD, AAAI, and WWW, etc). He organized several workshops at ACM KDD, IEEE ICDM, etc.

Chaoli Wang

Chaoli Wang is an Associate Professor of Computer Science and Engineering at the University of Notre Dame. He received a Ph.D. degree in Computer and Information Science from The Ohio State University in 2006. Dr. Wang's main research interest is scientific visualization, in particular on the topics of time-varying multivariate data visualization, flow visualization, and information-theoretic algorithms and graph-based techniques for big data analytics. He has published extensively in visual analysis of scientific data sets leveraging various graph representations. Dr. Wang is a recipient of the U.S. National Science Foundation CAREER Award. He organized three tutorials (2008, 2009, 2013) at IEEE VisWeek/VIS.

Leman Akoglu

Leman Akoglu is an Assistant Professor in the Department of Computer Science at Stony Brook University. She received her Ph.D. from the Computer Science Department at Carnegie Mellon University in 2012. She also spent summers at IBM T. J. Watson Research Labs and Microsoft Research at Redmond. Her research interests span a wide range of data mining and machine learning topics with a focus on algorithmic problems arising in graph mining, pattern discovery, social and information networks, and especially anomaly mining; outlier, fraud, and event detection. Dr. Akoglu's research has won 4 publication awards; Best Research Paper at SIAM SDM 2015, Best Paper at ADC 2014, Best Paper at PAKDD 2010, and Best Knowledge Discovery Paper at ECML/PKDD 2009. She also holds 3 U.S. patents filed by IBM T. J. Watson Research Labs. Dr. Akoglu is a recipient of the NSF CAREER award (2015) and Army Research Office Young Investigator award (2013). Her research is currently supported by the National Science Foundation, the US Army Research Office, DARPA, a gift from Northrop Grumman Aerospace Systems, and a gift from Facebook. She organized several workshops at ACM KDD, SIAM SDM, etc.