Hanghang Tong is currently an assistant professor at School of Computing, Informatics, and Decision Systems Engineering (CIDSE), Arizona State University since August 2014. 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 Post-doctoral fellow in 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 one ‘test of time’ award (ICDM 10-Year highest impact paper award), four best paper awards and four ‘best of conference’. He has published over 100 referred articles and more than 20 patents.
Ph.D., Computer Science, Carnegie Mellon University, 2009
M. Sci., Computer Science, Carnegie Mellon University, 2008
M. Eng., Pattern Recognition and Intelligent System, Tsinghua University, J2005
B. Eng., Automation Technology, Tsinghua University, 2002
Large scale data mining and machine learning, especially for graph and multimedia data with applications to social networks analysis, healthcare, cyber-security and e-commerce
Honors and awards
- “Data Mining Reveals the Secret to Getting Good Answers”, MIT Technology Review, 2013
- Best Paper Award, The 21st ACM International Conference on Information and Knowledge Management (CIKM), 2012.
- IBM Research Accomplishment Award on “Social and Cognitive Network Science”, 2012.
- Statistical Analysis and Data Mining on “Bests of SDM 2011”, 2011.
- Frontiers of Computer Science on “Bests of ICDM 2010”, 2010.
- Best Paper Award, 2008 SIAM Conference on Data Mining (SDM), 2008
- Best Research Paper Award, The 6th IEEE International Conference on Data Mining (ICDM), 2006.
- Associate Editor in ACM SIGKDD Exploration (since 2014).
- Guest Editor in “special issue on data mining technologies for computational social science”, DAMI 2012; “special issue on connected health at big data era”, TKDD 2014; “special issue on big data analytics and applications”, ELSEVIER Big Data Research 2014.
- Section Editor in “Social Network Applications in Homeland Security, Terrorism, Fraud De-tection, Public Sector, Politics and Case studies”, in Encyclopedia of Social Network Analysis and Mining (ESNAM) by Springer.
- Program Co-chair in the workshop on “Interactive Mining for Big Data” (in CIKM 2014), the workshop on “Connected Health at Big Data Era” (in KDD 2014); the 1st workshop on “Diffusion Networks and Cascade Analytics” (in WSDM 2014); the 2nd international workshop on “Large Scale Network Analysis (LSNA)” (in WWW 2013); the 10th workshop on “Mining and Learning with Graphs (MLG)” (in ICML 2012) and “Data Mining Technologies for Computational Collective Intelligence (DMCCI)” (in ICDM 2011).
- Senior Program Committee in CIKM 2013 and PAKDD 2013-2014.