Pang-Ning Tan is a Professor in the Department of Computer Science and Engineering at Michigan State University. He received his MS degree in Physics and PhD degree in Computer Science from University of Minnesota. His research interests are in data mining and machine learning with application to various scientific and engineering domains, particularly in environmental and ecological sciences, network science, and cybersecurity. He has published more than 150 peer-reviewed articles and co-authored a widely-used textbook on data mining. His research has been supported by NSF, NASA, ONR, NOAA, NIH, and ARO, and through gifts from Cisco, Bosch Research, Hewlett Packard Research, and Narus.
Industry Expertise (3)
Mining and Metals
Areas of Expertise (5)
University of Minnesota: Ph.D., Computer Science 2002
University of Minnesota: M.S., Physics 1996
University of Technology of Malasia: B.S., Physics 1992
Journal Articles (1)
2016 This paper presents a novel multi-task learning framework for the accurate prediction of spatio-temporal data at multiple locations. The framework encodes the data as a third-order tensor and performs supervised tensor decomposition to identify the latent factors that capture the inherent spatiotemporal variabilities of the data and their relationship to the target variable of interest.