RESEARCH

Research Units

Deep Learning for Hydrology

This research unit consists of five members. Three of the members have expertise in hydrology. The other two are experts in computer science. The objectives of this research unit are to apply deep machine learning techniques to hydrological issues, and meanwhile develop new deep learning techniques with hydrological data. Deep learning is nowadays a very popular approach in many fields. However, deep learning has hardly been applied to hydrological issues so far. There are many things that can be improved by deep learning techniques. In addition, it may be required to develop new deep learning techniques in order to solve hydrological issues. Collaborative work between hydrologists and computer scientists has a large potential to solve many kinds of hydrological issues.

Unit members

  • Japan
    Unit leader
    Kei ISHIDA
    Assistant Professor, Faculty of Advanced Science and Technology, Kumamoto University
    Japan
  • Japan
    Motoki AMAGASAKI
    Associate Professor, Kumamoto University
    Japan
  • Japan
    Masato KIYAMA
    Assistant Professor, Kumamoto University
    Japan
  • USA
    Ali ERCAN
    Assistant Professional Researcher (Assistant Research Professor), University of California, Davis
    USA
  • USA
    Tonbi TU
    Postdoctoral Scholar, Department of Environmental Science, Policy and Management, University of California, Berkeley
    USA