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Shen-Shyang Ho is a visiting assistant research scientist at the Center for Automated Research (CfAR), University of Maryland, starting 1 June 2010. Currently, he is a postdoctoral scholar at the California Institute of Technology, Pasadena, California. Before this, he was a NASA postdoctoral fellow at the Jet Propulsion Laboratory from 2007-2009. Shen-Shyang received his Ph.D. in Computer Science from George Mason University in 2007 and his Bachelor (Honors) in Science (Mathematics and Computational Science) from the National University of Singapore in 1999.
From 2007-2009, Shen-Shyang was the recipient of the highly competitive NASA postdoctoral fellowship to develop robust cyclone tracking and eye-locating algorithms using heterogeneous data from multiple satellite sources, and the development of novel data mining techniques to understand global cyclone evolutions. Currently, he is the co-I/ science-PI for a three-year NASA funded project to develop an information system for weather event analysis and tracking based on advanced moving object database, machine learning, and data mining techniques.
Shen-Shyang is the author of 25 technical articles, most in international peer-reviewed journals, conferences, and workshops including IEEE TPAMI (2), IEEE TAES, ICML, ACM GIS, IJCAI (2), UAI, KDD (2), and IEEE ICDM. He has 3 pending patents. He has served as a program committee member for IEEE ICDM and as a reviewer for IEEE TPAMI, IEEE TKDE, and IEEE TAES. He has also participated in NSF CISE/IIS grant review panels.
Tropical Cyclone Event Sequence Similarity Search via Dimensionality Reduction and Metric Learning
as author at Industry / Government Sessions ,