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Dr. Dingwen Tao is an assistant professor in the School of Electrical Engineering and Computer Science at Washington State University. He received his Ph.D. in Computer Science from University of California, Riverside in 2018 and B.S. in Mathematics from University of Science and Technology of China in 2013. Prof. Tao works at the intersection of HPC and big data analytics, focusing on scientific data management, HPC storage and I/O systems, fault tolerance at extreme scale, and distributed machine learning. He has published in major HPC and big data analytics conferences and journals, such as SC, PPoPP, HPDC, ICS, PACT, IPDPS, Cluster, ICPP, BigData, and TPDS. He has created and developed several open-source scientific data compression tools, which have been world-widely used by many universities, DOE national laboratories, and industrial companies. He was the receipt of the IEEE Computer Society TCHPC Early Career Researchers Award for Excellence in High Performance Computing in 2020, NSF CRII Award in 2020, and the UCR Dissertation Year Program Award in 2017.
|PPoPP 2021|| POSTER: An Efficient Uncertain Graph Processing Framework for Heterogeneous Architectures|
POSTER: A Novel Memory-Efficient Deep Learning Training Framework via Error-Bounded Lossy Compression
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