Dingwen Tao is an associate professor in the Department of Intelligent Systems Engineering at Indiana University, where he leads his research group, High-Performance Data Analytics and Computing (HiPDAC) Lab. Before joining IU, he worked as an assistant professor at Washington State University and University of Alabama between 2018 and 2022. Prior to that, he worked in the Computational Science Initiative (CSI) at Brookhaven National Laboratory, the Mathematics and Computer Science (MCS) Division at Argonne National Laboratory, and the High-Performance Computing (HPC) Group at Pacific Northwest National Laboratory. He is the recipient of various awards including NSF CAREER Award (2023), Amazon Research Award (2022), Meta Research Award (2022), R&D100 Awards Winner (2021), IEEE Computer Society TCHPC Early Career Researchers Award for Excellence in High Performance Computing (2020), NSF CRII Award (2020), IEEE CLUSTER Best Paper Award (2018), UCR Dissertation Year Program Award (2017). He is a Senior Member of ACM and IEEE.
Dingwen's research interests include high-performance computing (HPC), parallel and distributed systems, large-scale machine learning, scientific data management and visualization, fault tolerance and resilience, etc. He has published in the top-tier computing conferences and journals, including SC, ICS, HPDC, PPoPP, EuroSys, VLDB, DAC, AAAI, PACT, IPDPS, CLUSTER, ICPP, IEEE TC, IEEE TPDS, etc. He is currently an Associate Editor for IEEE Transactions on Paraellel and Distributed Systems (TPDS). He served as the Program Co-chair of 2021 IEEE International Conference on Scalable Computing and Communications (ScalCom), 9th Internation International Workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD), and Workshops on Big Data Reduction (IWBDR). He is also a reviewer, program committee member, or session chair of major HPC venues. His research has been supported by NSF, DOE, NOAA, Meta, Microsoft, AMD, ByteDance.