Sheng Di received his Ph.D. from the University of Hong Kong in 2011 (certificated in 2012). He was a postdoctoral fellow at INRIA, where he worked on workload/hostload prediction for Google data centers and optimization of resource allocation. He is now a computer scientist in the mathematics and computer science (MCS) division of Argonne National Laboratory.  His current research interest includes lossy compression for scientific datasets, high performance computing, scalable computing, and fault tolerance. He is a senior member of IEEE, institute fellow of NAISE, also the scientist at Large through the Consortium for Advanced Science and Engineering (CASE) at the University of Chicago.

He is the DOE 2021 Early Career Research Program Award Winner, and also the recipient of 2018 IEEE-Chicago Distinguished Mentoring Award and 2019 IEEE-Chicago Distinguished R&D Award.

Research Interests

• Scientific data compression
• Fault tolerance
• Cloud/grid computing
• High-performance computing
• Optimization