Scholar
Xin Liang
Google Scholar ID: QRj1QroAAAAJ
University of Kentucky
Citations & Impact
Citations
2,914
H-index
29
i10-index
58
Publications
20
Co-authors
8
list available
Contact
Publications
Resume (English only)
Academic Achievements
- He has published in many highly competitive conferences and journals such as IEEE/ACM SC, ACM HPDC, ACM PPoPP, ACM ICS, IEEE IPDPS, ACM PACT, IEEE BigData, IEEE Cluster, IEEE TPDS, etc. He has received a Dissertation Year Fellowship (DYP) from UCR, two Best Paper Awards from IEEE Cluster, one Best Paper Finalist from ACM ICS, one Best Paper Award from IEEE IPDPS, one Best Paper Award from IEEE TBD, a CRII Award from the NSF, an EPSCoR Fellowship from the NSF, and a CAREER Award from the NSF. In 2024, he received the IEEE CS TCHPC Early Career Researchers Award For Excellence in High Performance Computing. While working at ORNL, he led the ESAMR project funded by the Director's Research and Development (DRD) program as principal investigator. He is one of the key developers of SZ and a major contributor to MGARD, which are widely used data reduction software in the scientific computing community.
Research Experience
- During his Ph.D. studies, he interned at the Extreme Scale Resilience Group and the Parallel Extreme-Scale Data Analytics Team at Argonne National Laboratory (ANL), the Scalable Machine Learning Group at Pacific Northwest National Laboratory (PNNL), and the Data Science at Scale Team at Los Alamos National Laboratory (LANL). Prior to joining the University of Kentucky, he worked as an assistant professor at Missouri University of Science and Technology and as a Computer/Data Scientist in the Workflow Systems Group at Oak Ridge National Laboratory (ORNL).
Education
- He obtained his Ph.D. in Computer Science from the University of California, Riverside, in 2019, and his B.S. in Computer Science from Peking University in 2014, with a minor in Math and Applied Math.
Background
- His research interests broadly cover high-performance computing, parallel and distributed systems, scientific data management, large-scale data analytics, and distributed machine learning. He received his B.S. in Computer Science from Peking University, with a minor in Math and Applied Math.
Miscellany
- He is always looking for self-motivated students to work on high-performance computing, scientific data management, and big data analytics. If you're interested in his research, please contact him at xliang@uky.edu.
