Summary
Xin Liang is a tenure-track Assistant Professor of Computer Science at the University of Kentucky with 11 years of experience spanning academia and national labs. He earned a Ph.D. from UC Riverside and a B.S. from Peking University, and has applied his research on fault tolerance, lossy compression, and extreme-scale machine learning at Argonne, PNNL, LANL, and Oak Ridge. Xin blends systems-level expertise in HPC, I/O reduction, and energy-efficient algorithms with practical work on containerization and in-situ ML visualization, often optimizing scientific workflows for production at scale. Before returning to academia he worked as a computer/data scientist at ORNL and briefly taught and researched at Missouri S&T, giving him a strong track record of translating lab-scale innovations into deployable tools. His background uniquely pairs deep algorithmic thinking with hands-on performance engineering across CPU/GPU heterogeneous systems.
11 years of coding experience
5 years of employment as a software developer
Bachelor of Science (B.S.), Computer Science, Bachelor of Science (B.S.), Computer Science at Peking University
Doctor of Philosophy (PhD), Computer Science, Doctor of Philosophy (PhD), Computer Science at University of California, Riverside