Panruo Wu

Panruo Wu is an Associate Professor in the Department of Computer Science at the University of Houston (UH). He joined UH in 2018 as an Assistant Professor and holds a Ph.D. in Computer Science from the University of California, Riverside, and a B.S. in Mathematics from the University of Science and Technology of China (USTC). His primary research interests include high performance computing, numerical algorithms, parallel and distributed computing, fault-tolerant systems, and big data analytics. He leads projects such as LATER (Linear Algebra on Tensor Cores) and LibKernel, focusing on accelerating numerical computations and kernel machines.

His recent work emphasizes optimizing linear algebra operations on emerging hardware accelerators like GPUs, with a focus on tensor cores and energy-efficient solvers. Key contributions include fault-tolerant matrix decompositions, scalable frameworks for serverless parallel computing (Wukong), and accelerating kernel machines (TensorSVM).

Awards include a Best Paper Nomination at HPDC'20. His teaching spans algorithms, parallel computing, and numerical analysis, with courses like COSC 3320 (Algorithms and Data Structures) and COSC 6374 (Parallel Computations). His research is supported by NSF Grant No. 2146509.