Summary
Jiajia Li is an assistant professor and research scientist with 11 years of experience specializing in numerical linear algebra and high-performance parallel computing for sparse matrix and tensor algorithms. She optimizes core kernels like SpMV, GEMM, TTM and MTTKRP across multicore, distributed CPUs and accelerators (GPU, Xeon Phi), often using architecture-aware tuning and auto-tuning techniques. Her work spans national lab and academic settings, including PNNL, William & Mary, and NC State, and includes internships at IBM and Intel focused on distributed and optimized sparse tensor operations. Trained in computer architecture (Ph.D., Institute of Computing Technology, CAS), she blends deep systems-level insight with practical performance engineering to accelerate scientific computing workloads.
11 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy (Ph.D.), Computer Architecture, Doctor of Philosophy (Ph.D.), Computer Architecture at Institute of Computing Technology, Chinese Academy of Sciences
Bachelor (As an Accelerated Student), Information and Computing Science, Bachelor (As an Accelerated Student), Information and Computing Science at Dalian University of Technology
English, Chinese