Xiaoyi Lu is an associate professor in the Department of Computer Science and Engineering at the University of California, Merced, where he leads the Parallel and Distributed Systems Laboratory (PADSYS Lab). His research interests include parallel and distributed computing; scalable and efficient systems for high-performance computing (HPC), big data, artificial intelligence (AI), cloud and edge computing; high-performance communication and input-output (I/O) technologies (e.g., RDMA, NVMe, GPU, DPU); scalable algorithms and applications; and interdisciplinary research for social good.
Lu has published over 170 papers in prestigious conferences and journals, receiving 10 best (student) paper awards or nominations, including at SC 2019 and IPDPS 2024. He has delivered more than 100 invited talks, tutorials and presentations worldwide and is actively involved in the academic community. His research outputs, including OpenDOTA, SR-APPFL, PMIdioBench, HiBD, MVAPICH2-Virt and DataMPI, have made a broad impact across both industry and academia.
Lu has received notable honors, including the National Science Foundation (NSF) CAREER Award and research awards from Amazon, Google and Meta/Facebook.
Research interests: parallel and distributed computing, deep learning systems, digital twin systems, big data management