Rate My Professor Yan Gu
Ratings & reviews
Creates a welcoming and inclusive environment.
Always positive and motivating in class.
Always prepared and organized for students.
I truly appreciated how approachable and understanding you were. You made it easy to ask for help and always responded with kindness.
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About Yan
Yan Gu is an Associate Professor in the Computer Science and Engineering Department at the University of California, Riverside, a position he has held since January 2020. He received his Ph.D. in Computer Science from Carnegie Mellon University in September 2018, where he was advised by Professor Guy Blelloch and completed a thesis entitled 'Write-Efficient Algorithms.' Gu earned his Bachelor’s degree in Computer Science from Tsinghua University in July 2012, receiving the Outstanding Bachelor Thesis Award and the Outstanding Graduates Award. After his doctorate, he served as a Postdoctoral Associate in Carnegie Mellon University’s Computer Science Department from October to December 2018 under Guy Blelloch, followed by a Postdoctoral Associate position at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) from January to December 2019, supervised by Julian Shun.
Gu’s research specializes in designing efficient parallel algorithms for processing large-scale data with strong practical performance guarantees. His academic interests encompass shared-memory parallel algorithms for core problems in graphs and geometry, such as stepping algorithms for shortest paths, biconnectivity labeling, parallel convex hull and Delaunay triangulation, spatial partitioning data structures, and parallel tree structures including priority queues and range search trees. He also develops algorithms tailored to emerging hardware architectures, including processing-in-memory (PIM) systems, non-volatile memories (NVRAM) for write reduction, and space-efficient algorithms leveraging limited fast memory like DRAM. Gu’s contributions have earned prestigious recognitions, including the NSF CAREER Award in 2024 for the project 'Efficient Algorithms for Modern Computer Architecture,' which addresses memory bandwidth and size challenges; the Google Research Scholar Award in 2024; Outstanding Paper Award at SPAA 2024; Best Paper Awards at ESA 2023 and PPoPP 2023; Best Paper Runner-Up (Technical Paper) at VLDB 2023; and Outstanding Paper Award at SPAA 2020. Notable publications include 'Provably Fast and Space-Efficient Parallel Biconnectivity' (PPoPP 2023, Best Paper Award, with Xiaojun Dong, Letong Wang, and Yihan Sun); 'Efficient Parallel Output-Sensitive Edit Distance' (ESA 2023, Best Paper Award, with Xiangyun Ding, Xiaojun Dong, Youzhe Liu, and Yihan Sun); 'Parallel Integer Sort: Theory and Practice' (PPoPP 2024, with Xiaojun Dong, Laxman Dhulipala, and Yihan Sun); 'Optimal Parallel Algorithms in the Binary-Forking Model' (SPAA 2020, Outstanding Paper Award, with Guy E. Blelloch, Jeremy T. Fineman, and Yihan Sun); and 'Parallel and (Nearly) Work-Efficient Dynamic Programming' (SPAA 2024, with Xiangyun Ding and Yihan Sun). His work advances parallel computing theory and practice for modern systems.
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