I am an Associate Professor in the Department of Computer Science and Engineering (CSE) at the University of California, Riverside (UCR), where I have been on the faculty since 2020.
Prior to joining UCR, I was a postdoctoral associate at MIT CSAIL in 2019, working with Julian Shun. I obtained my Ph.D. in Computer Science from Carnegie Mellon University in 2018, advised by Guy Blelloch, and my Bachelor’s degree in Computer Science from Tsinghua University in 2012. You can find my [CV] here.
My current research focuses on designing efficient parallel algorithms for large-scale data with strong theoretical guarantees and practical performance. Learn more about our research group at the Parallel Algorithms Lab (PAL).
We always welcome highly self-motivated students to join our group. However, due to high inquiry volume, we only have very limited openings each year for Ph.D. positions, Master’s projects/theses, undergraduate research, and summer internships.
- For current UCR students (undergraduate or graduate): Please ensure you have taken CS 214 (Parallel Algorithms) and performed well.
- For prospective students: Please fill out this interest form and send me an email. This is particularly important for Ph.D. applicants, as we may not always review the general application pool.
Additional details can be found regarding [recruiting] and guidelines for requesting a [recommendation letter].
For course information, please refer to my teaching page.
This is the homepage of my lovely wife.
View my publication list:
A full list of my publications can be found here.
Research Interests and Selected Topics
Research
My research lies broadly in parallel computing, algorithm design and implementations, with a focus on developing efficient algorithms and data structures for large-scale data processing. Our work spans both algorithm theory and practical efficiency on modern systems, aiming to bridge the gap between theoretical upper bounds and real-world performance.
Our group works on a wide range of topics, including:
- Parallel Algorithms & Data Structures: Graph processing, spatial/geometric computing, concurrent data structures, and randomized incremental algorithms.
- Algorithm-Architecture Co-design: Write-efficient algorithms for non-volatile memory (NVRAM), space-efficient in-memory computing, Processing-in-Memory (PIM), and algorithm design for emerging architectures.
Selected publications grouped by topics can be found below:
- [Parallel Graph Algorithms]
- [Parallel Geometric Algorithms]
- [Parallel Data Structures]
- [Parallel Incremental Algorithms]
- [Write-Efficient Algorithms]
- [Space-Efficient Algorithms]
- [PIM & Emerging Architectures]