Suyan Qu
suyan (at) cs.wisc.eduSearching the Unknown - Alistair Sung
Research
My research interest lies in computer systems, especially storage systems and distributed systems. This includes consensus problems, serverless systems, blockchain technology, cloud storage infrastructures, database systems, machine learning systems, storage data structures, filesystems, etc. This field is too fantastic to miss out anything ¯\_(ツ)_/¯.
My current research focuses on analyzing and improving the performance of blockchain systems, specifically on the core consensus algorithm, the data model, and the storage engine. I built CBox, an emulation tool to study blockchain performance at scale. I worked on Firewood to build a faster authenticated storage system during my internship at Ava Labs. Currently, I am looking at improving intra-block parallel execution efficiency.
Before blockchains, my colleagues and I worked on building filesystems tailored towards persistent memories and improving stateful serverless functions through co-designing the compute and storage infrastructures.
Publications
- Chain-in-the-Box: Large-scale Blockchain Prototyping on a Single Machine. Suyan Qu, Andrea Arpaci-Dusseau, Remzi Arpaci-Dusseau. To appear in Financial Cryptography and Data Security 2026.
- Data-Centric Serverless Computing with LAMBDASTORE. Kai Mast, Suyan Qu, Aditya Jain, Andrea Arpaci-Dusseau, and Remzi Arpaci-Dusseau. Software 2026, 5, 5.
- MadFS: Per-File Virtualization for Userspace Persistent Memory Filesystems. Shawn Zhong, Chenhao Ye, Guanzhou Hu, Suyan Qu, Andrea Arpaci-Dusseau, Remzi Arpaci-Dusseau, and Michael Swift. 2023. In Proceedings of the 21th USENIX Conference on File and Storage Technologies (FAST ‘23). USENIX Association.