Research Profile¶
I'm Bryan Tan, a compiler engineer currently working in the industry. I graduated from UC Santa Barbara with a Master's degree in Computer Science in 2021. While I was at UCSB, I worked with Prof. Yu Feng on several research projects related to program verification for domain-specific languages. I currently work at Veridise, Inc., where I am involved in some research projects involving static analysis and formal verification of DSLs involving financial applications and zero knowledge proof circuits.
My research interests include type systems, program analysis, and program verification, especially in solving problems by applying domain-specific languages. I also have side interests in compiler construction techniques, program synthesis, and functional programming.
If you have any questions, feel free to email me at bryantan (AT) technius
(DOT) net.
Publications¶
My ORCID is: 0000-0002-4008-3846.
- J. Liu, et al., "Certifying Zero-Knowledge Circuits with Refinement Types," in 2024 IEEE Symposium on Security and Privacy (SP), San Francisco, CA, USA, 2024 pp. 81-81. doi: 10.1109/SP54263.2024.00078
- Junrui Liu, Yanju Chen, Bryan Tan, Isil Dillig, and Yu Feng. 2023. Learning Contract Invariants Using Reinforcement Learning. In Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering (ASE '22). Association for Computing Machinery, New York, NY, USA, Article 63, 1–11.
- Bryan Tan, Benjamin Mariano, Shuvendu K. Lahiri, Isil Dillig, and Yu Feng. 2022. SolType: Refinement Types for Arithmetic Overflow in Solidity. Proc. ACM Program. Lang. 6, POPL, Article 4 (January 2022), 29 pages.