About me

This is Anshunkang Zhou’s homepage! I am a Ph.D student at the Hong Kong University of Science and Technology, advised by Prof. Charles Zhang. My research focuses on enhancing software security through both dynamic and static techniques, such as fuzzing (S&P’24) and binary analysis (ASPLOS’24, ASPLOS’25, TOSEM’24).

Award

• Huawei Distinguish Collaborator, 2022

Publication

(* corresponding author)

ISSTA’25

KRAKEN: Program-Adaptive Parallel Fuzzing Anshunkang Zhou, Heqing Huang^*, Charles Zhang The 34th ACM SIGSOFT International Symposium on Software Testing and Analysis.

ASPLOS’25

Manta: Hybrid-Sensitive Type Inference Toward Type-Assisted Bug Detection for Stripped Binaries
Chengfeng Ye, Yuandao Cai^*, Anshunkang Zhou, Heqing Huang, Hao Ling, Charles Zhang ACM Conference on Architectural Support for Programming Languages and Operating Systems

ASPLOS’24

Plankton: Reconciling Binary Code and Debug Information
Anshunkang Zhou, Chengfeng Ye, Heqing Huang^*, Yuandao Cai, Charles Zhang.
ACM Conference on Architectural Support for Programming Languages and Operating Systems

S&P’24

Everything is Good for Something: Counterexample-Guided Directed Fuzzing via Likely Invariant Inference
Heqing Huang, Anshunkang Zhou, Mathias Payer, Charles Zhang.
The 45th IEEE Symposium on Security and Privacy.

TOSEM’24

ARCTURUS: Full Coverage Binary Similarity Analysis with Reachability-guided Emulation
Anshunkang Zhou, Yikun Hu^*, Xiangzhe Xu, Charles Zhang.
The 45th IEEE Symposium on Security and Privacy.