Published multiple papers in top-tier computer architecture/system conferences/journals, including ASPLOS, DAC, TCAD, and NeurIPS. Some representative publications include:
- TensorTEE: Unifying Heterogeneous TEE Granularity for Efficient Secure Collaborative Tensor Computing (ASPLOS 2024)
- Alchemist: A Unified Accelerator Architecture for Cross-Scheme Fully Homomorphic Encryption (DAC 2024)
- Real-Time Robust Video Object Detection System Against Physical-World Adversarial Attacks (TCAD 2023)
- ScaleCert: Scalable Certified Defense against Adversarial Patches with Sparse Superficial Layers (NeurIPS 2021)
Research Experience
Conducted research work under the supervision of his advisors during his Ph.D. studies at the Institute of Computing Technology, Chinese Academy of Sciences.
Education
Ph.D. Candidate, Institute of Computing Technology, Chinese Academy of Sciences, 2020-Present; B.S., Department of Automation, Tsinghua University, 2016-2020; Supervisors: Prof. Qi Guo, Xing Hu, Yunji Chen.
Background
Research Interests: Computer architecture, system security, deep learning systems, and domain-specific accelerators. Particularly focused on building secure and efficient neural network computing systems.