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I am a 4th-year Ph.D. student at King Abdullah University of Science and Technology (KAUST), advised by Di Wang. I also work closely with Tianhao Wang at University of Virginia.
I earned my Bachelor's and Master's degree in Electrical Engineering at Shanghai Jiao Tong University (SJTU) IEEE Pilot Class . I worked on power electronics (specialized in hardware design and control theory) during that time.
I will be joining Prof. Yuan Tian's group as a postdoc at UCLA in 2025's summer.
My current research is on data privacy (specifically, differential privacy). I am interested in pushing the boundaries of differential privacy via principled approaches in various applications.
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Publications [= means equal contribution ]
Preprint
Revisiting Differentially Private Hyper-parameter Tuning
USENIX Sec'25
Privacy Audit as Bits Transmission: (Im)possibilities for Audit by One Run
34th USENIX Security Symposium
S&P'24
Preserving Node-level Privacy in Graph Neural Networks
45th IEEE Symposium on Security and Privacy
CSAW'24 Applied Research Competition Finalist
Science Advances
A privacy-preserving federated machine learning method protects patients' privacy in omic data
Science Advances, VOLUME 10, ISSUE 5, 2 FEB 2024
S&P'23
A Theory to Instruct Differentially-Private Learning via Clipping Bias Reduction
44th IEEE Symposium on Security and Privacy
SIGMOD'23
Practical Differentially Private and Byzantine-resilient Federated Learning
International Conference on Management of Data, 2023
AISTATS'23
Privacy-preserving Sparse Generalized Eigenvalue Problem
The 26th International Conference on Artificial Intelligence and Statistics
TKDE'23
Nearly Optimal Rates of Privacy-preserving Sparse Generalized Eigenvalue Problem
IEEE Transactions on Knowledge and Data Engineering, 2023