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Lun Wang
I am a research scientist at Google, working on privacy-preserving machine learning. I received my PhD degree in computer science from UC Berkeley, advised by Prof. Dawn Song in summer 2022. Before that, I received my Bachelor's degree from Peking University in computer science in fall 2018.
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2023
- PATROL: Provable Defense against Adversarial Policy in Two-player Games
Wenbo Guo, Xian Wu, Lun Wang, Xinyu Xing, Dawn Song
Usenix 2023: 32nd USENIX Security Symposium.
- Why Is Public Pretraining Necessary for Private Model Training?
Arun Ganesh, Mahdi Haghifam, Milad Nasr, Sewoong Oh, Thomas Steinke, Om Thakkar, Abhradeep Thakurta, Lun Wang. (Authors are ordered alphabetically.)
ICML 2023: Fortieth International Conference on Machine Learning. (Acceptance rate: 1827/6538=27.9%)
- Secure Federated Correlation Test and Entropy Estimation
Qi Pang*, Lun Wang*, Shuai Wang, Wenting Zheng, Dawn Song.
ICML 2023: Fortieth International Conference on Machine Learning. (Acceptance rate: 1827/6538=27.9%)
PPAI Workshop @ AAAI 2022: The Third AAAI Workshop on Privacy-Preserving Artificial Intelligence.
- Byzantine-Robust Federated Learning with Optimal Rates and Privacy Guarantee [code]
Banghua Zhu*, Lun Wang*, Qi Pang*, Shuai Wang, Jiantao Jiao, Dawn Song, Michael I.Jordan.
AISTATS 2023: Artificial Intelligence and Statistics 2023. (Acceptance rate: 29%)
SpicyFL @ Neurips 2020: NeurIPS Workshop on Scalability, Privacy, and Security in Federated Learning.
2022
- Differentially Private Fractional Frequency Moments Estimation with Polylogarithmic Space
Lun Wang, Iosif Pinelis, Dawn Song.
ICLR 2022: the 10th International Conference on Learning Representations. (Acceptance rate: 1095/3391=32.3%))
PPAI Workshop @ AAAI 2022: The 3rd AAAI Workshop on Privacy-Preserving Artificial Intelligence.
TPDP Workshop @ ICML 2022: Theory and Practice of Differential Privacy.
- PRIVGUARD: Privacy Regulation Compliance Made Easier
Lun Wang, Usmann Khan, Joseph Near, Qi Pang, Jithendaraa Subramanian, Neel Somani, Peng Gao, Andrew Low, Dawn Song.
Usenix Security'22: the 31th Usenix Security Symposium. (Acceptance rate: 18%)
2021
2020
2019
- CHURP: Dynamic-committee proactive secret sharing. [project page]/[code]
SKD Maram, Fan Zhang, Lun Wang, Andrew Low, Yupeng Zhang, Ari Juels, Dawn Song.
CCS'19: Computer and Communications Security 2019. (Acceptance Rate: 149/934=16.0%)
- DUET: An expressive higher-order language and linear type system for statically enforcing differential privacy. [code]
Joseph Near, David Darais, Chike Abuah, Tim Stevens, Pranav Gaddamadugu, Lun Wang, Neel Somani, Mu Zhang, Nikhil Sharma, Alex Shan, Dawn Song.
OOPSLA'19: Proceedings of the ACM on Programming Languages, 2019. Distinguished Paper Award. (2.5% of all submissions)
- Towards practical differentially private convex optimization. [code]
Roger Iyengar, Joseph Near, Dawn Song, Om Thakkar, Abhradeep Thakurta, Lun Wang. (Authors are ordered alphabetically.)
Oakland'19: 2019 IEEE Symposium on Security and Privacy. (Acceptance rate: 12%)
- A generic technique for sketches to adapt to different counting ranges.
Tong Yang, Jiaqi Xu, Xilai Liu, Peng Liu, Lun Wang, Jun Bi, Xiaoming Li.
INFOCOM'19: IEEE Conference on Computer Communications.
Service
- Journal Reviewer: Journal of Causal Inference, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Dependable and Secure Computing, Transactions on Machine Learning Research, Frontiers in Computer Science
- Conference Reviewer: ITCS 2023, RANDOM 2023, AISTATS 2022-2023, ICML 2021-2023, ICLR 2022-2023, Neurips 2021-2023, CCS 2021/2023, WWW 2021, ECML-PKDD 2021, PoPETS 2021-2024
- Program Committee: CCS 2023, FL @ ICML 2023, SPAI 2020, WNA 2020
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