I am a young passionate researcher with a broad interest in privacy and security including differential privacy, applied cryptography, programming language theory, robust machine learning and blockchain system. I am now a PhD student in the EECS department of UC Berkeley, advised by Prof. Dawn Song. I am fortunate to work closely with Prof. Joseph Near and Prof. Xinyu Xing. I am a member of RISE Lab and Initiative for Cryptocurrencies & Contracts (IC3). I got my Bachelor's degree from Peking University, Beijing, China.

• Our paper "Towards practical differentially private causal graph discovery." is accepted by Neurips 2020.
  

• Towards practical differentially private causal graph discovery. [code]
  Lun Wang, Qi Pang, Dawn Song.
  NeurIPS 2020: Proceedings of The 34th Annual Conference on Neural Information Processing Systems. (Acceptance rate: 1900/9454=20.1%)
• TABOR: A highly accurate approach to inspecting and restoring trojan backdoors in AI systems.
  Wenbo Guo*, Lun Wang*, Xinyu Xing, Min Du, Dawn Song.
  ICDM 2020: 20th IEEE International Conference on Data Mining. (Acceptance rate: 91/930=9.8%)
• 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.
• Towards practical differentially private convex optimization. [code]
  Roger Iyengar*, Joseph Near*, Dawn Song*, Om Thakkar*, Abhradeep Thakurta*, Lun Wang*.
  S&P'19: 2019 IEEE Symposium on Security and Privacy. (Acceptance rate: 12%)

• SPAI 2020: Program Committee
• PoPETS 2020: External Reviewer