Yu Wei (卫煜)

PhD student in CS


HASS 273

Purdue University, 305 N University Street

West Lafayette, Indiana

I am a third year PhD student at Purdue, and I currently study cryptography under the supervision of Professor Vassilis Zikas. Prior to that, I studied at Nankai University, China, where I obtained my master’s and bachelor’s degrees in Computer Science (supervised by Professor Zheli Liu) and a bachelor’s degree in Law (supervised by Professor Yingxia Tang). Regarding work, my passion lies in crafting tools and systems that establish rigorous practices for privacy/security in computation. I am particularly interested in exploring the intersection of machine learning, cryptography, and privacy.

My recent research focuses on developing generic tools for differential privacy analysis. I’m primarily interested in addressing the following question: How can one compute the tight privacy/utility-tradeoff spectrum for any randomized algorithm within a given class?. I am exploring this question through various lens and my goal is to create an easy-to-use privacy analysis toolset for domain experts who know how to extract useful information, but don’t know how to prove the extracted result preserves privacy.

I am also fortunate to work with researchers in various fields, including machine learning, symmetric key cryptography, multi-party computation (MPC), and game theory. It is a real pleasure for me to learn from and exchange ideas at any intersection of privacy and various disciplines. If you are interested in working with me, please do not hesitate to reach out. I am eager to exchange ideas and welcome your input :smile: .


selected publications

  1. S&P
    Eureka: A General Framework for Black-box Differential Privacy Estimators
    Yun Lu , Malik Magdon-Ismail , Yu Wei, and Vassilis Zikas
    In 2024 IEEE Symposium on Security and Privacy (SP) , May 2024
  2. Distributed Differential Privacy via Shuffling Versus Aggregation: A Curious Study
    Yu Wei, Jingyu Jia , Yuduo Wu , Changhui Hu , Changyu Dong , and 4 more authors
    Trans. Info. For. Sec., Jan 2024
  3. How to Make Private Distributed Cardinality Estimation Practical, and Get Differential Privacy for Free
    Changhui Hu , Jin Li , Zheli Liu , Xiaojie Guo , Yu Wei, and 3 more authors
    In USENIX Security Symposium , Jan 2021