3/26/2018: Check out Zinan Lin's and Sewoong Oh's YouTube interview on our PacGAN paper.
10/2/2017: Zinan Lin was named a CMU Presidential Fellow for the 2017-2018 academic year. Congratulations, Zinan!
Cryptocurrencies have received a great deal of attention in recent years. I am interested in designing blockchain systems that account for fine-grained resource constraints in the network and in individual devices. This work ranges from protecting users' privacy to building faster consensus algorithms. A common theme in this work relies on explicitly modeling device or network behavior, and using these models to design more efficient algorithms with theoretical guarantees.
Generative adversarial networks (GANs) are a technique for learning a generative model from data. They have been tremendously successful at producing high-quality, sharp images. However, they are not well-understood. I am interested in studying the dynamics of GANs themselves, as well as using them for the release of privacy-preserving datasets.
Recent years have brought increasing levels of surveillance. I am interested in designing privacy-preserving algorithms that enable people to communicate freely without sacrificing privacy. I have been working on a few main problems within this theme, related to anonymous social media (e.g., Yik Yak, Secret) and anonymous peer-to-peer networks (e.g., Bitcoin, cryptocurrencies). A common theme in this work is that we wish to provide statistical anonymity guarantees against computationally-unbounded adversaries.
NextScholars (Mentor): Mentorship program for young women interested in STEM (2017-2018)
SEED (Mentor): Guided groups of Berkeley High School students in yearlong research projects on nuclear power, GMOs, and food deserts. (2012-2013)
TechBridge (Volunteer): Worked with groups of elementary-school girls on projects related to coding and basic electrical circuits. (2012-2014)