Xi Chen (陈熹)

I am a Ph.D. student at the Electrical and Computer Engineering Department of Rutgers University, advised by Shirin Jalali. My research lies at the intersection of generative models, high-dimensional statistics, information theory, and inverse problems. I study how structural properties including sparsity, low-dimensional geometry, and generative priors enable representation, compression, and recovery of high-dimensional data.

My work connects classical ideas from random projections, structured signal models, and statistical inference with modern generative frameworks such as diffusion models, VQ-VAEs, and discrete/tokenized representations. I am particularly interested in the statistical behavior and information-theoretic limits of compression and recovery, as well as scalable approximation and optimization algorithms that bridge theoretical guarantees with real-world imaging, sensing, communication, and intelligent systems.

I received my M.Sc. degree in Data Science from Tufts University, worked with Mike Hughes and Liping Liu, and B.Sc. degree in Electrical Engineering from Beijing Institute of Technology, worked with Jie Tian.

Email: firstname.chen15 [at] rutgers [dot] edu

Please feel free to reach out if you want to discuss or collaborate on research!