CV

Education

• Ph.D in Electrical and Computer Engineering, University of Michigan, Ann Arbor, Incoming
  • Advisors: Jun Gao, Qing Qu
  • Interests: reconstructing, generating and simulating 3D worlds, Computational Imaging, 3D modeling, etc.
• B.S. in Physics, Peking University, Present
  • Interests: Probabilistic Machine Learning, Diffusion Models etc.

Work experience

• Summer 2024: Intern in University of Michigan, Ann Arbor
  • Lead the ML for scientific application project in Qing’s group, the main project is to use the generative models to model and predict chaotic dynamic systems like fluids and use it to solve real-world problems, we primarily focus on the data assimilation task.
  • Introduce the current research projects in various seminars and symposiums, like IMSI workshop, CSP seminar etc.

Publications

FlowDAS: A Stochastic Interpolant-based Framework for Data Assimilation

Siyi Chen*, Yixuan Jia*, Qing Qu, He Sun, Jeffrey A Fessler. (2025). "FlowDAS: A Stochastic Interpolant-based Framework for Data Assimilation." CPAL. 2025.

Learning Diffusion Model from Noisy Measurement using Principled Expectation-Maximization Method

Weimin Bai, Weiheng Tang, Enze Ye, Siyi Chen, Wenzheng Chen, He Sun. (2024). "Learning Diffusion Model from Noisy Measurement using Principled Expectation-Maximization Method." ICASSP. 2024.

LatentDEM: Blind Inversion using Latent Diffusion Priors

Weimin Bai*, Siyi Chen*, Wenzheng Chen, He Sun. (2024). "LatentDEM: Blind Inversion using Latent Diffusion Priors." Arxiv. 2024.