Xin Xie

Xin Xie is a Schmidt AI in Science Postdoctoral Fellow affiliated with the Michigan Institute for Data & AI in Society (MIDAS) at the University of Michigan. Their research bridges topological photonics, deep learning, and quantum electrodynamics, focusing on designing novel states via topological optical structures and investigating light-matter interactions in 2D semiconductor materials.

• Education:
  • Ph.D. in Physics, Institute of Physics, Chinese Academy of Sciences (2022)
  • B.S. in Physics, Zhejiang University (2015)

Research interests center on topological photonics, leveraging deep learning to engineer optical structures and explore quantum phenomena like exciton-polariton transport and strong light-matter coupling. Their work integrates machine learning with quantum electrodynamics for applications in nanophotonics and quantum devices.

Recent publications highlight advancements in 2D photonic crystals, cavity Floquet engineering, and topological corner states, emphasizing their interdisciplinary approach combining theoretical physics, materials science, and AI-driven optimization.

• Scientific Awards:
  • Schmidt AI in Science Postdoctoral Fellowship
  • Michigan Data Science Fellowship
  • Postdoctoral Affiliates Program

Xin collaborates with mentors across multiple disciplines: Gongjun Xu (Statistics, Psychology), Hui Deng (Physics, EECS), and Yang Chen (Statistics). Contact via xiexin@umich.edu.