Xiang Ji

I am a postdoctoral researcher in Professor Sebastian Seung’s group at Princeton University. Previously, I received my Ph.D. in Physics and M.S. in Electrical Engineering from the University of California, San Diego, where I worked with Professor David Kleinfeld. My research combines advanced optical microscopy, computation, and biophysical theory to understand how the structure of biological networks gives rise to physiological and computational function.

Previously, I quantitatively studied brain vasculature at the system level, focusing on three major directions:

• Optical microscopy technqiues for organ-scale, high-resolution volumetric tissue imaging
  I developed an automated multiphoton microscopy platform for organ-scale, submicrometer-resolution 3D imaging of heterogeneous biological tissues.

• Scalable computational pipelines for multiscale quantification from 4D microscopy
  • I developed pipelines that transform hundreds of terabytes of volumetric microscopy data into whole-brain vascular connectomes, capturing the geometry, radii, and connectivity of millions of vessels with unprecedented completeness and precision.
  • I also developed a graph-constrained tracking algorithm that converts high-speed volumetric imaging of individual blood cells into quantitative measurements blood flow, making it possible to analyze fast flow dynamics across thousands of interconnected vessels in living mouse brains.
• Theory-driven analyses for turning measurements into principles
  I developed biophysical models that distill organizing principles from large-scale measurements, revealing how microvascular architecture enables robust metabolic support while imposing fundamental constraints on how blood flow can be controlled.

Now I am extending this perspective to biological neural networks. Using Drosophila as a model system, I am investigating how neuronal wiring diagrams enable visual computation.