Research

I have been working on the mathematical foundations of algorithms in 3-D computer vision and 3-D computational imaging. Recently my research has focused on Structure from Motion and Cryo-Electron Microscopy Imaging, which respectively asks to recover the 3-D structure of stationary scenes (e.g. Eiffel Tower) and macromolecules (e.g. Covid-19 spike protein) from their 2-D images. In these fields, I aim to develop fast and explainable algorithms that are robust to corrupted and noisy data, by leveraging advanced tools in computational geometry, algebra, statistics, signal processing and nonlinear optimization.

For prospective students, here is a list of courses that are relevant to my research:

• MAT 226: Numerical Methods
• MAT 235: Probability Theory
• MAT 258: Numerical Optimization
• MAT 270: Mathematics of Data Science
• MAT 271: Applied and Computational Harmonic Analysis
• STA 231: Mathematical Statistics
• ECS 174: Computer Vision
• ECS 231: Large-Scale Scientific Computation
• EEC 206: Digital Image Processing
• EEC 264: Estimation and Detection of Signals in Noise.