Published multiple papers including 'Miniscope3D: optimized single-shot miniature 3D fluorescence microscopy' in Nature LS&A, 'Spectral DiffuserCam: lensless snapshot hyperspectral imaging' and 'Deep learning for fast spatially-varying deconvolution' in Optica, and 'Physics-based learning for lensless imaging' in Optics Express.
Research Experience
Interned with Microsoft Research and Facebook Reality Lab; designed Miniscope3D, a miniature single-shot 3D fluorescence microscope; proposed Spectral DiffuserCam, a novel, compact, and inexpensive computational camera for snapshot hyperspectral imaging; developed MultiWienerNet, a deep learning-based approach for fast spatially-varying deconvolution; contributed to physics-based learning for lensless imaging projects.
Education
Graduated from UCLA in 2016 with a B.S. in Bioengineering, where he worked with Aydogan Ozcan on designing digital holographic microscopes for water-monitoring.
Background
Ph.D. candidate in Computational Imaging at UC Berkeley and UC San Francisco, advised by Laura Waller. His work combines optical design, convex optimization, and deep learning to achieve capabilities that are not possible with conventional imaging setups.