International Symposium on Computer Architecture · 2022
Cited
9
Resume (English only)
Academic Achievements
Published numerous papers in journals such as Science Advances, CVPRW, Optica, Biomedical Optics Express, IEEE TPAMI, covering topics like neural wavefront shaping for guidestar-free imaging, implicit neural representations for unsupervised turbulence mitigation, foveated thermal computational imaging using all-silicon meta-optics, real-time deep-learning aided lensless microscope, etc.
Research Experience
An Assistant Research Professor in Electrical and Computer Engineering at Rice University; part of the Digital Health Initiative, developing machine learning and imaging tools to reduce SWaP-C (size, weight, power, and cost) while improving performance in microscopy and medical imaging; a member of the Geometry, Light, & Imaging lab (GLEE lab).
Background
Assistant Research Professor, with research interests spanning computer vision, machine learning, applied optics, and nanofabrication. Current focus is on building end-to-end systems that integrate novel optics, sensors, and machine learning algorithms for applications in robotics, autonomous driving, wearables, medical sensing, machine vision, IoT, and virtual/augmented reality. Custom fabricated optics and chips are used to overcome limitations of traditional lenses and image sensors regarding size, weight, and functionality. Broadly, the research is in computational imaging, drawing from foundations of computer vision, computer graphics, machine learning, wave optics, photonics, and materials science.