A lens brings a single plane into focus on a planar sensor; hence, parts of the scene that are outside this planar focus plane are resolved under defocus. Can we break this precept by enabling a “lens” that can change its depth of field arbitrarily? This work investigates the design and implementation of such a computational lens with spatially- selective focusing. Our design uses an optical arrangement of a Lohmann lens and a phase-only spatial light modulator to allow each pixel to focus at a different depth. We extend classical autofocusing techniques to the spatially-varying scenario where the depth map is iteratively estimated using contrast and disparity cues, enabling the camera to progressively shape its depth-of-field to the scene’s depth. By obtaining an all-in-focus image optically, our technique advances upon prior work in two key aspects: the ability to bring an entire scene in focus simultaneously, and the ability to maintain the highest possible spatial resolution.
Speaker's Bio
Yingsi is a PhD candidate in Electrical and Computer Engineering at Carnegie Mellon University, advised by Prof. Aswin Sakaranarayanan and Prof. Matthew O’Toole. Her research focuses on designing and building next-generation computational imaging and 3D display systems. By integrating computer vision, optics, signal processing, and machine learning, she creates new approaches to capture, process, and visualize three-dimensional information for mixed reality and machine vision applications. Yingsi's work has been recognized with the Best Paper Award at SIGGRAPH 2023, the Best Demo Award at ICCP 2023, and the Best Paper Honorable Mention Award at ICCV 2025. Yingsi is also a recipient of the Tan Endowed Graduate Fellowship and the James Sprague Presidential Fellowship at Carnegie Mellon University.
Prior to CMU, Yingsi obtained her Bachelor of Science in Computer Science from Columbia University and her Bachelor of Arts in Physics from Colgate University. She was a research intern at Meta Reality Labs in the Display Systems Research team (2024, 2025) and Snap Research in the Computational Imaging team (2020). She was also a software engineering intern at Google Search (2019).