Join my group at Northwestern next year! Underrepresented and first-generation students can get application feedback by submitting their materials early (Nov 16), and all interested students should apply through the Computer Science program (Dec 15). More info here.
Thrilled to share that I'll be joining the Computer Science department at Northwestern University in March 2022!
VSS 2021 talk: Self-Motion Cues in the Natural Habitats of Zebrafish Support Lower Visual Field Bias -- A big thank you to VSS for the "travel" award covering conference fees.
Congratulations to my BAIR undergrad mentee Ellin Zhao for choosing UCLA for her PhD! It's a great fit for her combined passions for high-quality research and social impact.
Congratulations to my undergraduate mentee and ICCP coauthor Leyla Kabuli for receiving the NSF graduate research fellowship and for choosing Berkeley for her PhD! I'm so excited to see her future work.
Depth from Differential Defocus
Defocus reveals object location in cameras and microscopes. Inspired by the unique anatomy and behavior of the jumping spider, we explore differential defocus changes that enable efficient computation of depth, velocity, and phase. We develop a family of depth sensors for a variety of imaging settings, using standard cameras, deformable lenses, metalenses, and microscopes.
Best Student Paper ECCV 2016, Best Demo ICCP 2018
US Patent Application No. 62/928,929
ICCP 2021, PNAS 2019, Dissertation 2019, ICCP Demos 2018, IJCV 2017, ICCV 2017, ECCV 2016, ICCV Workshop 2015
Optic flow provides key motion cues, but the underlying brightness constancy constraint is often violated in real-world settings. We explore two kinds of mitigation strategies for brightness constancy violations: first, we show that explicit modeling of defocus-based violations can reveal depth and motion simultaneously; next, we explore spatial sampling techniques for robust self-motion estimation in generic and natural scenes, explaining biases found in larval zebrafish brains and behavior.
VSS 2021, ICCV 2017, ECCV 2016
Shape & Color
The human visual system explains pixel-to-pixel changes with a combination of material, geometric, and lighting-based explanations. We show that aligning color changes with shading cues disrupts shape perception, particularly around critical contours.
Interface Focus 2018, VSS 2013, VSS 2013
Teaching & Outreach
I am passionate about sharing the beauty of computational imaging and the math and science that make it work. As a recipient of the Harvard University Certificate of Distinction in Teaching, I have served as head TA for Harvard's undergraduate-level Introduction to the Theory of Computation (CS121) and Mathematical Methods in the Sciences (AM21b, a combined introduction to differential equations and linear algebra), and as a course TA for the graduate-level Computer Vision course (CS283). As an undergraduate, I spent several years as a course tutor for Yale's two-semester Fundamentals of Physics series, covering mechanics and electromagnetism (PHYS200, PHYS201).
In the wider community, I have taught introductory computer skills classes through Tech Goes Home and developed and taught content for elementary schoolers through Bay Area Scientists Inspiring Students.
I have mentored undergraduate students through their personal experiences of diversity and access through Harvard's Women in STEM and Women in Computer Science organizations, as well as through the Berkeley Artificial Intelligence Research undergraduate mentoring program. I have spoken at the Women Engineers Code conference and taught for ProjectCSGirls.