Emma Alexander

ealexander@berkeley.edu

Google Scholar

CV


I'm interested in low-level, physics-based, bio-inspired artificial vision.

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.

News

August 2021

Thrilled to share that I'll be joining the Computer Science department at Northwestern University in March 2022!

June 2021

I co-organized the virtual CVPR Computational Cameras and Displays Workshop on June 20. You can check out the talks here.

May 2021

ICCP 2021 talk: Depth from Differential Defocus as a Special Case of the Transport of Intensity Equation

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.

April 2021

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.

I gave the UCLA/Caltech Grundfest Memorial Lecture on differential defocus in photography and microscopy – recording available on the project page.

Research

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

[TIE project page] [metalens project page] [focal track project page] [focal flow project page]

[dissertation]

[media coverage 1 2 3 4 5 6 7]

Motion Estimation

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

[zebrafish project page] [focal flow project page]

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

[project page] [paper]

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.

As part of the Waller lab, I led undergraduate and rotation student projects, leading to an undergraduate-coauthored ICCP paper.