I'm a third-year Ph.D. student at Columbia University.
I am advised by Shree Nayar, and my work is
generously funded by the NDSEG fellowship.
Before my Ph.D., I worked with Aswin
Sankaranarayanan at CMU.
My research is in computational imaging.
I am interested in building vision systems the capture the minimal information needed to solve a task.
Previously, I have worked on structured light systems for 3D scanning and measuring fruit freshness.
We introduce a minimal sensing method to iteratively orient a solar panel toward the optimal orientation in any lighting environment,
regardless of the complexity of the illumination.
UrbanSky consists of 1,067 outdoor HDR lighting environments in New York City. At each location, we capture
the illumination using a 360° camera, we measure the global horizontal irradiance, and we record the capture date,
time of day, location, and current weather conditions.
A minimalist camera captures the smallest number of measurements needed to solve a task. Rather than
using square pixels, a minimalist camera uses freeform pixels whose shape are automatically learned
for the task at-hand.
We introduce a low-bandwidth method for 3D scanning with position sensing diodes that is robust to
global illumination.
Fine-Grain Prediction of Strawberry Freshness Using Subsurface Scattering Jeremy Klotz,
Vijay Rengarajan, and
Aswin C. Sankaranarayanan ICCV Workshop on Large-Scale Fine-Grained Food AnalysIs (LargeFineFoodAI), 2021
paper, video, code
We show subsurface scattering measurements are useful for predicting fruit freshness.