I am a PhD student in the Computing and Mathematical Sciences department at Caltech and advised by Professor Katie Bouman. Prior to my doctoral studies at Caltech, I was an undergrad at Carnegie Mellon University, where I recieved a B.S in Electrical and Computer Engineering with an additional major in Biomedical Engineering with Honors in December of 2018.

My primary research interests are in computational imaging. I am interested in methods that integrate physics-based models with data-driven approaches, which can be applied to a broad range of imaging domains from traditional computer vision to medical imaging.

Click here for a PDF of my CV.

News

June 2023 - I received the EAS New Horizons Award for my contributions at Caltech. Here’s the announcement.

June 2023 - Check out our work on image reconstruction without explicit priors, which I will be presenting on at ICASSP 2023!

June 2022 - Started an internship at Google Research.

May 2022 - Presented at SOCAMS on new work with Oscar, He, and Katie on learning image models from noisy data.

December 2021 - Attended AGU 2021, my first in-person conference!

September 2021 - DeepGEM: Generalized Expectation-Maximization for Blind Inversion accepted to NeurIPS 2021! Check out our project page.

April 2020 - Received Honorable Mention for the NSF GRFP.

October 2019 - Started my PhD at Caltech!

September 2019 - Participated in the Keck Institute for Space Studies workshop: Beyond Interstellar: Estracting Science from Black Hole Images

April 2019 - Received Honorable Mention for the NSF GRFP.

December 2018 - Graduated from Carnegie Mellon University with a B.S in Electrical and Computer Engineering and an additional major in Biomedical Engineering with University Honors.

November 2018 - Inducted into Tau Beta Pi.

September 2018 - Attended Grace Hopper Celebration for the first time.

August 2018 - Received the Mary Louise Brown Graham Memorial Scholarship for top undergraduate female students in engineering and science.