Welcome to the Ganapati Lab

We are a research group in the Swarthmore College Engineering Department. Our focus is creating physics-based machine learning algorithms for computational imaging systems. Examples of computational imaging include computed tomography (CT) and LED array microscopy, where hardware and software are co-designed to enable enhanced capability such as 3D imaging. However, these advanced features come at the cost of long acquisition times. In our group, we create data-driven design methods for computational imaging systems to improve temporal resolution, enabling scientific discovery in previously inaccessible regimes.

Students in lab

Our research is interdisciplinary, drawing from physics, optimization, machine learning, and signal processing. We collaborate with the Swarthmore College Biology Department, co-located with us in Singer Hall, using Fourier ptychography to visualize microscopic phase objects such as planarians, sea urchins, and human cells. We also collaborate with Lawrence Berkeley National Laboratory to improve micro-computed tomography.

2018 team picture

We are always looking for motivated Swarthmore undergraduates to join our team! (more info)

We are grateful for support from the National Science Foundation, Swarthmore College, the U.S. Department of Energy’s Office of Science, Janelia Research Campus, and the American Association for University Women.


July 2023

Our research is featured in a press release by Optica and on Phys.org.

June 2023

Our work Self-Supervised Deep Learning for Model Correction in the Computational Crystallography Toolbox is accepted to the 1st workshop on Synergy of Scientific and Machine Learning Modeling, International Conference on Machine Learning (ICML) 2023.

May 2022

Rey is awarded the McCabe Award, Swarthmore Engineering’s highest distinction.

April 2023

Vidya receives National Science Foundation CAREER award.

April 2023

Vidya presents poster on Cool Cameras for Science at the Reverse Science Fair at Willard Middle School.

October 2022

NeurIPS 2022 Machine Learning and the Physical Sciences Workshop paper A Self-Supervised Approach to Reconstruction in Sparse X-Ray Computed Tomography accepted, co-authored by Rey, Minh, and Judith.

October 2022

NeurIPS 2022 AI for Science Workshop paper Data-Driven Computational Imaging for Scientific Discovery accepted, co-authored by Yolanda and Andrew.

September 2022

Vidya on leave from Swarthmore to design machine learning algorithms for time-resolved serial femtosecond crystallography in the Sauter Group at Lawrence Berkeley National Laboratory. Swarthmore undergraduates interested in research opportunities should get in touch!

September 2022

Rey featured in an article about summer research at Berkeley Lab.

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