Searching for Strong Lenses with Convolutional Neural Networks
Mentoring an undergraduate to a 98.1/100 score in the LSST Strong Lens Data Challenge
The Legacy Survey of Space and Time (LSST), conducted by the Rubin Observatory, will provide an unprecedented dataset for discovering strong gravitational lenses with its wide-field imaging capabilities and deep observations — far more systems than can be inspected by eye.
I mentored an undergraduate student in the LSST Strong Lens Data Challenge, which took place in fall 2025. We developed a convolutional neural network that scored 98.1/100, and the work was presented at the WashU Fall 2025 Undergraduate Research Symposium.
