A team member's work on AI for COVID-19 was chosen as a best abstract in the European Respiratory Conference; a paper on topological phase transitions was published in Nature Photonics.
Research Experience
Works at Princeton University's Department of Electrical Engineering; research areas cover microscopy, computational photography, and biomedical imaging.
Background
Research interests include optical hydrodynamics, statistical physics using incoherent light, and quantum optics. Focuses on optimizing imaging systems through computation, materials science, and digital technology.
Miscellany
Utilizes machine learning for classifying dynamics in physics and for determining disease, guiding treatment, and predicting patient outcomes in biomedical imaging, with contributions to the response against the COVID-19 pandemic.