James L. Carmon Scholarship
Jason Terry, a Ph.D. student in the Department of Physics and Astronomy, is developing technologies that could revolutionize interpretations of telescope data. Recent generations of powerful telescopes, such as the James Webb Space Telescope, offer fresh information about the regions where exoplanets (planets outside of our solar system) form. Unfortunately, an exoplanet might be engulfed by dust or other obscuring phenomena, leaving traces in telescope images so subtle that the human eye might not notice or understand them. To address this gap, Terry will use existing astronomical images and high-performance computational resources to generate thousands of simulations of the regions where exoplanets form. He will use simulations to train machine-learning algorithms to help scientists detect exoplanets from real observations and answer new astronomical questions. This research will offer a novel method to estimate masses and locations of exoplanets and change how we search for and characterize them.
James L. Carmon Scholarship Honorable Mention
Benjamin Taylor, an M.S. candidate in the Odum School of Ecology, investigates how ants acquire, retain and retrieve information as a group. Because animal groups often face the same tasks repeatedly, their decisions in foraging and other behaviors could benefit collective learning based on experience. His research explores whether members of a colony of the ant Temnothorax rugatulus can pass information among individuals and progressively improve group performance in foraging over time. Taylor attaches miniature tags to multiple individuals and films them using high-resolution cameras, then deploys the high-resolution video data and advances in computer vision and other technologies to fine-scale track animal movements. He plans to use new analytical approaches to quantify and discriminate between various movement tracks of individual members and groups of ants under different experimental manipulations. The results of his research could advance understanding of collective problem-solving in animal and human societies, potentially with AI applications.