James L. Carmon Scholarship Award

The James L. Carmon Award is presented to University of Georgia graduate students who have used computers in innovative ways. Named for the late James L. Carmon, a UGA faculty member for 36 years who helped make the university a leader in computer research and development, the award was established by the Control Data Corp. Each year, graduate students may be selected as Carmon Scholars or for Honorable Mention.

2018 Recipients

Erin Baker, a doctoral student in genetics, is studying the molecular mechanisms governing thymus aging that could be used to treat disease and improve regenerative therapies. The thymus, which plays a crucial role in immune system function, is the organ where T cells proliferate, differentiate and mature. During fetal stages, T-cell proliferation in the thymus increases rapidly as the organ expands in size. But as people reach adulthood, the thymus loses mass and output of specialized T cells, increasing the body’s predisposition to disease and infection. Baker is employing novel mapping technologies to discover and characterize the molecular mechanisms that control this transition from the fetal expansion phase to the adult maintenance phase. If clinicians could use this knowledge to stimulate T-cell production in immunocompromised patients, debilitating if not deadly conditions—including various cancers and infectious diseases—could potentially become less virulent and even treatable.

Andreas Copan, a doctoral student in chemistry, has consistently shown himself to be self-motivated, highly talented and perceptive in identifying important problems. In his years at UGA, he has developed a deep understanding of molecular electronic structure theory and wide-ranging experience in computer programming and numerical algorithms. With this combination of skills, Copan has shown how to generalize density cumulant theory for the description of electronic excited states. Researchers can use this new model to predict the spectroscopic signature of a molecule, facilitating its identification. He also created a stand-alone software package that optimizes tensor contractions and improves numerical algorithms for large matrices to increase the range of chemical systems that can be modeled with this theory. These ideas contributed to a successful research proposal recently funded by the National Science Foundation.

Past Recipients