Grad Student Promise Recognized by NSF

STUDENT SUCCESS | Graduate students are key partners in the research enterprise of the University of Vermont. Its success both fosters and grows from their spirit of inquiry. This spring, four UVM graduate students were awarded prestigious National Science Foundation (NSF) Graduate Research Fellowships. Here are brief views of their groundbreaking work.

Searching for Resilience to Sea Star Wasting Disease

Sea stars, like humans, normally have a healthy community of microbes on their skin that serve as “the first line of defense” against pathogens or microbes that might try to enter the body, explains Andrew McCracken, a Ph.D. student who studies how animals adapt to deal with stressors in their environments. Problems occur when those natural microbial communities are disrupted and opportunistic microbes move in. And environmental stressors may topple the community altogether. Since 2013, sea star wasting disease (SSWD) has wiped out about 90 percent of the giant sea stars along the West Coast. McCracken was awarded an NSF Graduate Research Fellowship to see if populations might be able to rebound. He will run a metagenomics test to identify bacteria that significantly increase with SSWD and investigate how resilient populations may be over time and under various conditions.

Adding Up the Numbers on Brain Health and Power Grids

From the orbits and rotations of the planets in our solar system to the machines that influence our daily lives: it’s mathematics all the way down. Tobias Timofeyev, a doctoral student in UVM’s College of Engineering and Mathematical Sciences, was awarded an NSF Graduate Research Fellowship to use mathematical biology to study and model the neuronal connections in the human brain. The majority of neurons in the brain are excitatory, activating the electrical current that run’s through everyone’s brains. Inhibitory neurons restrict that flow and make other neurons less likely to send signals of their own. “I’m looking at models of regions in the brain and understanding how the fibers connecting them should impact the voltage of other regions,” Timofeyev says. A common approach to modelling such activity might involve super computers. Timofeyev, however, is extracting models from complex mathematical equations.

Uncovering the Digital Footprints of Anxiety in Young Children

Right now, your smartphone—part texting device, part camera, mostly digital oracle—is collecting data. Where you go. The number of steps it takes to get there. Elevation climbed. Your phone listens for you to speak to Siri, the angel of search. Data is gathered as we traipse around the Internet, inadvertently dropping cookie crumbs behind. Big data adds up. But how can it all become individually useful? For Bryn Loftness, a doctoral student in the University of Vermont’s Complex Systems and Data Science program, the answer involves getting personal with it. Loftness studies wearable technologies and develops algorithms that can improve human health. She was awarded an NSF Graduate Research Fellowship to uncover the digital phenotypes (think digital fingerprints) for internalizing disorders like anxiety and depression that often go undetected in young children. But what if a simple device could potentially flag cases early on?

Redesigning Evolution, One Robot at a Time

Piper Welch, a Ph.D. student in UVM’s College of Engineering and Mathematical Sciences, works with Professor Josh Bongard’s team of computer scientists to design and build “xenobots,” the world’s first self-replication living robots. And it isn’t a quick endeavor. Plus there isn’t a clearly defined stopping point for a xenobot’s evolution. Welch and team members aim to program the xenobots to perform a specific task—made more difficult because the xenobots have a limited range of mobility. Another problem is building the xenobots. “The process of sculpting their bodies is very time-consuming and hinders the scalability of our work,” Welch says. “What I hope to discover is a way of controlling the behavior of biobots without having to do this—by selecting for behaviors at the swarm level.” Welch was awarded an NSF Graduate Research Fellowship to do just this. One potential application for xenobots is to carry payloads like delivering chemotherapy or pain medication to a particular site.