Three students working with Chris Metzler, an assistant professor of computer science at the University of Maryland, have been awarded the prestigious Department of Defense National Defense Science and Engineering Graduate (NDSEG) Fellowship.
Adam Yang, a senior majoring in computer science, along with first-year computer science doctoral students Sachin Shahand Anand Idris, are among a select group of students nationwide selected to receive this year’s highly competitive NDSEG Fellowship.
Established in 1989, the NDSEG Fellowship program aims to increase the number of U.S. citizens trained in science and engineering disciplines vital to national security. It provides up to three years of full tuition, a monthly stipend, health insurance, and a travel budget for professional development.
Metzler, who also holds an appointment in the University of Maryland Institute for Advanced Computer Studies, describes Idris, Shah and Yang as exceptionally talented and creative researchers.
“While they each bring unique backgrounds and research interests, all three stand out for their intellectual rigor and drive to tackle complex scientific problems of national interest,” Metzler says. “In addition to their academic and research accomplishments, they’ve been outstanding members of the University of Maryland community and have worked to enhance educational opportunities for those around them.”
Idris work involves computational imaging, a field that relies on advanced optical hardware but still faces challenges capturing accurate images in difficult conditions. His research focuses on developing algorithms that enhance next-generation optics, enabling reliable imaging in scenarios such as low-light environments and atmospheric turbulence.
Yang’s research has a similar computational focus. He applies machine learning and computer vision techniques to remote sensing problems, with a particular emphasis on climate and weather monitoring. His work helps extract accurate insights from complex environmental data—critical for understanding and responding to global change.
Shah focuses on hardware-software co-design, integrating physics-based modeling and machine learning to solve complex, real-world problems. His research involves developing methods to identify optimal, task-specific sensors by leveraging novel techniques from information theory and neural representations. This interdisciplinary approach seeks to create intelligent and efficient sensing systems by uniting the physical and computational domains.
—Story by Melissa Brachfeld, UMIACS communications group