Mangalathu learned of the honor in early May, just days after he officially graduated from Georgia Tech with his Ph.D. in civil engineering.
“This award motivates me further to continue my research in the field of bridge engineering and to address the challenges in assessing the risk associated with natural disasters and aging infrastructure,” Mangalathu said.
“I am humbled, honored and grateful to have been selected as a recipient of the prestigious Nevada Medal for Distinguished Graduate Student Paper in Bridge Engineering for 2017.”
Mangalathu’s winning paper explored using machine learning techniques to identify the relative importance of uncertain input parameters and to generate bridge-specific fragility curves for bridges in California.
“[My] proposed approach helps bridge owners with rapid seismic assessment and spending their resources judiciously — for example, data collection, field investigations, censoring — in the generation of a more reliable database for regional risk assessment,” said Mangalathu, who has been working as a post-doctoral scholar in the School of Civil and Environmental Engineering since he completed his dissertation earlier in the spring,
The Nevada Medal recognizes outstanding grad student contributions to state-of-the-art bridge engineering, according to the University of Nevada, Reno Center for Civil Engineering Earthquake Research. Judges consider the work’s originality and its potential impact on bridge engineering, design and construction.