��������

 

As medical breakthroughs continue to improve the human condition, data scientists in the specialized field of network neuroscience are striving to isolate even more information in an effort to advance diagnoses and personalized treatments of diseases of the brain.

Among those elite data science researchers is �������� engineering alumnus Dr. Duy Duong-Tran, whose research seeks to unravel different characteristics of human brain functional networks—the quantification of human brain.

“Network science has seen unprecedented growth, in part, due to the birth of networked data in biology, finance, and other fields,” says Duong-Tran. “Such exciting, intertwined dynamics gave rise to the emerging field of network neuroscience,” with the biggest challenge closing the gap between discoveries and clinical application.

“Specifically, how do we progressively show that findings in network neuroscience are effective and relevant in diagnosis and prognosis to different human brain neurovegetative diseases,” explains Duong-Tran. “If we can close this gap, it would lay a stronger foundation for personalized medicine or therapeutic solutions.”

Duong-Tran earned his B.S. in industrial and entrepreneurial engineering and mathematics in 2014 and his M.S. in industrial engineering in 2017, both from ��������. He completed his Ph.D. from Purdue University in 2022 and works as a postdoctoral research fellow at the University of Pennsylvania. In January 2023, he will join the faculty of the United States Naval Academy, serving as a core member of a newly developed data science major. He will continue his research pursuits in network science focusing on applications in network neuroscience.

Duong-Tran’s research on the intersection of network science—an emerging research—area greatly inspired by graph-theory—and theoretical/computational neuroscience. His dissertation, titled “On geometric and algebraic properties of human brain functional networks,” was completed during spring 2022 semester.

Duong-Tran has set-up his life as an educator and researcher to help advance the emerging field of data science and network neuroscience through research that builds a stronger foundation to personalized medicine or therapeutic solutions.