Three SEAS students receive SUNY GREAT awards

by Charles Anzalone

The three are among eight UB students to receive the award. Across SUNY, 22 students  received the GREAT awards; all award winners have also been recognized nationally for their research by prestigious graduate fellowship programs sponsored by the National Science Foundation or the National Institutes of Health.

This includes the NIH F31 Individual Fellowships and the NSF Graduate Research Fellowship Program (GRFP).

“This SUNY award elevates the prominence of these external fellowships for graduate students,” says Elizabeth A. Colucci, assistant dean for graduate professional development in the Graduate School. “We at UB have been working diligently to increase awareness of the NSF GRFP and NIH individual awards, such as the F30 and F31.

“External awards provide not only funding support, but also career-enhancing recognition,” Colucci says. “As UB moves to Top 25 recognition, having graduate students win these prestigious awards will support this goal.”

Among the UB’s award recipients’ research topics are defending the country against terrorism, understanding anatomical structure imaging with an eye toward improving gross anatomy education, and understanding how artificial intelligence and machines interpret audio and images.

“SUNY graduate students are not simply researchers,” notes SUNY Interim Chancellor Deborah F. Stanley. “They are creating innovative solutions, and whether it be measuring the impacts of climate change or improving homeland security, our talented young minds are dedicating their intelligence to improving the lives of others.”

The three SEAS students receiving SUNY GREAT Awards and their research topics are:

“My dissertation work focuses on identifying optimal strategies to combat terrorism. Specifically, I focus on questions surrounding information disclosure (i.e., how should homeland security and/or defense-related information be released to the public), technology adoption/deployment and resource allocation. To address these challenges, I utilize techniques such as game theory, decisions analysis and machine learning.”

“My research focuses on a variety of artificial intelligence and machine learning areas to fundamentally advance the way systems understand audio and images. Specifically, I work on audio and image recognition, sound event detection and localization, sound-based echolocation, real-time video and image inpainting, and fundamental methods in deep metric learning.

“My research extends into industry applications as well. I am currently collaborating with ACV Auctions to develop and deploy an artificial intelligence system to diagnose faulty vehicle engines based purely on sound. Advancing the way systems understand sights and sounds allows us to automate and aid various aspects of life, whether it’s diagnosing a faulty engine from your phone, creating automatic sound surveillance systems, or fundamentally improving the construction of deep neural networks that are used in a variety of ways in our daily lives.”

"My research involves the use of test phantom metrology in multiple different photoacoustic medical applications. Test phantoms are recreations of physiological components of the human body. Phantoms provide a controlled testing environment with known parameters such as arteries of specific size, human-like blood pressures and realistic tissue. This accelerates the development of a technology by eliminating the need for human tests and providing application specific phantom metrology. Through this work I have progressed photoacoustics in the fields of blood pressure, biometrics and medical imaging.”

This story was reprinted from UB Now. Read the full story here.