UNIVERSITY PARK, Pa. — Abhronil Sengupta, associate professor of electrical engineering and computer science at Penn State, has been invited to participate in the National Academy of Engineering’s (NAE) Grainger Foundation Frontiers of Engineering 2026 Symposium, which will be held Sept. 21-24 at the University of Texas at Austin, in conjunction with Advanced Micro Devices (AMD).
“I feel honored and excited to be a part of this select group of people,” Sengupta said. “It’s a very interdisciplinary forum, and a lot of early career scientists attend, which I feel will help me bridge the gap between various disciplines and explore potential synergies with other researchers. I’m humbled by the recognition.”
Sengupta was selected as part of a group of 74 engineers who the academy describes as “performing exceptional research and technical work in a variety of disciplines across academia, industry and government.”
Sengupta defines his research as being broadly centered around neuroAI, which bridges neuroscience and artificial intelligence (AI), and neuromorphic computing. His team is using neuroscience to rethink AI in hopes of decreasing the energy expenditure required to operate their systems, and to re-establish a stronger biological underpinning in AI systems.
“Our motivation is primarily driven by the fact that the human brain does all of this incredible computing under severe power constraints,” Sengupta said. “We can draw continued inspiration from computational neuroscience and design our AI algorithms and hardware to be more brain-like.”
This year’s symposium has four primary themes: innovation in bioengineered materials, compute challenges for artificial intelligence, agriculture as a system-of-systems and hypersonics.
Sengupta said he is looking forward to the interdisciplinary nature of the event, given his own interdisciplinary research, which he said includes neuroscience, nanoelectronics and semiconductors, as well as machine learning and AI algorithms.
“It is an ideal opportunity to forge collaborations and translate some of our group’s basic research to near-term engineering application drivers,” Sengupta said. “Along with AI sustainability challenges, I think our research has potential for broader impact in fields like neuroengineering or understanding brain diseases.”