Tutuncuoglu receives NSF CRII grant to develop 3D printed neuromorphic circuitry

Neuromorphic computing — which performs tasks emulating human cognition and simulating natural learning — is an innovation that holds promise to accelerate the future of AI-powered devices and systems. However, current microfabrication techniques of neuromorphic circuitry are not currently scalable due to long prototyping cycles and other challenges. New research from the Wayne State University College of Engineering may offer a solution.

Gozde TutuncuogluGozde Tutuncuoglu, assistant professor of electrical and computer engineering, is leading a project focused on developing application-specific neuromorphic circuits using nanoscale 3D-printing technology. Her work is supported by a two-year, $174,889 grant through the National Science Foundation's Computer and Information Science and Engineering Research Initiation Initiative (NSF CRII). This prestigious, highly competitive grant is awarded to early-career investigators to launch their research and academic careers.

“Our brains outperform the most advanced supercomputers in unsupervised learning tasks like image-recognition and decision making while consuming significantly lower energy and occupying a much smaller area,” said Tutuncuoglu. “Advancement in neuromorphic computing is critical to tackle the increasing data volume, computation and communication requirements of modern applications such as Internet-of-Things, virtual drug discovery and artificial intelligence.”

According to Tutuncuoglu, use of a nanoscale 3D-printing platform instead of conventional techniques will offer design freedom in both materials and device architecture levels, and significantly shorten the device prototype cycles. Such a method also enables seamless configuration of device-performance metrics according to the requirements of different applications and algorithms.

The award number for this NSF grant is 2153177.


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