Parsa studying design of joint 3D solid-state learning machines for various cognitive use-cases
2023-10-23
(Press-News.org)
Parsa Studying Design Of Joint 3D Solid-State Learning Machines For Various Cognitive Use-Cases
Maryam Parsa, Assistant Professor, Electrical and Computer Engineering, received funding from the National Science Foundation for the project: "Collaborative Research: NCS-FR: DEJA-VU: Design of Joint 3D Solid-State Learning Machines for Various Cognitive Use-Cases."
In this collaborative project, Parsa joins a team of faculty members from the University of Wisconsin Madison (Dr. Akhilesh Jaiswal), and the University of California Irvine (Dr. Babak Shahbaba and Dr. Norbert Fortin) to design a new class of computer chips by leveraging advances in recent understanding of how the brain represents and computes information. Specifically, they will be focusing on the hippocampus region of the brain that can learn, recall past experience, and build knowledge on the fly. This three-year project has received total funding of $2,400,000 from the National Science Foundation.
In this project, a multi-disciplinary team of neuroscientist, statistician, hardware designer, and algorithm developer will model and quantify essential information processing steps in the hippocampus. They will then embed these functions onto solid-state computing chips through state-of-the-art hardware design techniques. Additionally, they will develop a hippocampal-aware, hardware-aware, algorithmic framework to enhance chip design, enabling online learning and decision-making in resource-constrained environments. The transformative potential of the project emerges from research conducted at three different levels of abstractions: neuroscience, hardware, and algorithm for the next generation of cognitive intelligence.
Parsa received $550,000 from NSF for this project. Funding began in Oct. 2023 and will end in late Sept. 2026.
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[Press-News.org] Parsa studying design of joint 3D solid-state learning machines for various cognitive use-cases
