Engineering
-2nd Year Students
-3rd Year Students
-4th Year Students- Seniors
-3rd Year Students
-4th Year Students- Seniors
229
Tempe
Modern AI usually runs on power-hungry digital hardware. Nature does better. In this project, you’ll explore a radically different approach: nano-oscillators—tiny electronic devices whose rhythms can compute. When driven properly, these oscillators naturally synchronize, drift, and respond to time-varying signals, making them ideal for voice and speech recognition, image identification, and many other applications.
Students will work with emerging devices (such as phase-change nano-oscillators), simple circuits, and data-driven learning methods inspired by the brain. Over two semesters, you will (1) build intuition through modeling and experiments, (2) encode audio signals into oscillator dynamics, and (3) demonstrate a small-scale AI task such as spoken-digit recognition—using physics, not massive neural networks.
This project is hands-on, interdisciplinary, and research-focused, blending electronics, materials, signal processing, and machine learning. It is well suited for students curious about neuromorphic computing, sustainable AI hardware, or graduate research. No prior AI experience is required—just curiosity, persistence, and a willingness to learn how matter itself can compute.
Students will work with emerging devices (such as phase-change nano-oscillators), simple circuits, and data-driven learning methods inspired by the brain. Over two semesters, you will (1) build intuition through modeling and experiments, (2) encode audio signals into oscillator dynamics, and (3) demonstrate a small-scale AI task such as spoken-digit recognition—using physics, not massive neural networks.
This project is hands-on, interdisciplinary, and research-focused, blending electronics, materials, signal processing, and machine learning. It is well suited for students curious about neuromorphic computing, sustainable AI hardware, or graduate research. No prior AI experience is required—just curiosity, persistence, and a willingness to learn how matter itself can compute.
Basic Circuits
Zhaoyang Fan
Tempe