Nguyen Michael Do
Electrical engineering
Hometown: Gilbert, Arizona, United States
Graduation date: Fall 2025
Additional details: First-generation college student, Honors student
FURI | Spring 2025
TCAD Modeling Aided by Physics-informed Neural Networks
Technology-Computer-Aided-Design (TCAD) solvers are highly accurate yet computationally expensive tools to simulate electronic device behavior. Photoconductive Semiconductor Switches (PCSS) are optoelectronic devices used in high-frequency amplification and power applications. This research project aims to train a physics-informed neural network (PINN) model to simulate device behavior and compare to the speed and accuracy of the TCAD solvers. By implementing a PINN model, this research aims to improve the efficiency of device-technology co-optimization (DTCO).
Mentor: Kexin Li
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