Corey Hu

Title: Corey Hu: Inventor in Circuit Design and Machine Learning

Introduction

Corey Hu is an inventor based in San Diego, California, whose patent work applies machine learning to electronic circuit design. The supplied information identifies her as working at NVIDIA Corporation.

Latest Patents

Hu is associated with one patent, titled “Generative Self-Supervised Learning to Transform Circuit Netlists.” The invention applies self-supervised machine learning to combinational gate sizing from an input circuit netlist. It describes a transformer neural network that selects gate sizes along paths connecting primary inputs and outputs, as well as sequential logic elements. These selections can be optimized for path delay, power consumption, and circuit area.

Career Highlights

Hu’s patent reflects work at the intersection of artificial intelligence and hardware design. By using a transformer architecture to guide gate sizing, the disclosed approach aims to help optimize important circuit characteristics.

Collaborations

The supplied information names Siddhartha Nath and Haoxing Ren as Hu’s coworkers. Their inclusion indicates professional connections in the broader circuit-design and machine-learning environment, though specific contributions to this patent are not provided.

Conclusion

Corey Hu’s patent highlights an approach to circuit optimization that combines self-supervised learning with transformer-based analysis of netlists.