Shang-Hung Lin

Title: **Shang-Hung Lin: A Leading Innovator in Neural Network Technologies**

Introduction

Shang-Hung Lin, based in San Jose, CA, is a prolific inventor with an impressive portfolio of 32 patents. His work primarily focuses on advancements in artificial intelligence and machine learning, particularly within the realm of convolutional neural networks (CNN). As technology continues to evolve, Lin's contributions stand out for their innovative approaches to complex problems.

Latest Patents

Among his latest patents is a method for pruning and retraining convolutional neural networks. This approach involves training a CNN model and pruning it at specified ratios, allowing for further training and pruning without constraints from prior steps. This iterative process aims to enhance model efficiency while achieving desired pruning targets. Another notable patent involves the development of an inertial measurement system that integrates accelerometer, magnetometer, and gyroscope data to accurately estimate heading angle errors, showcasing Lin's expertise in sensor technologies.

Career Highlights

Shang-Hung Lin has held significant positions at leading technology companies, including InvenSense, Inc. and NVIDIA Corporation. His experiences at these industry giants have equipped him with the skills necessary to make substantial contributions to the field of neural networks and machine learning technologies.

Collaborations

Throughout his career, Lin has collaborated with talented individuals such as Yuan Zheng and Steve Nasiri. These partnerships have fostered an environment of innovation and creativity, allowing for the development of groundbreaking technologies that push the boundaries of what's possible in AI and machine learning.

Conclusion

With a robust portfolio of patents and a distinguished career in the tech industry, Shang-Hung Lin continues to be an influential figure in the world of innovations. His work not only enhances the capabilities of artificial intelligence but also paves the way for future advancements that can reshape various technological landscapes.