Na Yu

Title: Na Yu: Innovator in Vehicle Data Mining and Signal Detection

Introduction

Na Yu is a prominent inventor based in San Jose, California, known for his contributions to vehicle data mining and signal detection technologies. With a total of six patents to his name, Yu has developed innovative solutions that enhance the way vehicles interact with their environments.

Latest Patents

One of Yu's latest patents is titled "Interaction auto-labeling using spatial overlap of track footprints for mining interactions." This invention provides a method for quickly sorting through and identifying relevant data sets from large amounts of data collected by various vehicles. The process involves evaluating sensor data collected over time to identify interactions between vehicles on the road. The data is classified according to specific driving maneuvers, such as "turning left across traffic" or "lane change."

Another significant patent is "Multi-modal, multi-technique vehicle signal detection." This invention describes a vehicle equipped with cameras that capture two-dimensional images of three-dimensional objects. A light detector and semantic classifier work together to identify lights within these images, allowing the vehicle to interpret and respond to its surroundings effectively. The inclusion of a depth sensor and object projector further enhances the vehicle's ability to focus on regions of interest within the captured images.

Career Highlights

Na Yu has worked with notable companies such as GM Cruise Holdings LLC and Samsung Electronics Co., Ltd. His experience in these organizations has contributed to his expertise in developing advanced vehicle technologies.

Collaborations

Yu has collaborated with talented individuals in his field, including Clement Creusot and Divya Thuremella, who have contributed to his innovative projects.

Conclusion

Na Yu's work in vehicle data mining and signal detection showcases his commitment to advancing automotive technology. His patents reflect a deep understanding of how vehicles can better interact with their environments, paving the way for safer and more efficient driving experiences.