San Jose, CA, United States of America

David Hung Huynh


Average Co-Inventor Count = 9.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2024

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1 patent (USPTO):

Title: Innovator Spotlight: David Hung Huynh and His Advances in Machine Learning for Delivery Solutions

Introduction: David Hung Huynh is an innovative inventor based in San Jose, California. With a focus on integrating machine learning with delivery systems, Huynh has patented a groundbreaking approach that enhances driver safety and operational efficiency in delivery workflows.

Latest Patents: David Hung Huynh holds a patent for "Machine Learning Item Delivery Using Sensor Data." This patent presents various embodiments for leveraging machine learning routines in conjunction with peripheral device data to infer driver activity and location. By utilizing data collected from a peripheral device with a machine learning routine, Huynh's invention aims to improve the estimation of driver location and activity. This offers contextually relevant assistance to delivery drivers without necessitating manual input, thus promoting both safety and efficiency.

Career Highlights: David is part of Amazon Technologies, Inc., where he collaborates with other talented professionals in the tech industry. His focus on innovative solutions within logistics showcases his commitment to enhancing delivery operations through technology. The impact of his work is evident in the improved workflows that benefit drivers and operational processes alike.

Collaborations: Throughout his career, David has worked alongside esteemed colleagues, including Ruth Ravichandran and Hebaallah Aly Abdelhalim Aly Ismail. Together, they contribute to advancing technological solutions within their field, helping to push the boundaries of what's possible in delivery systems.

Conclusion: David Hung Huynh exemplifies the spirit of innovation in the technology sector. His patent on machine learning for delivery systems not only advances operational efficiency but also enhances safety for drivers on the road. As he continues his work at Amazon Technologies, Inc., the impact of his contributions is likely to resonate across the industry and inspire further developments in machine learning applications.

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