Ann Arbor, MI, United States of America

Subramanya Nageshrao

USPTO Granted Patents = 2 

Average Co-Inventor Count = 4.4

ph-index = 1

Forward Citations = 5(Granted Patents)


Location History:

  • Ann Arbor, MI (US) (2020)
  • Mountain View, CA (US) (2023)

Company Filing History:


Years Active: 2020-2023

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2 patents (USPTO):Explore Patents

Title: Subramanya Nageshrao: Innovator in Reinforcement Learning and Vehicle Technology

Introduction

Subramanya Nageshrao is a notable inventor based in Ann Arbor, MI (US). He has made significant contributions to the fields of reinforcement learning and vehicle technology. With a total of 2 patents, his work is at the forefront of innovation in these areas.

Latest Patents

Nageshrao's latest patents include "Interpreting Data of Reinforcement Learning Agent Controller" and "Vehicle Adaptive Learning." The first patent describes systems and methods that involve calculating a plurality of state-action values based on sensor data through a reinforcement learning agent (RLA) controller. This controller utilizes a deep neural network (DNN) and generates a plurality of linear models mapping the state-action values to the sensor data via a fuzzy controller. The second patent outlines a computing system that determines vehicle actions based on inputting vehicle sensor data to a neural network, which includes a safety agent that assesses the probability of unsafe vehicle operation. This system can adapt over time through a periodically retrained deep reinforcement learning agent.

Career Highlights

Subramanya Nageshrao is currently employed at Ford Global Technologies, LLC, where he applies his expertise in developing advanced technologies for vehicles. His innovative work has positioned him as a key player in the automotive technology sector.

Collaborations

Nageshrao has collaborated with notable colleagues such as Dimitar Petrov Filev and Hongtei Eric Tseng, contributing to the advancement of technology in his field.

Conclusion

Subramanya Nageshrao's contributions to reinforcement learning and vehicle technology exemplify the impact of innovative thinking in modern engineering. His patents reflect a commitment to enhancing vehicle safety and performance through advanced computational methods.

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