John David Reeder

Title: John David Reeder: Innovator in Machine Learning and Autonomous Systems

Introduction

John David Reeder is a notable inventor based in San Diego, CA. He has made significant contributions to the fields of machine learning and autonomous systems. With a total of 2 patents, his work focuses on advanced technologies that enhance signal processing and multi-agent systems.

Latest Patents

One of his latest patents is titled "Neural network approach for identifying a radar signal in the presence of noise." This innovative system utilizes a self-supervised machine-learning approach to determine the presence of an intermittent signal amidst noise. The system comprises a receiver, an encoding neural network, a decoding neural network, and a gating neural network. The receiver detects radiation and generates a sampled sequence that includes values describing both the intermittent signal and noise. The encoding neural network compresses each window of the sampled sequence into a context vector, while the decoding neural network decompresses this vector into an interim sequence that describes the intermittent signal, effectively suppressing the noise. The gating neural network produces a confidence sequence that identifies the presence of the intermittent signal in each sampled value.

Another significant patent is "Method for performing multi-agent reinforcement learning in the presence of unreliable communications via distributed consensus." This system is designed for executing predetermined functions within a total operational area, utilizing a plurality of autonomous agents. Each agent detects local parameters and employs a Kalman filter component to establish an environment state based on multiple state measurements over time. The output from the Kalman filter is integrated into reinforcement learning by an actor-critic task controller, which determines subsequent actions based on a reward function. Each agent also includes a Kalman consensus filter to address errors in state measurements over time.

Career Highlights

John David Reeder works for the USA as represented by the Secretary of the Navy. His role involves developing cutting-edge technologies that contribute to national defense and advanced research initiatives. His expertise in machine learning and autonomous systems has positioned him as a key player in his field.

Collaborations

Some of his notable coworkers include Diego Marez and Michael W Walton. Their collaborative efforts have further advanced the research and development of innovative technologies in their respective areas.

Conclusion

John David Reeder's contributions to machine learning and autonomous systems demonstrate his commitment to innovation and technological advancement. His patents reflect a deep understanding of complex systems and a drive to improve operational efficiency