Milpitas, CA, United States of America

Buddha Puneeth Nandanoor


Average Co-Inventor Count = 1.0


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Innovations of Buddha Puneeth Nandanoor

Introduction

Buddha Puneeth Nandanoor is an accomplished inventor based in Milpitas, CA (US). He has made significant contributions to the field of machine learning, particularly in the development of innovative neural network models. His work is characterized by a focus on continuous learning and the optimization of machine learning processes.

Latest Patents

Nandanoor holds a patent for "Continuous learning for machine learning models." This invention describes a system where a first neural network (NN) model generates labels for training a second NN model. The second NN model operates on multiple devices, including decentralized user and edge devices. The system utilizes a 'teacher' model to process data from these devices, creating a labeled dataset. This dataset is then used by a “student” model to calculate gradient data for updates. The student model may be similar to the NN model instances on the devices. The system also validates the updated student model to ensure improved performance when processing new and historical data, distributing the validated updates to the devices.

Career Highlights

Buddha Puneeth Nandanoor is currently employed at Amazon Technologies, Inc., where he continues to innovate in the field of machine learning. His work has garnered attention for its practical applications and potential to enhance the efficiency of machine learning models.

Collaborations

Nandanoor collaborates with various professionals in his field, including his coworker Ariya Rastrow. Their combined expertise contributes to the advancement of technology at Amazon Technologies, Inc.

Conclusion

Buddha Puneeth Nandanoor is a notable inventor whose work in machine learning is paving the way for future innovations. His patent on continuous learning for neural networks exemplifies his commitment to enhancing technology and improving machine learning processes.

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