Sunnyvale, CA, United States of America

Aditya Rawal

This inventor holds 2 USPTO granted patents. Top assignees: Cognizant Technology Solutions U.S. Corporation, Uber Technologies, Inc.. Active years: 2021-2024.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Aditya Rawal. Retrieved from https://idiyas.com/inventor/aditya-rawal

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile


% Patents Active = 100.0

Average Co-Inventor Count = 2.9

ph-index = 1

Forward Citations = 5(Granted Patents)


Company Filing History:


Years Active: 2021-2024

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2 patents (USPTO):Explore Patents

Title: Aditya Rawal: Innovator in Neural Network Technologies

Introduction

Aditya Rawal is a prominent inventor based in Sunnyvale, CA, known for his contributions to the field of neural networks. With a focus on generating training datasets and evolving recurrent networks, he has made significant strides in artificial intelligence and machine learning. His innovative work has led to the filing of two patents, showcasing his expertise and creativity in this rapidly evolving domain.

Latest Patents

Aditya Rawal's latest patents include groundbreaking technologies that enhance the capabilities of neural networks. The first patent, titled "Generating training datasets for training neural networks," describes a generative cooperative network (GCN) that comprises a dataset generator model and a learner model. This system generates training datasets used to train the learner model, which is then evaluated against a reference training dataset. The dataset generator model is modified based on this evaluation, ensuring continuous improvement. The GCN stores the training datasets, the dataset generator model, and the learner model, allowing the trained learner model to receive input and generate output effectively.

The second patent, "Evolving recurrent networks using genetic programming," outlines a system and method for evolving a recurrent neural network (RNN) to solve specific problems. This innovative approach includes a memory that stores a candidate RNN genome database, an assembly module for constructing RNN layers, and an evolution module that enhances the candidate RNN nodes. Additionally, a training module trains these nodes using data, while an evaluation module assesses their performance and assigns fitness values. The competition module forms an elitist pool of candidate RNN nodes based on their fitness, and a solution harvesting module facilitates the deployment of RNN layers.

Career Highlights

Aditya has worked with notable companies such as Cognizant Technology Solutions and Uber Technologies, where he has applied his skills in machine learning and artificial intelligence. His experience in these organizations has allowed him to collaborate with leading experts in the field and contribute to innovative projects.

Collaborations

Some of Aditya's notable coworkers include Risto Miikkulainen and Felipe Petroski Such, who have also made significant contributions to the field of neural networks. Their collaborative efforts have further advanced the understanding and application of artificial intelligence technologies.

Conclusion

Aditya Rawal's work in neural network technologies exemplifies the spirit of innovation and creativity in the tech industry. His patents reflect a deep

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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