Bengaluru, India

Devesh Solanki

This inventor holds 1 USPTO granted patent. Top assignee: Zscaler, Inc.. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Devesh Solanki. Retrieved from https://idiyas.com/inventor/devesh-solanki-ypa4am1a

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


Average Co-Inventor Count = 1.0


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Devesh Solanki: Innovator in Synthetic Data Generation

Introduction

Devesh Solanki is a prominent inventor based in Bengaluru, India. He has made significant contributions to the field of data science, particularly in the area of synthetic data generation. His innovative work is aimed at enhancing machine learning models while ensuring data privacy.

Latest Patents

Devesh holds a patent titled "Systems and methods for generating and utilizing synthetic data." This patent describes a process that includes receiving a set of real network traffic data and generating synthetic data based on patterns learned from that data. The synthetic data can be utilized for training and testing machine learning models, as well as configuring customer cloud environments. The systems he developed are designed to produce a large amount of synthetic data from a limited set of real data while anonymizing sensitive information. This ensures compliance with data privacy practices.

Career Highlights

Devesh Solanki is currently employed at Zscaler, Inc., where he continues to innovate in the field of data generation and machine learning. His work is crucial in developing systems that can effectively utilize synthetic data for various applications.

Collaborations

Devesh has collaborated with notable colleagues, including Chenhui Hu and Zhen Yu, who share his passion for advancing technology in data science.

Conclusion

Devesh Solanki's contributions to synthetic data generation represent a significant advancement in the field of machine learning and data privacy. His innovative approaches are paving the way for more effective and secure data utilization in various applications.

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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