Hyderabad Telangana, India

Manish Khati

This inventor holds 1 USPTO granted patent. Top assignee: Accenture Global Solutions Limited. Active years: 2026.


% Patents Active = 100.0

Average Co-Inventor Count = 7.0

ph-index = 1


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Manish Khati - Innovator in Machine Learning

Introduction

Manish Khati is a notable inventor based in Hyderabad, Telangana, India. He has made significant contributions to the field of machine learning through his innovative patent. His work focuses on enhancing data labeling processes, which is crucial for the development of intelligent systems.

Latest Patents

Manish holds a patent titled "Hierarchical data labeling for machine learning using semi-supervised multi-level labeling framework." This patent involves a sophisticated method for processing data samples. The implementation includes receiving a plurality of data samples, generating a random forest structure, and utilizing a graph embedding algorithm to extract features. The approach aims to improve the accuracy of labeling data samples, which is essential for machine learning applications. He has 1 patent to his name.

Career Highlights

Manish is currently employed at Accenture Global Solutions Limited, where he applies his expertise in machine learning and data analysis. His role involves developing innovative solutions that leverage advanced technologies to solve complex problems. His contributions have been instrumental in driving the company's success in the tech industry.

Collaborations

Manish collaborates with talented professionals, including Hrishikesh Satbhai and Srikant Vilas Khole. Together, they work on various projects that push the boundaries of technology and innovation.

Conclusion

Manish Khati is a prominent figure in the realm of machine learning, with a focus on improving data labeling techniques. His patent and work at Accenture Global Solutions Limited highlight his commitment to advancing technology. His contributions are paving the way for more efficient machine learning applications in the future.

Profile summary based on public USPTO records.
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