Guntur, India

Kamanchi Chandramouli

This inventor holds 1 USPTO granted patent. Top assignee: International Business Machines Corporation. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Kamanchi Chandramouli. Retrieved from https://idiyas.com/inventor/kamanchi-chandramouli

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

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Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Kamanchi Chandramouli: Inventor in Machine Learning

Introduction

Kamanchi Chandramouli is an inventor based in Guntur, India. His patent work focuses on accelerating machine learning from spatio-temporal data. He is associated with International Business Machines Corporation.

Latest Patents

Chandramouli is credited with 1 patent: “Accelerated Learning from Spatio-Temporal Data.” The invention describes a computer-implemented method, program product, and system for training machine learning models more efficiently. It partitions an independent variable in input data, creates lower-granularity samples within each partition, and trains a model on those samples. When results from a predetermined number of samples are statistically identical at a specified confidence level, the system outputs one result. For partitions without a qualifying result, it merges pairs of samples and uses the merged data to train the model.

Career Highlights

Chandramouli’s patent describes an approach to reducing the work required to learn from spatio-temporal data by identifying when lower-granularity samples produce statistically consistent training results. His work is associated with International Business Machines Corporation.

Collaborations

His listed coworkers include Krishnasuri Narayanam and Pankaj Satyanarayan Dayama.

Conclusion

Kamanchi Chandramouli’s patent presents a method for accelerating machine learning through partitioned data, statistical comparisons, and selective sample merging.

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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