Ann Arbor, MI, United States of America

Sundaresh Ram

This inventor holds 1 USPTO granted patent. Top assignee: University of Michigan. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Sundaresh Ram. Retrieved from https://idiyas.com/inventor/sundaresh-ram

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

Calculating rank

Average Co-Inventor Count = 1.0

ph-index = 1


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Sundaresh Ram and Patent Innovation in Tissue Assessment

Introduction

Sundaresh Ram is an inventor associated with the University of Michigan in Ann Arbor, Michigan. His patent work includes a computer-implemented approach to assessing tissue and detecting abnormalities across multiple views.

Latest Patents

The provided information identifies one patent associated with Ram: “Dictionary-Based Tissue Assessment and Abnormality Detection.” The method processes multiple input samples representing tissue from different views, determines sparse codes for each sample, and compares reconstruction errors against machine-learned composite dictionaries. Each composite dictionary combines constituent dictionaries associated with the respective views. The system then provides a tissue assessment based on the dictionary that produces the minimum reconstruction error. Ram is credited with 1 patent in the information provided.

Career Highlights

Ram’s listed patent reflects an application of machine learning to medical image analysis. By combining information from multiple views, the method aims to support tissue assessment and abnormality detection.

Collaborations

Ram is associated with the University of Michigan. The provided information also names Craig Galban as a coworker.

Conclusion

Sundaresh Ram’s patent describes a multi-view, dictionary-based method for tissue assessment, highlighting the use of machine learning in medical analysis.

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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