Pittsburgh, PA, United States of America

Ian Volkwein

This inventor holds 1 USPTO granted patent. Top assignee: Ford Global Technolgoies, LLC. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Ian Volkwein. Retrieved from https://idiyas.com/inventor/ian-volkwein

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

ph-index = 1


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Ian Volkwein: Inventor Advancing Machine-Learning Training

Introduction

Ian Volkwein is an inventor associated with Pittsburgh, Pennsylvania, and Ford Global Technologies, LLC. His patent work addresses the preparation of video data for training machine-learning systems.

Latest Patents

Volkwein is credited with 1 patent, titled “Neural network.” The invention describes a computer that uses a processor and memory to plot three-dimensional positions of labeled cuboids across frames between two keyframes in a densely labeled video sequence. It can create a sparsely labeled sequence by removing cuboids whose positions fall within a user-selected distance of a line connecting their positions in the keyframes. The resulting sequence can then be provided as training data for a machine-learning system.

Career Highlights

Volkwein’s listed patent reflects work on video annotation and machine-learning data preparation. By generating sparsely labeled sequences from densely labeled video, the described approach offers a way to prepare training material using selected spatial relationships across frames.

Collaborations

Volkwein’s listed coworkers include Parul Kothari and Iurii Simanovskyi. His patent is associated with Ford Global Technologies, LLC.

Conclusion

Ian Volkwein’s patent focuses on transforming labeled video into training data for machine-learning systems, highlighting his contribution to innovation in video-based data preparation.

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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