Van Nuys, CA, United States of America

Sergey Butylkov

This inventor holds 1 USPTO granted patent. Top assignee: Genesee Valley Innovations, LLC. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Sergey Butylkov. Retrieved from https://idiyas.com/inventor/sergey-butylkov-ezgegs4k

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

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Average Co-Inventor Count = 1.0


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Innovations in Micro-Assembly Control by Sergey Butylkov

Introduction

Sergey Butylkov is an accomplished inventor based in Van Nuys, CA (US). He has made significant contributions to the field of micro-assembly control through his innovative patent. His work combines advanced modeling techniques to enhance the accuracy and efficiency of micro-object manipulation.

Latest Patents

Sergey Butylkov holds a patent titled "System and method for hybrid-model-based micro-assembly control with the aid of a digital computer." This patent addresses control loop latency by predicting the positions of micro-objects using a hybrid model that integrates both physics-based and machine-learning models. The models are combined through gradient boosting, allowing for improved accuracy in micro-assembly processes. The hybrid model is designed to prevent overfitting and ensure sufficient predictive ability by evaluating data extrapolated and interpolated from training data.

Career Highlights

Sergey is currently associated with Genesee Valley Innovations, LLC, where he applies his expertise in micro-assembly control. His innovative approach has the potential to revolutionize the field by increasing the throughput and accuracy of micro-assembly tasks.

Collaborations

Some of his notable coworkers include Anne Plochowietz and Anand Ramakrishnan, who contribute to the collaborative environment at Genesee Valley Innovations, LLC.

Conclusion

Sergey Butylkov's work in hybrid-model-based micro-assembly control exemplifies the intersection of physics and machine learning in advancing technology. His contributions are paving the way for more efficient micro-assembly processes 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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