Columbus, OH, United States of America

Farshud Sorourifar

This inventor holds 1 USPTO granted patent and 1 published patent application. Top assignee: Mitsubishi Electric Research Laboratories, Inc.. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Farshud Sorourifar. Retrieved from https://idiyas.com/inventor/farshud-sorourifar

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

Calculating rank
USPTO Granted Patents = 1 

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: Farshud Sorourifar and Generative AI-Based Stochastic Control

Introduction

Farshud Sorourifar is an inventor associated with Columbus, Ohio, and Mitsubishi Electric Research Laboratories, Inc. His patent work explores how generative AI can help predictive controllers manage uncertainty in mechanical systems.

Latest Patents

Sorourifar is named on 1 patent, titled “Stochastic Control Subject to Generative AI-Based Disturbance.” The invention describes a predictive controller that uses a deep generative decoder model to estimate a probability distribution for disturbances based on partial observations. It samples from that distribution, decodes the sample into predicted disturbance values over a time horizon, and uses the probabilities of those predictions to determine control commands for the mechanical system.

Career Highlights

The patent reflects work at the intersection of stochastic control, predictive control, and deep generative modeling. By incorporating uncertainty into its predictions, the described approach aims to help a mechanical system adjust its operation in response to disturbances.

Collaborations

Ye Wang is identified as a coworker associated with Sorourifar’s work. The patent also connects Sorourifar’s inventive activity with Mitsubishi Electric Research Laboratories, Inc.

Conclusion

Farshud Sorourifar’s patent presents a generative AI-based approach to predictive control that accounts for uncertain disturbances when determining how a mechanical system should operate.

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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