San Francisco, CA, United States of America

Stathis Vafeias

This inventor holds 1 USPTO granted patent and 2 published patent applications. Top assignee: Stripe, Inc.. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Stathis Vafeias. Retrieved from https://idiyas.com/inventor/stathis-vafeias

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


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Stathis Vafeias: Innovating Network Fraud Detection.

Introduction

Stathis Vafeias is an inventor based in San Francisco, California, and works at Stripe, Inc. His patent work focuses on applying machine learning to identify potentially fraudulent activity in networked environments.

Latest Patents

Vafeias is associated with 1 patent, titled “Systems and Methods for Generating Embeddings of Network Event Data to Detect Fraudulent Behavior in Networked Environments.” The invention describes a service that receives a request to perform a network operation, identifies the event data associated with it, and applies that data to a machine-learning model. Trained using sample event datasets, including modified versions of those datasets, the model generates embeddings that indicate whether the operation may be fraudulent.

Career Highlights

At Stripe, Inc., Vafeias’s patent reflects work on using machine learning to analyze network events and support fraud detection. The approach centers on generating data representations that can help assess the risk associated with network operations.

Collaborations

Vafeias’s listed coworker is Yashu Lingaraju. Their shared professional context is associated with Stripe, Inc.

Conclusion

Stathis Vafeias’s patent presents a machine-learning approach to detecting potentially fraudulent network activity by generating embeddings from event data.

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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