Barsa, Lebanon

Mohammad Zakaria

This inventor holds 1 USPTO granted patent and 1 published patent application. Top assignee: B.yond, Inc.. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Mohammad Zakaria. Retrieved from https://idiyas.com/inventor/mohammad-zakaria-zuumg5we

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: Mohammad Zakaria: Inventor in Telecommunications Network Analysis.

Introduction

Mohammad Zakaria is an inventor based in Barsa, Lebanon. His work includes a patented approach to analyzing telecommunications network traffic with machine learning. He is associated with B.yond, Inc.

Latest Patents

Zakaria’s listed patent, “Network Packet Capture Analysis Using Machine Learning Model,” describes a method for diagnosing communication flows in telecommunications networks. The approach correlates network packets and labels them to indicate whether individual communication subtasks succeed or fail. It then extracts features from the labeled packets and uses machine learning to predict whether the overall communication flow succeeds or fails. Further models can help identify the root cause of a failure or determine the type of success.

This method aims to make network issue diagnosis more accurate and efficient. Zakaria has 1 patent listed in the provided information.

Career Highlights

Zakaria’s patent work focuses on applying machine learning to network packet analysis and telecommunications troubleshooting. His listed company affiliation is B.yond, Inc.

Collaborations

The provided information names Kenan Jarah and Jamal Atieh as Zakaria’s coworkers. It does not specify their roles in the patent or describe particular collaborative contributions.

Conclusion

Mohammad Zakaria’s listed invention applies machine learning to correlated network packet data to support faster, more precise diagnosis of telecommunications communication flows.

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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