Abu Dhabi, United Arab Emirates

Mohammed F Tolba

This inventor holds 1 USPTO granted patent. Top assignee: Khalifa University of Science and Technology. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Mohammed F Tolba. Retrieved from https://idiyas.com/inventor/mohammed-f-tolba

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: Innovations by Mohammed F Tolba

Introduction

Mohammed F Tolba is a prominent inventor based in Abu Dhabi, AE. He has made significant contributions to the field of artificial intelligence, particularly in the area of deep neural networks. His innovative approach focuses on reducing memory storage and energy consumption in AI edge devices.

Latest Patents

One of his notable patents is titled "Approximate computing and data reuse architectures for AI edge devices." This method aims to enhance the efficiency of deep neural networks by determining the weights associated with them. The process involves receiving an input feature map and utilizing the weights to generate approximated weights. By employing these approximated weights along with the input feature map, a convolution inference can be performed, leading to reduced resource usage.

Career Highlights

Mohammed F Tolba is affiliated with Khalifa University of Science and Technology, where he continues to advance his research and innovations. His work is instrumental in pushing the boundaries of AI technology and its applications.

Collaborations

He collaborates with esteemed colleagues such as Hani Saleh and Mahmoud Al-Qutayri, contributing to a dynamic research environment that fosters innovation.

Conclusion

Mohammed F Tolba's contributions to AI and deep learning exemplify the impact of innovative thinking in technology. His work not only addresses current challenges but also paves the way for future advancements in the field.

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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