On January 20, 2026, the Electrical Engineering Department – IRC for Communication System and Sensing at King Fahd University of Petroleum & Minerals (KFUPM) hosted a seminar titled “From Model to Silicon: A Comprehensive Guide to Edge-AI Implementation Frameworks.” The seminar was delivered by Dr. Atif Raza Jafri from the Electronics and Nanoscale Engineering Division, James Watt School of Engineering, University of Glasgow (Scotland).

The talk highlighted the rapid shift in artificial intelligence from cloud-only processing to running AI inference directly on edge devices. Dr. Jafri discussed the key benefits of Edge-AI—including improved privacy and security, ultra-low latency for real-time applications, reduced data transmission, and enhanced energy efficiency—while emphasizing the practical challenges of deploying AI at the edge.

The seminar presented a comprehensive perspective on Edge-AI implementation, focusing on how developers and researchers can integrate specialized software tools with optimized hardware platforms to translate AI models into efficient, real-world deployments across diverse device architectures.

The following are the highlights of the event: