Summary
Eyad G is an AI researcher with 10 years of engineering experience who combines academic rigor—MSc in Computer Science from Western University—with practical systems work in ML, computer vision, and embedded software. He has authored eight peer-reviewed papers on topics spanning federated learning, medical imaging, and IoT security, and has delivered measurable results such as a 72% reduction in deep learning training time with minimal accuracy loss. At NORDIK he built a decade-long Twitter dataset and a Financial Stress Index for Canada using NLP and ML, while prior roles include improving Alzheimer’s and breast-cancer detection models and deploying high-accuracy vision pipelines for biomedical applications. Comfortable in Python, C/C++, Java and SQL, he also bridges research and production—optimizing IPC latency by 78% and automating grading workflows to scale instruction for 200+ students—revealing a pragmatic focus on efficiency as well as innovation.
10 years of coding experience
2 years of employment as a software developer
Bachelor of Applied Science - BASc, Computer Engineering, 3.51, Bachelor of Applied Science - BASc, Computer Engineering, 3.51 at Nile University
Master of Science - MS, Computer Science, 87, Master of Science - MS, Computer Science, 87 at Western University