Ahmed Elsheikh is a Professor and computational engineer with 8+ years of postdoctoral and research experience bridging modern machine learning and multi-scale modelling to build computationally efficient digital twins for uncertainty quantification and risk assessment. Based at Heriot-Watt University and with prior research roles at UT Austin and Imperial College, he combines deep ML framework expertise with practical modelling developed through a PhD from McMaster. He actively applies his skills in competitive settings such as Kaggle and contributes to AI security and community initiatives—serving as an OWASP AI Exchange core author and GSoC 2025 mentor—highlighting a rare blend of academic rigor and applied security-minded engineering. Notably, his work spans both theory (EMNLP publications) and practice, focusing on robust, scalable approaches that make uncertainty-aware decision-making computationally tractable.
8 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD, ENGINEERING, Doctor of Philosophy - PhD, ENGINEERING at McMaster University
Bachelor's degree, ENGINEERING, Bachelor's degree, ENGINEERING at Al-Azhar University
Contributions:19 commits, 16 pushes, 1 branch in 19 days
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.