Computational Models for Type 1 Diabetes (T1D)
Develop novel computational disease models that could be used to identify factors that impact the rapid/slow progression of Type 1 Diabetes (“T1D”) in infants and young children who are genetically pre-disposed and may be pre-symptomatic clinically. Such methodologies and models may
Role I lead the efforts of developing AI models for disease progression modeling, which lead to publications in high-impact journals such as Lancet D&E (IF 45), Lancet C&A (IF 38), Diabetes Care (IF 19), etc.
IBM Research. May 2017 - May 2022 .
Mohamed Ghalwash is an Associate Professor of Artificial Intelligence at Ain Shams University and Zewail City of Science, Technology, and Innovation. His research focuses on interpretable machine learning for spatio-temporal pattern discovery, with applications in healthcare analytics, health behavior modeling, and decision support, drawing on prior research leadership at IBM and Temple University. He has supervised eight postgraduate students across Ain Shams University and Zewail City, with thesis topics spanning security applications, Bayesian structure learning, and explainable AI, and currently serves as co-PI on a three-year STDF-funded grant (2026–2029, 2,700,000 LE) developing AI-driven immunoinformatics approaches for Foot-and-Mouth Disease vaccine design.
Alongside his academic research, he brings more than ten years of software engineering leadership across senior roles at IBM, Proteinea, Raya Software, and Asset Technology Group, spanning technical team leadership, software architecture, and large-scale enterprise system delivery. This engineering background has also shaped his applied research, extending into machine learning for security and biotech domains, including cryptanalysis and AI-driven vaccine design.