I am a PhD candidate in Computational Biophysics at the University of Bologna. My work blends hydrogen–deuterium exchange mass spectrometry (HDX-MS), large-scale molecular dynamics, and modern AI architectures to decode the behaviour of both ordered and intrinsically disordered proteins.

Before starting my PhD, I completed an MSc in Medicinal and Biological Chemistry at the University of Edinburgh and earned a BSc in Pharmaceutical Sciences from MSA University in Egypt. My academic journey and research experiences developed my interest in the intersection of biology, chemistry and computational methods, especially in the context of proteins . This foundation sparked my passion for using simulations and AI to explore protein strctures and dynamics and support structure-based drug discovery.

I aim to contribute to open-source Python tools for studying protein dynamics and structures, and to collaborate with experimental researchers to validate and refine these tools—ultimately enhancing their effectiveness in computational biochemistry and structure-based drug design.

FutureData4EU Project

Awarded a Marie Curie (MSCA) COFUND scholarship through FutureData4EU, I am training to harness high-performance computing and big-data pipelines for health and enabling-technology applications. My doctoral research sits at the intersection of these pillars, with the goal of turning raw biophysical data into actionable molecular insights.

Key Competencies

• HDX-MS data analysis, protection factor estimation, and uptake modeling
• Molecular simulations and enhanced sampling (QM/MM, umbrella sampling, OpenMM, CP2K)
• Machine learning integration in biophysical modeling (scikit-learn, PyTorch)
• Scientific computing with Python (NumPy, pandas, Matplotlib) and workflow automation
• Open-source tool development and reproducible research practices