Dr. Mohamed Elbadawi is a Lecturer in Computational Physiology/Biomedicine at Queen Mary University of London's School of Biological and Behavioural Sciences. His research focuses on leveraging digital technologies like AI, robotics, and 3D printing to advance healthcare. He has received recognition as a Stanford Top 2% Scientist (2022-2023). Elbadawi holds a PhD in Mechanical Engineering from the University of Sheffield (2014-2017), an MSc in Biomedical Engineering from the University of Surrey (2012-2013), and a BSc in Pharmacology from the University of Bristol (2007-2010). His research interests include AI-driven drug discovery, 3D printing for precision medicine, bioelectronics for programmable drug delivery, and sustainability in pharmaceutical manufacturing. He leads modules like 'AI and Data Analytics in Physiology and Biomedicine' and 'Developing AI Solutions in the Biosciences.' Elbadawi has secured grants such as the £20,021 EPSRC-funded 'i-GREENPHARM' project and the £35,000 Innovate UK grant for 'Terpene enhancement of anxiolytic properties of cannabinoids.' He also collaborates with organizations like TSIP to develop community-focused AI solutions for medication management. His editorial roles include membership on the Frontiers in Industrial Microbiology editorial board. He actively publishes in journals like Materials Today Advances , ACS Sustainable Chemistry & Engineering , and International Journal of Pharmaceutics .










