Dr. Hiba Alsmadi is a distinguished researcher and expert in AI and Data Science. With a PhD in Computer Science – AI from Liverpool John Moores University, her work has consistently pushed the boundaries of innovation in using AI in health and has been awarded The Faculty PVC’s Award for the Best PhD Thesis. She has authored numerous impactful papers, contributing significantly to the academic discourse. Driven by a passion for advancing technology for societal benefit, she actively engages in many research projects in many areas such as education, healthcare ,business and sport science. Her commitment is to disseminate cutting-edge research to a global audience. In addition, she is the organizer for the event of women in AI which celebrates the achievements of women who are transforming the field of artificial intelligence. The event is featuring inspiring stories from innovators across industries such as healthcare, finance, and education, showcasing their groundbreaking contributions and leadership.

Dr. Hiba is actively engaged in the collaborative agreement between Teesside University and Middlesbrough Football Club (MFC), which is designed to facilitate the exchange of expertise and promote innovative research into the application of artificial intelligence within sports science. Furthermore, this collaboration provides students with the opportunity to apply advanced AI techniques to authentic datasets supplied by MFC, thereby enhancing their practical and research skills. Dr. Hiba's contributions continue to shape the future of AI and inspire the next generation of innovators. Here some projects that she worked on:

1. Evaluating AI's Impact on Health Life Expectancy Disparities Among Marginalized Communities.
2. Developing a new method to help physicians diagnose spinal deformities using 3D images. The method starts by segmenting the images to extract the region of interest by using FeaStNet, a GCN-based model.
3. Proposing a novel methodology to automatically aid clinicians in performing the diagnosis of Chronic Lower Back Pain (CLBP) on lumbar spine Magnetic Resonance Imaging (MRI) images.
4. Developing a computer vision system capable of capturing and analysing the motion and movements of physiotherapy practitioners during practical examinations.
5. Evaluating the Effectiveness of AI-powered Chatbots in improving critical thinking and clinical skills for healthcare students in SHLS.
6. Brain tumour classification in MRI images and treatment suggestions using deep learning.
7. Predictive analysis to identify important metrics of MFC team for a successful performance.
8. Developing an optimized Promotional Strategy using AI for food heck company
9. AI- Powered instant textual feedback on physiotherapist student practical performance