Profile

Hela Limam

University of Tunis El Manar

Domain of Research: Intelligent Systems,Artificial Intelligence,Software Engineering and Quality,Data Science,Decision Making,Decision Support Systems

Dr. Hela LIMAM is an Associate Professor of Management Information Systems at the Higher Institute of Computer Science (Institut Supérieur d’Informatique - ISI), University of Tunis El Manar, Tunisia. She is also affiliated with the BestMOD Research Laboratory at ISG Tunis, where she actively contributes to scientific and academic research in information systems and data science. Dr. LIMAM holds a Habilitation Degree (HDR) in Management Sciences (July 2023), a PhD in Management Information Systems (June 2014), a Master's degree in Management Information Systems (September 2007), and a Bachelor’s degree in Applied Computer Science in Management (June 2005). She earned her High School Diploma in Sciences in 2001 from La Sagesse Brasilia School in Lebanon. Her research interests are broad and interdisciplinary, focusing on: • Semantic Web and Online Community Management • Artificial Intelligence applications in Healthcare, particularly Ischemic Stroke Prediction • Machine Learning techniques for medical data analysis • Semantic Caching and Web Service Optimization • Data Science and Predictive Modeling She has co-authored several papers, including: • “Applications of artificial intelligence for DWI and PWI data processing in acute ischemic stroke: Current practices and future directions”, published in Clinical Imaging • “Automatic triaging of acute ischemic stroke patients for reperfusion therapies using Artificial Intelligence methods and multiple MRI features: A review”, also in Clinical Imaging • “A Hybrid Approach for Predicting the Evolution of Ischemic Stroke Lesion Volume” (with Manel Bouajjar) • “Selection of predictive characteristics for ischemic stroke with Machine learning technique” (with Eya Jouini) Dr. LIMAM is also developing a semantic approach to managing online communities, titled “ESWCM: An Event-Driven Semantic Web Community Management Approach”, in collaboration with Ahlem Slaimi. This work enhances traditional ontologies like FOAF and SIOC to better model user engagement patterns such as self-esteem, collaboration, and friendship. She has supervised various research and master’s theses, particularly in the areas of digital health, web technologies, and AI-based systems. In addition to her academic and research contributions, Dr. LIMAM is actively involved in scholarly reviewing and conference organization. She has applied for roles in international program committees and is engaged with global research communities, particularly those focusing on data science and AI in healthcare.