Dr. Nawel Ben Chaabane | Visual Awards | Best Researcher Award
Dr. Nawel Ben Chaabane | Audensiel | France
Dr. Nawel Ben Chaabane is an accomplished data scientist and researcher in artificial intelligence with strong expertise in machine learning, deep learning, and predictive modeling. She has developed cutting-edge applications in healthcare, medical imaging, and signal processing, bringing advanced AI methods to real-world challenges. Her career reflects a balance between academic research, professional engineering, and teaching, all driven by a passion for using AI to enhance decision-making, diagnostics, and human well-being.
Professional Profile
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Summary of Suitability
Dr. Nawel Ben Chaabane holds a Ph.D. in Artificial Intelligence (University of Western Brittany, LATIM, France) with a strong specialization in AI for healthcare. Her doctoral research focused on the prediction of pathological evolution through physiological signal analysis, particularly using deep learning approaches such as LSTMs and time-LSTMs for gait profile prediction. She also holds a Master’s in Information Processing and an Engineering degree in Computer Science, both completed with distinction.
Education
She completed her doctorate in Artificial Intelligence at the University of Bretagne Occidentale, LATIM, where her research focused on the predictive analysis of physiological signals for monitoring pathological progression, with a particular emphasis on quantified gait analysis. Prior to this, she obtained a master’s degree in Information Processing through a co-diploma program between the École Nationale d’Ingénieurs de Tunis and the University of Paris 5, graduating with honors and ranking second in her class. She also earned an engineering degree in Computer Science from the Institut National des Sciences Appliquées et de Technologie in Tunisia, where she laid the foundation for her expertise in computational methods, signal processing, and AI systems.
Experience
Her professional path integrates both research and industry applications. She currently serves as an R&D Engineer in Artificial Intelligence at Audensiel, leading projects such as SIRS-Bot, a medical diagnostic and prognostic chatbot powered by deep learning models applied to clinical imaging and reasoning. Previously, she worked as a software engineer developing hospital IT solutions at Dapsys, contributing to process optimization in healthcare systems. She also has academic teaching experience as a lecturer in computer development at the University of Bretagne Occidentale and as an online instructor in computer science and mathematics. Her earlier research experience includes work at the Laboratoire Informatique d’Avignon, where she developed speech recognition methods for mobile robots using deep learning under noisy conditions.
Research Interest
Her research interests span a wide spectrum of artificial intelligence and data science, with particular focus on medical applications. These include predictive modeling for healthcare outcomes, analysis of physiological signals such as gait patterns, speech processing in challenging environments, and the integration of AI for clinical decision support. She is especially engaged in advancing time-series modeling with LSTM and Transformer-based neural networks, deep learning for biomedical imaging, and natural language processing in healthcare contexts. Her interest in interdisciplinary AI allows her to bridge technical innovation with impactful applications in human health and diagnostics.
Awards and Recognition
She has participated in several international schools and specialized training programs that reflect her recognition in the scientific community. These include advanced summer schools and workshops on deep technology, industry 4.0, nanotechnology, and AI for healthcare organized by leading universities and medical centers in Europe. She has also been recognized for her academic excellence with distinctions in her master’s program, highlighting her dedication and outstanding performance throughout her academic and professional journey.
Publication Top Notes
Visual question answering for medical diagnosis
Conclusion
Dr. Nawel Ben Chaabane is an innovative researcher and data scientist whose contributions to artificial intelligence extend across predictive modeling, deep learning, and healthcare applications. With an outstanding educational background, extensive academic research, and professional expertise in both teaching and applied engineering, she exemplifies the qualities of a forward-thinking scientist. Her pioneering work in physiological signal analysis, healthcare-focused AI, and predictive diagnostics highlights her ability to create solutions with tangible societal impact. Through her research, teaching, and industry projects, she has consistently demonstrated leadership, technical depth, and creativity, making her a strong candidate for award nomination and recognition in the field of artificial intelligence and data science.