Dr. Lynda Dib | Explainable Artificial Intelligence | Best Researcher Award
Universite Laval | Canada
Dr. Lynda Dib is a distinguished computer scientist and PhD candidate at Universite Laval, Canada, specializing in Explainable Artificial Intelligence (XAI) with a strong focus on applications in education. With over two decades of academic and research experience, she previously served as an associate professor and research director at the University of Annaba, Algeria, where she led projects in artificial intelligence, multi-agent systems, and computational modeling. Her academic journey has been marked by international collaborations in France, Canada, and across Europe, where she contributed to projects in genetics, pathology, and machine learning. As a prolific researcher, she has authored impactful publications on interpretability, explainability, and the integration of AI in educational and healthcare contexts. She is an active reviewer for prestigious journals, serves on scientific committees, and mentors doctoral candidates, solidifying her role as a global contributor to the advancement of ethical and reliable AI technologies.
Profile:
Scopus
Education:
Dr. Lynda Dib academic background is characterized by excellence and international breadth. She is currently pursuing a PhD in Computer Science at Université Laval, Canada, under the supervision of Prof. Laurence Capus, with a thesis centered on improving reliability and robustness of local explainability methods in machine learning models. Her prior academic achievements include a State Doctorate in Computer Science jointly completed at Université Badji Mokhtar, Annaba, Algeria, and LIP6, Université Pierre et Marie Curie, Paris, with a dissertation on computational modeling and videomicroscopy in cancer pathology. She further enriched her expertise through a postdoctoral fellowship at INRA, Orléans, France, specializing in quantitative genetics and mathematical modeling of phenotypic plasticity. She also holds advanced degrees in Computer Science, including a Master’s (Magistère), DEA, and State Engineer degree, all from Annaba, each awarded with distinctions. These milestones reflect her rigorous academic preparation and multidisciplinary foundation in AI and computational sciences.
Experience:
Dr. Lynda Dib professional experience spans academia, international research collaborations, and leadership in interdisciplinary projects.she has been an Associate Professor and Research Director at the University of Annaba, Algeria, where she also previously served as Lecturer and Senior Lecturer, and Assistant Lecturer. Her career highlights include leading national projects such as developing multi-agent anti-collision systems and designing ontologies for hospital patient monitoring. She has been actively engaged in European Union projects like NovelTree, Treebreedex, and CellPop, advancing research in genetics, modeling, and AI applications. In Canada, she has been affiliated with research groups including ERICAE and GRAAL at Université Laval, contributing to knowledge engineering and machine learning research. She has also been a visiting researcher at Université de Montréal and worked with INRIA Nancy, reflecting her global mobility. Her teaching, supervision, and research leadership highlight her academic and scientific versatility.
Awards and Honors:
Dr. Lynda Dib distinguished career has been recognized with multiple awards and honors across her academic journey. She was officially qualified for the Senior Lecturer (Maître de Conférences) position in France, marking international recognition of her expertise. Earlier, she received multiple academic distinctions for her exceptional performance, achieving top grades across her undergraduate, graduate, and doctoral studies. Her early academic promise was marked by a regional award for best mathematics performance in East Algeria, setting the foundation for her career in computational sciences. In addition to formal awards, she has been entrusted with roles of high responsibility, including serving as a jury member for doctoral theses and HDR evaluations, reviewer for prestigious journals such as Bioinformatics, Computers in Biology and Medicine, and JAAMAS, and committee member for leading conferences like ICSIP and AMINA. These honors underscore her leadership, academic excellence, and trusted role in shaping scientific discourse internationally.
Research Focus:
Dr. Lynda Dib research focus lies at the intersection of artificial intelligence, explainability, and educational technology. Currently, her doctoral work at Université Laval is dedicated to advancing explainable AI (XAI), specifically enhancing the reliability, consistency, and robustness of local interpretability methods in machine learning models. Her contributions aim to bridge the gap between technical AI models and human-centered understanding, particularly in education and healthcare contexts. Beyond her doctoral work, she has significant experience in multi-agent systems, computational modeling of biological processes, and ontology-based systems for decision support in hospitals. Her collaborative projects extend to genetics, phenotypic plasticity modeling, and forest improvement, reflecting her interdisciplinary expertise. With a strong publication record in Springer and Elsevier venues, she is actively engaged in shaping future directions of AI ethics, interpretability, and practical deployment in learning environments. Her research combines technical depth with a commitment to transparency and trustworthiness in AI technologies.
Publication:
Title: Is Lime Appropriate to Explain Polypharmacy Prediction Model
Year: 2025
Conclusion:
Dr. Lynda Dib presents an impressive academic and professional profile with a proven record of research leadership, publications, and international collaboration. Her specialization in Explainable Artificial Intelligence applied to education and healthcare adds both societal relevance and technical innovation, making her a strong candidate for the Best Researcher Award. With continued emphasis on top-tier publications, funding acquisition, and mentoring contributions, she is well-positioned to achieve even greater international recognition and significantly advance the field of artificial intelligence.