Dr. Chahira Cherif | Computer Science and Artificial Intelligence | Research Excellence Award
Université Oran 1 | Algeria
Dr. Chahira Cherif is an Associate Professor of Computer Science with a strong academic and research profile in higher education and software systems research. She holds a State Engineering degree in Computer Science, a Magister (Master’s) degree, and a Ph.D. in Computer Science, reflecting a solid and progressive academic foundation in computing and information technologies. Her professional experience includes service as a State Computer Science Engineer before transitioning into academia, where she has been actively engaged in teaching at both Bachelor’s and Master’s levels under the LMD system, along with supervising Master’s theses. Her research interests focus on intelligent software systems, software evolution, system security, and advanced computing methodologies, with active involvement in nationally recognized research initiatives, including the PREFU project on intelligent evolution and security of software systems. She has participated in international conferences, workshops, and scientific gatherings across Algeria and France, contributing to scholarly exchange and collaboration. Her scientific output is reflected through peer-reviewed publications indexed in international databases, with an established h-index-1 supported by multiple research documents-5 and citation-4 records. Through her combined roles as educator, researcher, and project contributor, she continues to make meaningful contributions to computer science research and academic development, strengthening innovation, knowledge dissemination, and the advancement of intelligent and secure software systems.
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Featured Publications
Predictive approach to the degree of business process change
International Journal of Computing and Digital Systems, 14(1), 10505–10513, 2023 · Citations: 5
Change impact study by Bayesian networks
Modeling Approaches and Algorithms for Advanced Computer Applications, pp. 429–438, 2013 · Citations: 5
Cancer classification through the selection of genes extracted from microarray data
Przegląd Elektrotechniczny, 101(4), 2025 · Citations: 4
Étude de l’impact de changement dans les systèmes à objet par les réseaux bayésiens
Communication Science et Technologie, 13(1), pp. 90–108, 2015 · Citations: 4
Towards a probabilistic approach for better change management in BPM systems
IEEE 23rd International Enterprise Distributed Object Computing Conference, 2019 · Citations: 3