Seifedine Kadry
Peer Evaluator – Norway Region
Seifedine Kadry is a professor of Data Science at Noroff University College, Norway since November 2020. He holds a HdR (Habilitation Degree) in Engineering Sciences from Rouen University, France (2017) and a Ph.D. in Engineering Sciences from Blaise-Pascal University, France (2007). He also earned an M.S. in Applied Mathematics and Computer Science from EPFL Lausanne, Switzerland (2002) and a B.S. in Computer Science and Applied Mathematics from the Lebanese University (1999). Previously, he was a professor at the Department of Mathematics and Computer Science at Beirut Arab University and the founder and director of the Data Science Center there. He also held academic positions at the American University of the Middle East, Kuwait, and Lebanese University, Lebanon.
Prof. Kadry has extensive teaching experience, having taught courses such as NoSQL Database, Big Data Analytics, Discrete Mathematics, Automata Theory, Computing Statistics, Machine Learning, Data Science, AI, Business Statistics, Biostatistics, Probability, Statistics for Business, Probability for Engineering, Java Programming, Operating Systems, and Database. He has been actively involved in quality assurance and accreditation, serving as a member of various committees and as an accreditation expert for multiple organizations and countries.
His professional roles include being a European Project Fund Reviewer, IEEE Senior Member, Fellow of IET, IETE, and IASCIT, and serving as Editor in Chief of IJEECS and IJQCSSE journals, as well as Associate Editor of IEEE Access. He has led numerous research projects in fields like stochastic modeling, fatigue stochastic, and machine learning for medical imaging. He has supervised multiple PhD and Master theses on topics such as brain tumor classification, pricing European options with deep learning models, and big data in the telecommunication sector.
Prof. Kadry is proficient in Arabic, French, English, and has basic proficiency in Norsk. His computer skills include MATLAB, R, Python, FEMLAB, ANSYS, MAPLE, MATHEMATICA, Microsoft Access, Visual Basic, SQL server, Microsoft Office, and various web technologies. His research has been widely published in international journals, covering topics such as performance monitoring of hydropower plants using machine learning, fuzzy N-soft sets for cyber harassment identification, and federated learning for image processing in smart cities.
