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Hafida Benhidour

Assistant Professor

Department of computer Science, King Saud University

علوم الحاسب والمعلومات
Building 6, third floor, office 31. P.O. 22452. Riyadh 11495

introduction/brief CV

I am an assistant professor in the Department of Computer Science at King Saud University. I have been contributing to the academic and research community since October 2011. My research primarily focuses on the interdisciplinary applications of machine learning and deep learning, with particular interests in computer vision, and natural language processing. I am also interested in complex networks and recommender systems.

I earned my PhD in Computer Science from the University of Tsukuba, Japan, in 2009, following my M.S. and engineering degrees in Computer Science from the Institut National d’Informatique (INI), Algeria. During my studies, I was honored to receive the Monbukagakusho scholarship from Japan's Ministry of Education, which supported me from 2004 to 2008.  After my PhD studies, I spent two years as a researcher in the Humanistic System Lab at the University of Tsukuba in Japan.

I have supervised various projects and theses, covering topics related to deep learning, complex networks, and recommender systems.

My teaching portfolio includes a variety of courses at both undergraduate and graduate levels, including artificial intelligence, machine learning, data structures, and theory of computation.

areas of expertise

Machine learning, deep learning, computer vision, natural language processing, complex networks, and recommender systems.

publications
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courses
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course

AI problem solving - Knowledge representation - Automatic theorem proving - Learning by example - Learning by analogy - Learning by discovery - Self-reference and Self-production - Reasoning:…

course

Fundamental concepts of data structures. Performance measurement of algorithms. Implementation and use of lists, stacks, queues, priority queues, trees, heaps, hash tables and graphs. Recursion.…

course

Fundamental concepts of data structures. Performance measurement of algorithms. Implementation and use of lists, stacks, queues, priority queues, trees, heaps, hash tables and graphs. Recursion.…