VERIMAG - Université Grenoble alpes - France
AUTHOR PROFILE
EARLY ACADEMIC PURSUITS
Salim Chehida's academic journey commenced with an Engineer Degree in Computer Science from the University of Mostaganem, Algeria. He furthered his studies with a Magister Degree in Information Systems Engineering and eventually pursued a Ph.D. in Computer Science specializing in Software Engineering and Systems Security from the University of Oran 1 in Algeria in collaboration with the University of Grenoble Alpes in France.
PROFESSIONAL ENDEAVORS
Dr. Salim Chehida has had a diverse professional career, starting as a Software Engineer at the Finance Direction in Algeria and later transitioning to roles as a Scientific Researcher and Assistant Professor at the University of Mostaganem, Algeria. Currently, he serves as a Research and Development Expert at the University of Grenoble Alpes in France, contributing significantly to the fields of Software Engineering and Deep Learning.
CONTRIBUTIONS AND RESEARCH FOCUS
Dr. Chehida's expertise lies in Software Engineering, particularly in the design, development, security, verification, and validation of software systems. He has made notable contributions to various innovative projects, including those related to cyber-physical systems (CPS) and Internet of Things (IoT) systems. His research focuses on deep learning applications, including image classification, segmentation, and object detection, as well as smart grid security.
IMPACT AND INFLUENCE
Dr. Chehida's research and development work have had a significant impact on academia and industry, particularly in the domains of software engineering and deep learning. His involvement in numerous projects, collaborations with companies and institutions worldwide, and contributions to conferences and publications have established him as a respected expert in his field.
ACADEMIC CITES
Dr. Chehida's publications and technical reports have been widely cited, reflecting the importance and relevance of his research contributions. His work in smart grid security and deep learning applications has garnered attention from researchers and professionals in academia, industry, and government organizations.
LEGACY AND FUTURE CONTRIBUTIONS
As Dr. Chehida continues to advance his research and development endeavors, his legacy in the fields of software engineering and deep learning is assured. His future contributions are expected to further enhance our understanding and application of smart grid security measures and deep learning techniques, addressing critical challenges in cybersecurity and artificial intelligence for years to come.
NOTABLE PUBLICATION
Model-based Self-adaptive Management in a Smart Grid Substation 2023 (2)
Generation and verification of learned stochastic automata using k-NN and statistical model checking 2022 (1)
Learning and analysis of sensors behavior in IoT systems using statistical model checking 2022 (5)