Prof. Raed Abu Zitar | Machine Learning in Tracking | Best Researcher Award

Prof. Raed Abu Zitar | Machine Learning in Tracking | Best Researcher Award

Prof. Raed Abu Zitar, Sorbonne University, United Arab Emirates

Prof. Zitar is a distinguished academic with a Ph.D. in Computer Engineering focused on Artificial Intelligence and Neural Networks from Wayne State University. With a robust background that includes a Masterā€™s in Genetic Algorithms and a Bachelorā€™s in Electrical Engineering, he has had a notable career as a Senior Research Scientist and Chair of Excellence at the Sorbonne Center of Artificial Intelligence, Sorbonne University, Abu Dhabi. His research, which includes advanced work on drone detection and tracking, spans AI, machine learning, and robotics. Notable for his contributions to metaheuristic optimization and machine learning, Prof. Zitar has received prestigious awards such as the ASAI and UNESCO Fellowships, and has been recognized for his leadership and innovative work in the field.

Professional Profile:

Scopus
Orcid
Google Scholar

Suitability for the Research for Best Researcher Award

Prof. Raed Abu Zitar is a highly suitable candidate for the Research for Best Researcher Award due to his extensive expertise and significant contributions to the fields of Artificial Intelligence, Machine Learning, Robotics, and Computer Vision. His educational background includes a Ph.D. in Computer Engineering with a focus on Artificial Intelligence and Neural Networks from Wayne State University, complemented by a Masterā€™s in Computer Engineering and a Bachelorā€™s in Electrical Engineering. This robust academic foundation underpins his diverse research interests and accomplishments.

Dean of Faculty of Computing and Engineering, Liwa College šŸŽ“
Prof. Raed Abu Zitar is the Dean of the Faculty of Computing and Engineering at Liwa College, Abu Dhabi. He began this role in September 2024, leading the faculty in advancing computing and engineering education.

Academic Background šŸ“š

Prof. Zitar holds a Ph.D. in Computer Engineering with a focus on Artificial Intelligence and Neural Networks from Wayne State University, where he explored machine learning with rule extraction. He also earned a Masterā€™s in Computer Engineering with a specialization in Genetic Algorithms from North Carolina A&T State University and a Bachelorā€™s in Electrical Engineering from the University of Jordan.

Professional Experience šŸ’¼

Prof. Zitar has a distinguished career as a Senior Research Scientist and Chair of Excellence at the Sorbonne Center of Artificial Intelligence, Sorbonne University, Abu Dhabi, from February 2021 to September 2024. His work there focused on drone detection and tracking using advanced machine learning techniques. He was also the Founding Coordinator of the Master of Artificial Intelligence Program at Ajman University and managed the Teaching and Learning Center.

Research Interests and Contributions šŸ”¬

His research spans various areas, including artificial intelligence, machine learning, robotics, computer networks modeling, and computer vision. He has published significant papers on the JAYA algorithm and renewable energy optimization techniques, demonstrating his expertise in metaheuristic optimization and advanced machine learning applications.

Awards and Recognitions šŸ†

Prof. Zitar has received several prestigious awards, including the ASAI and UNESCO Fellowships. He was honored for supervising the Best Graduation Projects at Ajman University and received an Appreciation Award from CUCA University for his contributions to the Smart Learning Conference.

Innovations and Impact šŸš€

Prof. Zitarā€™s extensive research and leadership in AI and machine learning have made a notable impact on the field. His work continues to influence advancements in energy optimization and computational methods, reflecting his commitment to pushing the boundaries of technology and education.

Publication Top Notes:

  1. Title: Wind, Solar, and Photovoltaic Renewable Energy Systems with and Without Energy Storage Optimization: A Survey of Advanced Machine Learning and Deep Learning Techniques
    • Citations: 104
    • Year: 2022
  2. Title: Gene Selection for Microarray Data Classification Based on Gray Wolf Optimizer Enhanced with TRIZ-Inspired Operators
    • Citations: 95
    • Year: 2021
  3. Title: Development of an Efficient Neural-Based Segmentation Technique for Arabic Handwriting Recognition
    • Citations: 88
    • Year: 2010
  4. Title: Multiclass Feature Selection with Metaheuristic Optimization Algorithms: A Review
    • Citations: 86
    • Year: 2022