Mr. Mohammed Aljamal | Artificial intelligence and Robotics | Best Researcher Award
PhD Candidate In Computer Science and Engineering, University of Bridgeport , United States
Mohammed Aljamal is a Ph.D. candidate in Computer Science & Engineering at the University of Bridgeport, specializing in Robotics and Machine Learning ๐ค. He holds an M.S. in Artificial Intelligence and has a strong background in business strategy, management, and new business development ๐ผ. He is the President of the UB Robotics Club and a member of various academic societies ๐. Mohammedโs expertise includes ROS, SLAM, and AI, and he has significant experience in both academic and industry projects ๐. He is passionate about leading innovative solutions and advancing user experiences ๐ก.
Profile:ย
Education and Experience:
- Education ๐: Ph.D. in Computer Science & Engineering (2022-2026) – University of Bridgeport; M.S. in Artificial Intelligence (2020-2021) – University of Bridgeport; Business Analytics (2020) – University of Illinois; B.S. in Mechanical Engineering (2001-2006) – Al Mustansiriya University.
- Experience ๐ผ: Labs Engineer (2022-Present) – University of Bridgeport; Technology Solutions Advisor (2015-2017) – Zee-Group; Deputy Director (2013-2015) – Mega Planet; Business Development Manager (2010-2013) – Al Otaiba Enterprises.
Professional Development:
Mohammed has continually developed both his technical and leadership skills. He holds certifications in AWS Cloud Foundations โ๏ธ, ROS Fundamentals ๐ , and Business Analytics ๐. His experience as a leader in academic and industrial settings has honed his problem-solving abilities, project management expertise, and the ability to design innovative solutions ๐. He is dedicated to growing as a researcher and applying his expertise to solve real-world challenges ๐ง .
Research Focus:
Mohammed’s research focuses on Robotics, Machine Learning, and Artificial Intelligence ๐ค. His work specifically includes reinforcement learning applied to Robotics Operating Systems (ROS) and CNN enhancement for AI tasks ๐ง . He also explores practical applications of these technologies, aiming to improve system efficiency and human-robot interaction ๐. His goal is to develop solutions that bridge the gap between theoretical research and real-world industrial applications ๐.
Publications :
- “Comprehensive Review of Robotics Operating System-Based Reinforcement Learning in Robotics” – M Aljamal, S Patel, A Mahmood – Applied Sciences, 2025 ๐
- “Enhancement of CNNHQ with an Activation Function” – A Kariri, M Aljamal, J Al Aridhee, I Albukhari, N Matondo-Mvula, K Elleithy – IEEE LISAT, 2023 ๐