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 🤖. He holds an M.S. in Artificial Intelligence and has a strong background in business strategy, management, and new business development 💼. He is the President of the UB Robotics Club and a member of various academic societies 🎓. Mohammed’s expertise includes ROS, SLAM, and AI, and he has significant experience in both academic and industry projects 🌍. He is passionate about leading innovative solutions and advancing user experiences 💡.
Profile:
Google Scholar
Education and Experience:
- Education 🎓: 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 💼: 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 ☁️, ROS Fundamentals 🛠, and Business Analytics 📊. 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 🌟. He is dedicated to growing as a researcher and applying his expertise to solve real-world challenges 🧠.
Research Focus:
Mohammed’s research focuses on Robotics, Machine Learning, and Artificial Intelligence 🤖. His work specifically includes reinforcement learning applied to Robotics Operating Systems (ROS) and CNN enhancement for AI tasks 🧠. He also explores practical applications of these technologies, aiming to improve system efficiency and human-robot interaction 🌐. His goal is to develop solutions that bridge the gap between theoretical research and real-world industrial applications 🌍.
Publications :
- “Comprehensive Review of Robotics Operating System-Based Reinforcement Learning in Robotics” – M Aljamal, S Patel, A Mahmood – Applied Sciences, 2025 📚
- “Enhancement of CNNHQ with an Activation Function” – A Kariri, M Aljamal, J Al Aridhee, I Albukhari, N Matondo-Mvula, K Elleithy – IEEE LISAT, 2023 📘