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OverView
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Hussein Alahmer is an academic and researcher specializing in Artificial Intelligence (AI), optimization, and computer vision. I completed PhD in AI, with a focus on computer vision, from the University of Lincoln in 2018. Driven by a passion for advancing the field, my research has primarily revolved around the application of optimization techniques to solve engineering problems, with a particular emphasis on AI and computer vision. My expertise lies in leveraging optimization algorithms to enhance the performance and efficiency of complex engineering systems. Additionally, from my experience of AI and computer vision enables me to develop innovative approaches for image and video analysis, object recognition, and scene understanding. Currently, I serves as an assistant professor at Al Balqa Applied University, contributing to the College of Artificial Intelligence. In this role, I plays a vital role in educating and mentoring students, helping them grasp the fundamentals of AI, optimization and computer vision and empowering them to apply these concepts to real-world challenges. With a strong commitment to research and teaching, I continues to make significant contributions to the field, driving advancements in optimization, AI, and computer vision.
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Research Intersets:
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Optimization, Deep Learning, Computer Vision, Natural language processing, Medical image processing
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Qualifications
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Degree
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University
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Specialization
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Graduation year
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1 | PHD | University of Lincoln | Computer Science | 2018 | 2 | MASTER DEGREE | University of Sunderland | Computer Science | 2012 | 3 | BACHELOR'S DEGREE | Mutah university | Computer Science | 2004 |
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Experiences
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Academic Experience:
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2018 -Current :Assistant Professor,Al-Balqa Applied University,Jordan.
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Administrative Experience:
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2023 -Current :Vice Dean for Student Affairs,Al-Balqa Applied University,Jordan. 2020 -2023 :Assistant Dean for Quality Affairs,Al-Balqa Applied University,Jordan.
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Publications
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1- Retrofitting conventional chilled-water system to a solar-assisted absorption cooling system: Modeling, polynomial regression, and grasshopper optimization ,Journal of Energy Storage, 2023,Vol. 65,no. . 2- Optimal Water Addition in Emulsion Diesel Fuel Using Machine Learning and Sea-Horse Optimizer to Minimize Exhaust Pollutants from Diesel Engine ,Atmosphere, 2023,Vol. 14,no. 3. 3- Applied Intelligent Grey Wolf Optimizer (IGWO) to Improve the Performance of CI Engine Running on Emulsion Diesel Fuel Blends ,Fuels, 2023,Vol. 4,no. 1. 4- Modeling, polynomial regression, and artificial bee colony optimization of SI engine performance improvement powered by acetone-gasoline fuel blends ,Energy Reports, 2023,Vol. 9,no. 3. 5- Exhaust emission reduction of a SI engine using acetone-gasoline fuel blends: Modeling, prediction, and whale optimization algorithm ,Energy Reports, 2022,Vol. 9,no. 1. 6- Environmental assessment of a diesel engine fueled with various biodiesel blends: Polynomial regression and grey wolf optimization ,Sustainability, 2022,Vol. 14,no. 3. 7- Modeling and optimization of a compression ignition engine fueled with biodiesel blends for performance improvement ,Mathematics, 2022,Vol. 10,no. 3. 8- A robust deep learning approach for glasses detection in non-standard facial images ,IET Biometrics, 2020,Vol. 10,no. 1.
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University Courses Taught
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1- Introduction to optimization. 2- Deep learning. 3- Knowledge representation and reasoning. 4- Machine learning. 5- Robot vision. 6- Computer architecture. 7- Artificial intelligence programming. 8- Computer vision. 9- Robotics Lab 1. 10- Robotics lab 2.
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Conferences and Workshops
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Conference/Workshop Name
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Conference/Workshop Place
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Conference/Workshop Date
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1 | International Conference on Power, Energy and Electrical Engineering (PEEE) | Spain | 2022/11 | 2 | International Conference on Power and Energy Systems Engineering (CPESE) | Japan | 2022/09 |
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