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Dr. Ameni Boumaiza

Title
Scientist
Email:
aboumaiza@hbku.edu.qa

Dr. Ameni Boumaiza is currently working as a Scientist at Qatar Environment and Energy Research Institute (QEERI), Hamad Bin Khalifa University. She is serving as a Project Lead of the PV Adoption and Trade project under the Energy Management Program and has worked on several projects funded by the Qatar National Research Fund. Her primary research focus is on Solar Energy management and smart systems based on AI. She has completed several studies on solar PV adoption, techno-economic modeling of energy systems and energy trading applications based on the Blockchain technology.

Prior to joining HBKU/QEERI, Dr. Ameni Boumaiza received a full PhD merit-based scholarship from the Ministry of Higher Education and Research in France. She got her PhD in 2013 in Computer Engineering from the French Institute for Research in Computer Science and Automation INRIA and the University of Lorrain, France and from the Computer Vision Center CVC in UAB Barcelona, Spain. She has held various positions in academia and industry in France. She was a part of the French Alternative Energies and Atomic Energy Commission Institute CEA-List and the Vision and Content Engineering Lab LVIC in Saclay, Paris, France. Having benefited from closed interactions with laboratories, companies such as CEA-LVIC, INRIA, Thales, she got a strong background in artificial intelligence, renewable energy systems, computer vision, machine learning and robotics.

Her scientific research focuses on strategies addressing energy systems, artificial intelligence, robotics, image processing data science with an emphasis on data mining and machine learning and evaluative techniques to create solutions to complex challenges. She is specialized in software development modeling, simulation, testing, and quality assurance. She managed complex technical BI projects and collaborated directly with global engineering and research teams to create business intelligence solutions, and identify and assess new technologies prior to the software implementation.

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