Researcher Image
نمير احمد فؤاد
PhD - assistant professor
AVI-Cinna E-learning Center , AVI-Cinna E-learning Center
[email protected]
Summary

Dr. Nemir Ahmed Al-Azzawi is currently an Assistance Professor at the Ibn Sina Center for E-Learning at the University of Baghdad, Iraq. He worked as a faculty member at the University of Baghdad for more than 10 years. His research interests focus on Sound modeling and compressions, Medical Image Analysis, Image Registration and Fusion, Artificial intelligence, and machine learning.

Qualifications

B.Sc in Electrical Engineering from College of Engineering, University of Al-Mustansiriya, 1995. M.Sc in Electronics and Communication from College of Engineering, University of Baghdad, 1997. Ph.D in Electrical and Electronics Engineering from the School of Electrical and Electronics, University of Science Malaysia USM, 2010.

Responsibility

Former member of the editorial board of Al-Khwarizmi journal. Undergraduate and postgraduate teaching Supervising postgraduate students Supervising B.Sc.’s students’ graduation projects Supervising B.Sc.’s students during summer training.

Awards and Memberships

In 1994, obtained a prize from the University of Al-Mustansiriya as he ranked 2 in his department.

In 1995, obtained the second prize after a competition held amongst the top Iraqi graduates from all Iraqi Universities in Electrical Engineering.

In 2007, obtained the award for the best supervisor in a graduation project for the academic year 2006-2007, College of Engineering / University of Technology and Applied Sciences-Oman.

In 2019, obtained the award for the best research paper presented at the International Conference ICICT 2019.

In 2019, obtained the award for the best presenter of his paper entitled " Security in telehealth applications: issues in medical image watermarking scheme through the shearlet transform".

In 2023, obtained the award for excellent work in the 2022 IIOE Arabic Micro-course Competition.

Research Interests

Focus on Sound modeling and compressions, Medical Image Analysis, Image Registration and Fusion, Artificial intelligence, and machine learning.

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