U O Z

Loading


Zhehat Rebar Abdulqader

Zhehat Rebar Abdulqader

  • Email: Zhehat.abdulqader@uoz.edu.krd
  • Working address: Presidency - A / Floor 1 / 24 (Office)
Contact Me
Follow Me

Bio

I am Zhehat Rebar Abdulqader, an Information Technology Specialist, Programmer, Developer, and Academic Researcher from Duhok, Kurdistan Region – Iraq. I have a strong academic and professional background in Information Technology and Computer Science, complemented by extensive experience in software development, database management, web development, networking, and IT systems administration.

I hold a Master’s degree in Information Technology from Duhok Polytechnic University, College of Informatics, Department of Information Technology, and a Bachelor’s degree in Computer Science from the University of Zakho, College of Science, Department of Computer Science. My academic background has provided me with a solid foundation in both theoretical knowledge and practical applications of modern computing and information technologies.

Professionally, I have advanced expertise in the design, development, implementation, and management of databases, websites, software applications, and IT systems. I also possess strong competencies in programming, computer networking, web application development, and system administration, with a focus on developing reliable, efficient, and scalable technological solutions.

As a researcher, my primary areas of interest include Deep Learning, Data Science, Internet of Things (IoT), and Computer Vision. I am particularly interested in applying artificial intelligence and emerging technologies to address complex real-world problems and contribute to innovative and impactful research.

In addition to my technical and research expertise, I have substantial experience in teaching, training, and academic mentoring. I have supported and guided students and professionals in areas including programming, networking, system administration, and information technology, with an emphasis on practical learning, technical development, and continuous professional growth.


Specialties

Artificial Intelligence (AI)

Image  Classification


Area of Interest

Artificial Intelligence (AI), Deep Learning (DL), Machine Learning (ML), Image Processing and Classification, Data Science, Internet of Things (IoT), Programming Languages.

Experience name
Researcher | Deep Learning Models, Machine Learning Models, Image Classification, Computer Vision, Internet of Things.
Teaching/Training | Curriculum development, Technical training delivery, Teach.
Artificial intelligence | Experience with AI, ML, and DL.
Programming | C++, Python, SQL, C#, PHP.
Web Application Development | Back-end, Front-end Developer.
System Administration | Databases, Systems, Websites, IT Support, Maintenance.
Graphic Design | Interior Book design, Roll-up, Poster, Social Media Management.
Committee name Actions
Continuing Education Monitoring Committee in Crisis
Conference Preparatory Committee
Social Media Managing Committee
Registration Committee
Examination Committee
Registration Committee
ICT & Statistics Center
Thesis title Actions
Develop a deep learning model for skin disease detection and classification
Article title Actions
Deep Learning-Based Skin Disease Detection and Classification
Deep Learning-Based Skin Disease Detection and Classification: A Systematic Literature Review
Responsible AI Development for Sustainable Enterprises A Review of Integrating Ethical AI with IoT and Enterprise Systems
Deep and Machine Learning Algorithms for Diagnosing Brain Cancer and Tumors
Conference name Actions
International Conference on Advanced Science and Engineering (ICOASE2025)
Training course name Date Organizing organization
Pedagogical Training Course for Teacher Professional Development 2026-08-20 Duhok Polytechnic University - Pedagogical Training and Academic Development Center
Imperial English - UK 2024-07-30 Duhok Polytechnic University - Language Center
Language Proficiency
Kurdish Fluency
English Advance
Arabic Advance

Week Time Table

Academic year: 2026 - 2027 Semester: Fall (Autumn)

Day 09:00–10:00
Sunday
ICT
Monday
Tuesday
Wednesday
Thursday

Sunday

  • 09:00–10:00
    ICT