Ahmed Abdullah Omar -

Assistant Lecturer

Ahmed Abdullah Omar

Research Interests

Gender	MALE
Place of Work	College of Health and Medical Techniques / Kirkuk
Department	Medical Laboratory Techniques
Qualification	Master
Speciality	Computer Science (Applied Computing) - Robotics
Email	ahmedomer@ntu.edu.iq
Phone	0000000000
Address	Kirkuk, Kirkuk, Kirkuk, Iraq

Academic Links

Computer and Information Research Scientis

A researcher and assistant lecturer with a strong interest in artificial intelligence and robotics. Brings a professional background as a software engineer, with extensive experience in coding, debugging, web development, software design, and open-source contributions. Holds a master’s degree with focused training in continuous integration and delivery techniques.

Recognized multiple times as an outstanding student throughout the academic journey. Detail-oriented and tech-savvy, with proficiency in tools such as Git, GitHub, Docker, Jenkins, CircleCI, Android Studio, and Visual Studio. Skilled in object-oriented programming and cloud-based development environments.

Passionate about applying advanced programming techniques and research to solve real-world problems in AI and robotics.

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HyDrone Intelligent Water Surface Robot for Lake Conservation, supervised by Dr. Zati Hakim, was nominated by University of Malaya for the Commonwealth Science Conference 2021, presented as a poster at the Royal Society and African Academy of Sciences.

Skills

SQL (80%)

Python (80%)

C++ (80%)

ICT Management (80%)

Computer Network (100%)

Advance Microsoft Office Tools (Excel, Word, Access) (90%)

working experience

Academic Qualification

Masters in computer science (Applied Computing)

Sep 1, 2018 - Aug 1, 2021

Completed a mixed-mode program that combined advanced coursework and research, with subjects including Advanced Networking with Cisco Devices, Advanced Algorithms, Computer Vision, and Image Processing. The program concluded with a dissertation titled "Development of Water Surface Robot System for Lake Sanitation and Sampling", focusing on the design and implementation of a robotic solution for environmental monitoring and water quality improvement.

Bachelors in computer engineering (Computer Network)

Nov 1, 2012 - Aug 1, 2016

Received the Best Student of the Year award throughout all four years of undergraduate study, recognizing consistent academic excellence. In the final year, completed a project focused on securing images using AES and RSA encryption algorithms, developed with C# in Visual Studio.

Advanced Diploma in Continuous Integration and Continuous Delivery (CI/CD)

Aug 1, 2019 - Sep 30, 2019

Completed an Advanced Diploma in Continuous Integration and Continuous Delivery (CI/CD) at the University of Southern Denmark (Syddansk Universitet) as part of a summer school program. The course focused on modern DevOps practices, including automated build, test, and deployment pipelines, using tools such as Git, Jenkins, Docker, and cloud-based development environments.

Working Experience

Research Assistant [University of Malaya - Kuala Lumpur]

Oct 1, 2019 - Nov 1, 2020

Designed and developed an innovative robotic system for cleaning lakes, ponds, and other static water bodies, integrated with a feature for automated water sampling to support environmental monitoring and analysis.

Teaching Assistant [Al-Kitab University - Kirkuk]

Sep 1, 2016 - Apr 1, 2017

- Selected for the role after being recognized as the best student of the year and demonstrating strong subject proficiency.
- Promoted a collaborative learning environment to enhance student engagement, academic performance, and interpersonal skills.
- Assisted in preparing laboratory sessions and supported lecturers in fostering cognitive and social development through diverse teaching methods.

Publications

Applied AI in Water Surface Robotics for Lake Sanitation and Sampling

Feb 23, 2026

Journal 2025 International Conference on Robotics and Artificial Intelligence (ICRAI)

publisher IEEE

DOI https://doi.org/10.1109/ICRAI68431.2025.11396693

Low‑cost robotic systems for water sanitation and sampling are often limited by onboard computation and task‑specific designs, rarely addressing both functions simultaneously. This work introduces an intelligent water surface robot that integrates sanitation and sampling capabilities through real‑time mechanical control and sensor data streaming for off‑board analytics. By shifting computation to external servers, the system enables deployment of advanced algorithms without hardware constraints, with results communicated back for immediate robotic action. The design combines lightweight PVC structures that support up to 17 kg, electronics for cooling, battery monitoring, and sensor integration, as well as APIs for remote connectivity, mapping, and communication. Networking incorporates RTK localisation for precise positioning. Experiments demonstrate the performance of a genetic algorithm-based wayfinding approach with RTK localisation, as well as the deep learning-based floating trash detection from live video streams. This open robotic platform exemplifies applied intelligent systems, enabling robotics engineers to enhance hardware while AI researchers test and refine automation and vision models.

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