CV

You can find a short academic CV below. For more details, connect with me on LinkedIn.

Current Position

I currently work as a researcher and data engineer at the National Aid Fund in Jordan, where I focus on developing intelligent systems to support social protection programs using real-world data, analytics, and AI-driven tools.

Previous Experience

• AI Researcher – National Aid Fund (2021-Present)
  Conducting comprehensive data analysis to inform decision-making, program development, and reporting requirements.
• Master’s Researcher – PSUT (2019–2022)
  Developed a discretization algorithm based on rough set theory. Focused on machine learning, symbolic AI, and medical imaging applications.
• Teaching Assistant – PSUT (2019–2020)
  Assisted in data science, machine learning, and programming courses.
• E-Tutor – JOVITAL EU Project (2019–2020)
  Mentored international student teams across Jordan, Slovenia, Germany, and Italy in virtual collaboration.

Education

• MSc in Data Science – Princess Sumaya University for Technology, Jordan (2019–2022)
• BSc in Software Engineering – Al-Hussein Bin Talal University, Jordan (2016–2019)
  Graduated First in Class (Highest Honors)

Research & Technical Interests

My academic focus includes symbolic AI, rough set theory, machine learning, neural networks, and deep learning models for medical image segmentation. I’m also passionate about the ethical and social applications of AI in public sectors.

Skills

• Python, SQL, C++, JavaScript, HTML/CSS
• PyTorch, TensorFlow, Scikit-learn, OpenCV, FastAPI
• PostgreSQL, SQLite, MongoDB
• Git, Docker, Jupyter, Linux

Languages

• Arabic: Native
• English: Fluent (Academic MOI)

Publications

• Alnawafleh, T. M., Radzi, Y., Alshilpi, M., Oglat, A. A., & Alflahat, A. (2024). A Comprehensive Review of the Recent Advancements in Imaging Segmentation and Registration Techniques for Glioblastoma and Focusing on the Utilization of Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) Scans. Current Medical Imaging.
• Alflahat, A. (2023, Feb). An Efficient Discretization Algorithm Using Rough Set Theory. UNER Peer Review.
• Alflahat, A. T. (2022). An Efficient Discretization Algorithm Using Rough Set Theory (Doctoral dissertation, Princess Sumaya University for Technology, Jordan).
• Alflahat, A. (2021, Feb). IoT Powered by Big Data: Architecture, Ecosystem, Applications. International Journal of Circuits, Systems and Signal Processing (NAUN).
• Razaque, A., Li, Y., Liu, Q., Khan, M. J., Doulat, A., Alflahat, A. (2018, Oct). Enhanced Risk Minimization Framework for Cloud Computing Environment. 2018 IEEE/ACS 15th International Conference on Computer Systems and Applications (AICCSA), pp. 1–7. IEEE.

See Google Scholar for full list.

Licenses & Certifications

• IoT Programming and Big Data, 2022 – edX.org – CurtinX
• Analyzing and Visualizing Data with Power BI, 2021 – edX.org – DavidsonX
• CS50’s Introduction to Artificial Intelligence with Python, 2021 – edX.org – HarvardX
• Introduction to Data Science with Python, 2021 – edX.org – HarvardX
• Introduction to Computer Science and Programming Using Python, 2020 – edX.org
• A+ of Computer Maintenance, 2019 – TAG-KS
• ACTSAU Conference Participant, 2018 – ACTSAU
• Lab Partner – Paper Research, 2018 – IEEE/ACS
• Training of Trainers, 2018 – TAG-KS
• International Collegiate Programming Contest, 2018 – ACM
• Fundamental Android: Basics, 2017 – AHU
• Networking to Programming: Synergy for Career Excellence – IoT, 2016 – Cisco Networking Academy