Application Support · Technology · Development

Mohmmad Alqallaf

Application Support Officer focused on banking technology, production support and reliable systems, with a broader background in software development, automation and research.

Application SupportLinuxOracle SQLPythonSoftware DevelopmentFirebaseMachine LearningResearchCloud Application SupportLinuxOracle SQLPythonSoftware DevelopmentFirebaseMachine LearningResearchCloud
01 / About

A little about me.

I am an Application Support Officer at Kuwait International Bank (KIB), working in IT application support with a focus on banking systems, cards, production support and incident investigation.

My work involves supporting business-critical applications, investigating technical issues, automation, monitoring, working with Linux and Oracle SQL, and coordinating with internal teams and vendors. Beyond operations, I have experience in software development and academic research.

Application SupportBanking SystemsLinuxOracle SQLDevelopmentResearch
02 / Experience

Professional experience.

Current role

Application Support Officer

Kuwait International Bank (KIB)

Aug 2025 — Present

Provide application support for core banking and card management systems, helping maintain operational stability and reliable service availability.

Monitor ATM, POS and online-channel transactions, investigate technical issues, analyze system behavior and support timely incident resolution.

Coordinate with internal teams, business users and external vendors to troubleshoot production issues, support system changes and maintain system performance.

Production SupportCardsATM / POSLinuxOracle SQLIncident Investigation
03 / Education

Education.

American University of the Middle East (AUM)

BSc, Information Systems Technology

Sep 2023 — Jun 2025
GPA 3.79 / 4.00Award Best Capstone Project
American College of the Middle East (ACM)

Diploma, Information Technology

Jan 2021 — Jan 2023
GPA 3.98 / 4.00
06 / AI Lab

AI experiments & builds.

A hands-on lab for computer vision, deep learning and language-model work. Each entry opens into a dedicated page with the implementation, technical approach, repository results and an interactive visual explanation.

U-Net colorization result
01 U-Net · PyTorch

Image Colorization with U-Net

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A PyTorch U-Net that predicts chrominance channels in Lab color space to generate plausible color from grayscale landscape images.

PyTorchU-NetLab Color
Pothole detection result
02 YOLOv8 · Detection

Pothole Detection

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An end-to-end YOLOv8 object-detection pipeline covering dataset preparation, annotation conversion, training and inference.

YOLOv8UltralyticsOpenCV
Car plate detection result
03 YOLOv11 · Detection

Car Plate Detection

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Vehicle license-plate detection using YOLOv11, including annotation conversion, training, evaluation and prediction visualization.

YOLOv11Object DetectionPython
SpaceBot terminal output
04 Phi-2 · LoRA · LLM

SpaceBot — Educational LLM

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A compact educational chatbot fine-tuned on space-related questions using Microsoft Phi-2, LoRA and 4-bit quantization.

Phi-2LoRALLMSciQ