I turn machine learning, computer vision, and generative AI into systems people can test, understand, and use.
Observe a problem. Build an AI system. Measure the result.
Four projects across traffic simulation, iOS, document AI, and explainable autonomy. Each case study shows the engineering decisions and what the evidence supports.
Vehicle detection, queue analytics, and adaptive signal policies across synthetic CARLA and SUMO scenarios.
A bilingual grocery companion with family lists, offline sync, and image, voice, and barcode assisted capture.
An RTL grammar analysis and i‘rab experience built on ALLaM through IBM watsonx.
Explore four project architectures: adaptive traffic simulation, Thalaja’s multimodal capture, cloud document retrieval, and explainable autonomous perception.
My strengths combine model development, generative AI, and cloud systems. I train and evaluate models, build retrieval and language workflows, and connect AI to APIs, monitoring, and usable interfaces.
I train, compare, and evaluate models for vision and multimodal tasks, then examine where their predictions succeed or fail.
I build retrieval and language workflows, including document question answering and Arabic analysis, with attention to evidence and evaluation.
I connect models to APIs, cloud services, monitoring, and mobile interfaces, from AWS document workflows to Azure ML and iOS prototypes.
From AI engineering studies and the Apple AI Foundation Program to applied projects and research leadership.
The full résumé ↓Designing the research track’s editorial plan and three step quality process to make current AI research accessible in Arabic.
Built projects in computer vision, deep learning, robotics, and generative AI.
Collaborated on Thalaja, combining on device product experience with AI assisted grocery capture.
Marsad and Wadeh show how I turn focused challenges into testable AI prototypes.
Led a hackathon concept spanning crowd safety, player analytics, and an Arabic fan assistant. Validated three demo videos and five core scenarios.
Explore Marsad ↗Selected from 200+ ideas. Built an Arabic right to left grammar experience and iteratively improved it through example based evaluation.
Read case study ↗Contributed management side solutions to a simulated cyber resilience case. Our ten person team combined technical and management recommendations for a panel of KPMG consultants.
Case competition · not a client engagementI’m curious about the whole path from model behavior to the decision a person makes with it.
I also lead a research team working to make AI research more accessible in Arabic.
Bahçeşehir University · 2026
Saudi Council of Engineers · AI Specialist
Abdullah Al-Shobaki · Riyadh
“I had the privilege of mentoring Abdullah during a 5-week AI Foundation Program at the Apple Developer Academy. Throughout the program, he demonstrated strong ambition, commitment, and an impressive ability to grasp new concepts quickly. His dedication to learning was evident, and he consistently approached challenges with curiosity and determination. In addition to his technical growth, Abdullah stood out for his collaborative spirit and willingness to work effectively with his peers. I am confident he will continue to excel in his journey and be an incredible asset to any team. I highly recommend him.”
Shahad Alharbi · Software Engineer & Tech Mentor, Apple Developer Academy
I’m open to AI engineering opportunities in Saudi Arabia and beyond.
