Ibraheem Alhashim
Senior Principal AI Researcher at HUMAIN
Dammam, Eastern Province, Saudi Arabia
Summary
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Rockstar🎓
Top SchoolIbraheem Alhashim is a Senior Principal AI Researcher based in Dammam with 14 years of experience translating advanced AI research into real-world products and smart-city solutions. He has led teams and initiatives across government, startups and national AI centers—building MVPs from large vision-language models and GPT-based chatbots to computer-vision systems for visual pollution detection and monocular depth estimation. As a former CTO and co-founder, he combines product-minded engineering with deep academic roots (PhD, SFU) and a postdoc background in depth and 3D reconstruction, which informs his practical work on projects like DenseDepth. Known for bridging research and deployment, he has steered national-scale AI efforts at SDAIA and advised public-sector Applied Research teams, while also shipping consumer-facing platforms such as Mawidy. Colleagues value his ability to move from novel model ideas to validated production tests and metrics—a skill reflected in his hands-on contributions to model evaluation and loss implementations.
13 years of coding experience
12 years of employment as a software developer
Deep Learning Nanodegree, Computer Science, Deep Learning Nanodegree, Computer Science at UdacityBachelor of Science (BSc), Computer Science, Bachelor of Science (BSc), Computer Science at Portland State UniversityDoctor of Philosophy (PhD), Computer Science, Doctor of Philosophy (PhD), Computer Science at Simon Fraser University
Arabic, English
Github Skills (9)
computer-vision10
transfer-learning10
deeplearning-ai10
deep-learning10
tensorflow10
deep-neural-networks10
python10
image-processing9
pytorch3
Programming languages (11)
Github contributions (5)
ialhashim/DenseDepth
Dec 2018 - Nov 2022
High Quality Monocular Depth Estimation via Transfer Learning
Role in this project:
ML Engineer
ML EngineerContributions:2 reviews, 74 commits, 16 PRs in 3 years 11 months
Contributions summary:Ibraheem added testing code and incorporated it into the existing codebase, specifically testing on the NYU Depth V2 dataset. They also modified the `layers.py`, `utils.py`, `test.py` and `loss.py` files to implement the necessary test setup and related functionalities, including the depth loss function, image loading, and result display. These modifications suggest a focus on model evaluation and validation within this monocular depth estimation project.
pytorchpythonmonocular-depth-estimationdeep-learningtransfer-learning
ialhashim/EmojiNetTutorial
Apr 2018 - Feb 2022
An AI tutorial on the problem of object detection and segmentation using Keras
Contributions:21 commits, 1 PR, 10 pushes in 3 years 10 months
deep-learningunet-image-segmentationobject-detectioncomputer-visionmachine-learning
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