I'm passionate about making lives more exciting and efficient using technology, e.g., artificial intelligence. I strongly believe that man and machine working together will make a better decision than a man or a machine independently.
My current and previous work showcases a broad spectrum of my AI knowledge and experience. From hardware to software, computer vision to natural language processing, and theory to practical solutions.
Most of my projects involve practical implementations of state-of-the-art AI technology. I enjoy theoretical stuffs; however, I'm mostly interested in AI technology that is feasible, responsible, explainable, non-incremental and has real-world values to whomever using the technology. More specifically, I'm interested in new AI techniques that will solve real-world problems when developing AI solutions in real situations. These include:
Currently responsible for developing AI solutions that work in real lives and have significant impact on innovation activities and operational efficiency at GM. Main contributor to a deployed AI solution with an impact up to $8M/year in GM operational savings.
Responsible for implementing state-of-the-art deep learning algorithms for two projects: speech multi-keywords spotting and time-series anomaly detection.
Graduate Research Assistant.
Developed a vision-based cognitive advanced driver assistance system using Deep Learning. Our work
at national and international news sites: CBC News, The Washington Post, Vice News, and other news
Teaching Assistant. Responsible for assisting instructors in the labs and classrooms for several courses in the area of machine learning, artificial intelligence, and control systems.
Developed control and instrumentation systems for two major projects at KFUPM: unmanned ground vehicle (UGV) and solar-powered reverse-osmosis water desalination system.
Trained as an automation engineer for gold and copper extraction automation.
Assigned to assist the project management team.
Thesis: Large-Scale Traffic Flow Prediction Using Deep Learning in the Context of Smart Mobility. Supervisor: Fakhri Karray.
Thesis: Invariance and Immersion (I&I) Control Design for Unmanned Aerial Vehicles. Supervisor: Sami Elferik.
Thesis: Development of a 3D-Image Electric Tomography Data Acquisition System for Cylindrical Object Image Reconstructions. Supervisor: Deddy Kurniadi.
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