• Design assisted and semi-automated image annotation using Napari and VGG Image Annotator (VIA)
• Design database handling data collection, data preparation, visualization, and sharing on Firebase Google Cloud.
• Design a data collection node to screen road conditions using different sensors (3D Camera, IMU, LiDAR, GPS). [project demos]
• Design and integrate Drone-based data collection using DJI Mavic 3 / DJI Tello. [demo video]
• Design a hybrid deep learning-based system for automated X-ray CT inspection for industrial applications. [project demo]
• Design a smart dental diagnosis and treatment support using semantic networks using CT images. [project demo]
• Design and implement hybrid classification/object detection ML models for inspection of Highways in winter conditions
• Implement an incremental method based on a dynamic model confidence score thresholding for better data selection and training.
• Lead and collaborate with a team of 6 students, 4 trainees and a lab engineer

• prototype a Jetson Nano based system to collect sensor data and control feeding for Tilapia fish aquarium.
• Manual data cleaning, preparation and annotation of the collected underwater camera images using LabelMe
• Design online visualization and monitoring, using Grafana, of the feeding process, fish growth, and fish health
• Design an object detection model to assess the fish health diagnosis. Implement a real-time optimal feeding strategy
• Manage the AWS assets used for model deployment and the hosting of the website
• Participate in the market assessment and potential collaborator/client discussions
• Follow up and coordinate with the external outsourcing (website and logo)

• Design/build an automated monitoring and control system of a cooling system in greenhouses
• Design a datalogger system to collect humidity temperature, water level, etc
• Design online monitoring and control of an evaporative cooler using a FastAPI webserver
• Implement a time-lapse recording of a tomato life cycle in the KAUST greenhouse.
• Write the project documentation and participate in the writing of a fund proposal application

• Design and implement an electrical arc fault detection algorithm based on an active filter
• implement an FFT-based detection algorithm using spectral and statistical indicators (features)
• Develop a Matlab user interface tool to integrate the developed detection algorithm
• Validate the algorithm simulated Hardware-In-the-Loop (HIL) using Matlab and VHDL-AMS modeled power loads.
• Participate in writing my first IEEE journal paper as a co-author. PDF

Phase 1: Requirement management for the automotive industry:

• Participate in creating the requirement management system for the company
• Write the clients/stockholders’ needs and translate them into concise and traceable technical specifications
• Define the different tests to be conducted to satisfy the needs

Phase 2: Apply the requirement management for the crank sensor simulator in a case study:

• Define the technical specification and test of the target crank sensor simulator
• Design a crank signal generator using an analog differential amplifier
• Fabricate the first prototype of the crank signal generator
• Test/validate and write a final specification document of the designed system