HASSAN ALMAHDAWI

During internship at NAQUA, I had the opportunity to rotate across several key departments including power, automation feeding, production plants, shrimp farms, and workshops. This hands-on experience gave me a well-rounded understanding of how large scale aquaculture operations work from the ground up.
I also led several exciting AI focused projects:
1. Built an optical sorting system using machine learning to classify shrimp based on size and quality grade.
2. Developed a model to detect and remove unwanted objects like weeds, small fish, and crabs from the shrimp batches, while also identifying signs of illness for better quality control.
3. Created a fast and efficient larvae counting tool using object recognition to speed up early stage shrimp monitoring.

Led a final-year research project focused on estimating soil moisture using drones equipped with L-band microwave radiometers and ground robots. Developed a simulation pipeline for electromagnetic modeling using HFSS to extract S-parameters, and applied the RTMS model to calculate brightness temperature and derive soil moisture levels. Implemented field data collection and analysis workflows to validate model accuracy.

Building from a scratch, an autonomous robot for tennis ball collection and delivering using Raspberry Pi 4, integrating computer vision with a YOLO model for real-time object detection. Implemented encoder-based odometry and ultrasonic and distance sensors for accurate navigation and obstacle avoidance. Designed a servo-actuated mechanism for ball pickup and deliver to

Served as a Crowd Manager with Al-Yamama Trains, following intensive training in crowd control, safety, and teamwork. Managed large crowds with clear communication and full-time commitment, demonstrating enthusiasm and adaptability in a high pressure environment.