Today's Edition
MUDHI ALOBTHANI (ABU DHABI)
In the UAE, innovation is no longer a distant ambition, it is being actively shaped by students who are transforming ideas into real-world solutions. At Abu Dhabi University, two computer engineering students are redefining how artificial intelligence can serve both education and sustainability, reflecting the country’s broader vision for a knowledge-based, future-ready society.
AI-powered Evaluation System
Wadha Hassan Salim Ahmed Almansoori, a Computer Engineering student with a concentration in Artificial Intelligence, is tackling one of the most familiar yet complex challenges in academic life: fairness in oral examinations. Her capstone project introduces an AI-powered system that evaluates not only what students say, but how they say it —analysing voice, facial expressions, and language to assess confidence, engagement, and depth of understanding.
Inspired by her own experience as a student, Almansoori recognised the subjectivity that often shapes oral assessments. “Sometimes it is not just about what you know, but how the examiner perceives you in that moment,” she explained. Her solution aims to bring consistency and transparency into the evaluation process, particularly in collaborative academic environments where accurately measuring individual contribution can be difficult.
By combining speech recognition, facial analysis, and natural language processing, her system represents a step towards more balanced and meaningful assessments. While still under development, the project highlights the potential of AI to support educators, reduce bias, and ultimately enhance the student experience.
Waste-Sorting Robot
In a different yet equally impactful field, fellow student Hamad Abdulla Rashed Mohammed Alnuaimi is applying artificial intelligence and robotics to address environmental challenges. His innovation — an AI-powered autonomous waste-sorting robot — aims to improve recycling efficiency by removing the need for manual sorting.
Designed for indoor environments such as universities, offices, and public spaces, the robot uses computer vision and machine learning to identify and classify waste materials in real time. It can navigate spaces independently, sort items into designated compartments, and even return to a docking station for automatic recharging.
Alnuaimi’s idea was sparked by a simple observation: despite the availability of recycling bins, improper waste sorting remains common. By automating the process, his system reduces human error and promotes more effective recycling practices. “When waste is not properly separated, recyclable materials are often contaminated and cannot be processed correctly,” he noted, emphasising the environmental impact of inefficient systems.
Developing such a complex solution required integrating multiple technologies-from LiDAR-based navigation to real-time machine learning models-into a single, functional prototype. Despite technical challenges, Alnuaimi adopted a modular approach, building and refining each component step by step.
