Aya Ali

Designed and deployed an AI-driven phishing detection web app using TF-IDF, encoder-based text representations, ensemble classifiers and transformer models, achieving ~96% classification accuracy and real-time API deployment.

Guided students in building end-to-end ML and deep learning models, led workshops using Python, TensorFlow, and scikit-learn, and developed datasets and reproducible evaluation pipelines for student projects and competitions.

Selected for a competitive AI–Cybersecurity scholarship; designed, developed, and evaluated machine learning models for phishing detection and malware analysis, building security-aware AI pipelines to enhance cyber defense.

Developed CNN and classical ML models including DBSCAN and online regression techniques, improving prediction accuracy and gaining practical experience with TensorFlow and scikit-learn during a summer internship.

Developed a real-time mobile application to display competition results across categories, enabling instant score updates and improving communication and transparency for participants and organizers.

Designed and implemented an autonomous delivery robot using RRT-based path planning and YOLOv11 for real-time object detection, achieving ~90% obstacle-avoidance accuracy in simulations and an Android control interface.

Grade: 3.11 GPA

Activities and societies: Graduation project: Autonomous Delivery Robot; RoboRAVE app developer; Student Mentor Union chair; coursework in AI, autonomous systems, and cybersecurity.

Pursuing a B.Sc. in Electrical Engineering with coursework and projects in AI model design, autonomous vehicle systems, and cybersecurity; graduation project developed an autonomous delivery robot with RRT path planning and YOLO-based object detection.