UROP Project

Unmanned Aerial Vehicles (UAVs): Machine Learning Approaches for Drone Cybersecurity

Artificial Intelligence, machine learning, cybersecurity, unmanned aerial vehicles
Research Mentor: Salma Aboelmagd, She/her
Department, College, Affiliation: Electrical and Computer Engineering Department, FAMU-FSU College of Engineering
Contact Email: saboelmagd@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Looking for Research Assistants: Yes
Number of Research Assistants: 2
Relevant Majors: Electrical Engineering
Computer Engineering
Computer Science
Project Location: On FSU Main Campus
Research Assistant Transportation Required: FSU transportation options (e.g., Seminole Express)
Remote or In-person: Partially Remote
Approximate Weekly Hours: 5, During business hours
Roundtable Times and Zoom Link:
Not participating in the roundtable

Project Description

Machine learning is revolutionizing the deployment and operation of unmanned aerial vehicles (UAVs), enabling them to be used in critical domains such as logistics, surveillance, disaster management, agriculture, and defense. This project focuses on leveraging machine learning and AI-driven solutions to improve UAV autonomy and strengthen cybersecurity. By integrating advanced data analytics and AI models, the project will address challenges such as real-time decision-making, path optimization, fault detection, and resilience against cyber-attacks. Students will explore how machine learning algorithms can enhance UAV systems to be more efficient and more robust, ultimately enabling UAVs to operate effectively in complex, real-world environments.

Research Tasks: Data collection
Data analysis
Building machine learning models
Literature review
Documenting and reporting research outcomes

Skills that research assistant(s) may need: Basic programming skills in Python/Matlab
Basic data Analysis skills
Basic experience in MS Excel
Basic research skills

Mentoring Philosophy

My goal is to prepare engineering and computer science students for the rapidly evolving future of machine learning. UAV security represents one of the most dynamic applications of ML, where efficiency, safety, and security are critical. As a mentor, I aim to provide students with hands-on research experiences that bridge theory with practice through real-world inspired simulations and data-driven projects. By fostering a collaborative, inclusive, and innovative environment, I encourage students to think critically, work in teams, and develop both technical and research communication skills. I am committed to recognizing their contributions by including students as co-authors on publications, presentations, and reports to help build their academic and professional profiles. Ultimately, my philosophy is to empower students to become future leaders and innovators in AI, machine learning, and UAV technologies.

Additional Information


Link to Publications


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