Setareh demonstrated several notable skills throughout the project, including: Advanced Technical Proficiency – She showcased strong coding skills by building a machine learning model in Python to classify network intrusions, demonstrating her deep understanding of AI and cybersecurity applications. Research and Analytical Thinking – She conducted thorough research on optimal AI models for cybersecurity, analyzing their practical applications and effectiveness. Problem-Solving Skills – Her ability to apply machine learning to a real-world challenge highlighted her strong problem-solving mindset and technical ingenuity. Passion and Subject Mastery – Setareh's enthusiasm for AI and cybersecurity was evident in her work, as she approached the project with a high level of curiosity, dedication, and expertise. Presentation and Communication – She effectively articulated complex technical concepts, making her insights accessible and impactful. Her combination of technical expertise, research abilities, and clear communication made her an outstanding contributor to the project.

Setareh engaged with stakeholders professionally and effectively throughout the project. She actively participated in discussions, demonstrating confidence and deep subject knowledge when presenting her research and technical work. She maintained clear and proactive communication, ensuring that her findings and contributions were well understood by the team. Setareh was also receptive to feedback, integrating suggestions to refine her approach and improve her deliverables. Her ability to explain complex machine learning and cybersecurity concepts in an accessible way made her engagement with stakeholders highly valuable.

Setareh effectively managed her time and consistently met project deadlines. From the start, she was highly organized and proactive, ensuring that her work was completed on time and to a high standard. She balanced research, coding, and analysis efficiently, demonstrating strong time management skills. Despite the complexity of her machine learning model and cybersecurity research, she stayed on track with deliverables, providing well-structured updates and communicating any progress or challenges promptly. Her ability to manage multiple tasks without compromising quality made her a reliable and standout contributor to the project.