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Derin Gezgin |
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I am a third-year undergraduate student at Connecticut College, double majoring in Computer Science and Statistics and Data Science. While pursuing my degrees, I collaborate with professors at Connecticut College, University of Vermont, Cornell University, and University of Pennsylvania on research projects in areas such as artificial intelligence for games, computer vision, software engineering. and continual learning. At the same time, I work as a teaching assistant and grader for multiple Computer Science and Statistics courses. I am currently the Head Teaching Assistant of the Department of Computer Science at Connecticut College. I was also a member of the Connecticut College Computer Science Student Advisory Board as the Diversity Chair. My Erdős number is 4. |
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ResearchI'm a member of two research labs at Connecticut College: the Autonomous Agent Learning Lab, where I work with Prof. Gary B. Parker and Jim O'Connor, and the Informatics Lab, where I work with Prof. Timothy James Becker. My research in the Autonomous Agent Learning Lab focuses on artificial intelligence for games and evolutionary robotics, while in the Informatics Lab I work on real-world applications of computer vision and machine learning. I am currently working with Prof. Nick Cheney at the University of Vermont as part of the Neurobotics Lab through a Summer 2026 research internship, exploring continual learning and open-ended evolution. From May 2025 to March 2026, I collaborated with Prof. Mayur Naik at the University of Pennsylvania and Prof. Saikat Dutta at Cornell University. During this collaboration, I contributed to IRIS, a neuro-symbolic framework that combines large language models with static analysis to detect security vulnerabilities across entire software repositories. I led the Docker integration for IRIS, containerizing the project workflow, publishing prebuilt images to Docker Hub for 189 Java projects, making them easier to build and run reproducibly. I also developed PoC-Gym, a system for LLM-assisted Java proof-of-concept exploit generation that combines CVE-tailored prompts, static source–sink traces, coverage-based feedback, and runtime validation. |
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Teaching ExperienceI am fortunate to serve as a teaching assistant and grader for the courses below, working with classes of 20–40 students. During the 2026–2027 academic year, I serve as the Head Teaching Assistant for the Department of Computer Science, coordinating a team of 25 teaching assistants. Previously, during the 2025–2026 academic year, I served as the COM110 TA Manager, coordinating the COM110 teaching assistants, session scheduling, and grading. So far, as an undergraduate student, I have accumulated over 550 hours of TA service. F: Fall Semester & S: Spring Semester & U: Summer Session COM110: Introduction to Computer Science and Problem Solving Connecticut College • S24, F24, S25, U25, F25, S26 COM212: Data Structures Connecticut College • F24, S25, F25, S26, F26 COM219: Computer Organization Connecticut College • F25 COM304: Algorithms Connecticut College • F26 COM316: Artificial Intelligence Connecticut College • F26 COM322: Computer Vision Connecticut College • S26 STA107: Introduction to Statistics Connecticut College • S26 STA207: Advanced Regression Techniques Connecticut College • F25, F26 |