PoC-Gym: Towards More Reliable LLM-Assisted Proof-of-Concept Exploit Generation
Second Workshop on Large Language Models For Generative Software Engineering, 2026
Derin Gezgin
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.
Outside of research, 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.
Research
I am 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.
From May 2025 to March 2026, I collaborated with Prof. Mayur Naik at the University of Pennsylvania and Prof. Saikat Dutta at Cornell University. 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.
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.
Publications
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Evolutionary Optimization of Deep Learning Agents for Sparrow Mahjong
AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 2025
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Playing Atari Space Invaders with Sparse Cosine Optimized Policy Evolution
AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 2025
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A framework for river connectivity classification using temporal image processing and attention based neural networks
ACM Conference on Computing and Sustainable Societies, 2025
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SCOPE for Hexapod Gait Generation
IJCCI Conference on Evolutionary Computation and Theory and Applications, 2025
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Evolving Neural Controllers for Xpilot-AI Racing Using Neuroevolution of Augmenting Topologies
IJCCI Conference on Evolutionary Computation and Theory and Applications, 2025
Teaching Experience
I am fortunate to serve as a teaching assistant and grader at Connecticut College 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 600 hours of TA service, supporting more than 200 unique students.
F: Fall Semester & S: Spring Semester & U: Summer Session
- COM110: Introduction to Computer Science and Problem Solving S24, F24, S25, U25, F25, S26
- COM212: Data Structures F24, S25, F25, S26, F26
- COM219: Computer Organization F25
- COM304: Algorithms F26
- COM316: Artificial Intelligence F26
- COM322: Computer Vision S26
- STA107: Introduction to Statistics S26
- STA207: Advanced Regression Techniques F25, F26