📚 Research
My research focuses on the intersection of artificial intelligence and software security, particularly in automated vulnerability discovery and fuzzing technologies.
� Current Research
Ongoing Research Paper
Status: Under Review
Focus Area: AI-driven security testing and transformer-based fuzzing frameworks
My current research explores novel applications of generative models in security testing, investigating how transformer architectures can be leveraged to improve automated vulnerability discovery and enhance fuzzing effectiveness.
Details will be published after the peer-review process is completed.
🎓 Academic Background
Bachelor's Thesis
Institution: TU Berlin
Completion: October 2024
Focus: Generative models in security testing and transformer-based fuzzing frameworks
My undergraduate thesis investigated the application of modern machine learning techniques to automated security testing, with particular emphasis on how generative models can enhance traditional fuzzing approaches. The work explored the potential of transformer architectures in understanding and generating security-relevant test cases.
🔬 Research Interests
AI-Driven Security
Leveraging machine learning and AI techniques to automate vulnerability discovery and enhance security testing methodologies.
Advanced Fuzzing
Developing intelligent fuzzing frameworks that combine traditional techniques with modern ML approaches for improved coverage and enhanced vulnerability detection capabilities.
Container Security
Exploring security boundaries in containerized environments and developing novel detection mechanisms for container threats.
📊 Research Philosophy
My research approach emphasizes the practical application of theoretical advances in real-world security contexts. I believe in bridging the gap between academic research and industry needs by focusing on:
- Reproducible Research: Ensuring all experiments and frameworks can be easily replicated
- Open Source Contributions: Making research tools and datasets available to the community
- Interdisciplinary Collaboration: Combining insights from AI, systems security, and software engineering
- Practical Impact: Focusing on research that can be translated into real security improvements