About me

Hi there 👋

I’m Christoph Landolt, a doctoral researcher at the CISPA Helmholtz Center for Information Security in Saarbrücken, Germany, supervised by Mario Fritz. As an ELLIS PhD student, my research focuses on agentic and self-improving systems for cyber security, particularly exploring the intersection of generative AI, multi-agent learning, and game theory to build safer and more resilient autonomous agents in adversarial environments.

Before starting my PhD, I worked as a master’s thesis research fellow at the Cyber-Defence Campus in Switzerland, where I worked on training offensive penetration testing agents using multi-agent reinforcement learning (MARL). I also held a position as a research assistant in machine learning at the Institute for Computational Engineering (ICE) in Buchs, Switzerland, and gained several years of industry experience.

Research Interests

• Adversarial AI & AI Safety: Developing robust AI systems that can withstand and adapt in adversarial settings, with a focus on cyber security.
• Multi-Agent & Equilibrium Learning: Investigating cooperative and competitive interactions among autonomous agents using Agentic, MARL and game-theoretic frameworks.
• Generative AI for Security: Leveraging generative models to explore both attack and defense in cyber environments.
• Reinforcement Learning: Applying deep RL techniques to enable autonomous decision-making in complex, uncertain scenarios.
• Secure & Trustworthy Foundation Models: Studying how to align and secure foundation models for deployment in critical infrastructure.

News

• August 2025: Attending ELLIS Doctoral Symposium on Robust AI
• August 2025: Attending CISPA - ELLIS - Summer School 2025 on Trustworthy AI - Secure and Safe Foundation Models
• June 2025: Our paper Securing RAG: A Risk Assessment and Mitigation Framework was presented at the IEEE Swiss Conference on Data Science 2025
• June 2025: Gave a presentation on Multi-Agent Reinforcement Learning at Cyber Alp Retreat Davos 2025
• June 2025: Poster presentation of our work Multi-Agent Reinforcement Learning in Cybersecurity: From Fundamentals to Applications at ELSA General Assembly 2025
• May 2025: Started as an ELLIS PhD student

Education & Background

• PhD in Computer Science, CISPA Helmholtz Center / ELLIS PhD Program, 2024 – present
• MSc in Engineering (Data Science), OST - Eastern Switzerland University of Applied Sciences
  Thesis: Training of Offensive Penetration Testing Agents with Multi-Agent RL on Graphs (CYD Fellowship)
• BSc in Systems Engineering (Computer Science), OST - Eastern Switzerland University of Applied Sciences
  Thesis: Anomaly Detection in Web Traffic using ML for Attack Recognition

Publications

You can find a list of my publications under Publications or on Google Scholar.

How to Connect

For collaboration opportunities, questions, or discussions related to my research, feel free to reach out through my email or connect with me on LinkedIn.