About Me

I am a PhD Candidate at Eötvös Loránd University (ELTE), Faculty of Informatics, in Budapest, Hungary. My research is focused on the development of secure and privacy-preserving machine learning systems.

Research Interests

My work primarily revolves around:

• Synthetic Data Generation: Creating high-fidelity data that mimics real-world datasets.
• Privacy Preservation: Implementing techniques like Differential Privacy to protect sensitive information.
• Generative Models: Leveraging GANs and other generative architectures for robust data modeling.
• Machine Learning Security: Ensuring the integrity and confidentiality of ML pipelines.

Teaching & Mentoring

• Course Labs Developer: Designing and teaching practical lab sessions for the IDaSec Practicum (Introduction to Data Security) at ELTE.
• Student Supervision: Mentoring and supervising B.Sc. and M.Sc. students in secure machine learning implementations, differential privacy, and thesis research.

Professional Goal

My goal is to bridge the gap between advanced machine learning capabilities and the fundamental right to data privacy, enabling data-driven innovation that is both ethical and secure.

You can find more details about my work in the Biography and Publications sections.