I am a Master’s student in Artificial Intelligence at the University of Amsterdam, where I focus on advanced AI concepts and research methodologies. I hold dual Bachelor's degrees in Computer Science and Economics. Additionally, I am pursuing a Bachelor's in Mathematics at Fernuniversität Hagen to deepen my mathematical expertise for AI research.

My primary research interests lie in Deep Learning, particularly in Natural Language Processing, Computer Vision, and Reinforcement Learning. In my Bachelor's theses, I explored innovative ways to improve Transformer efficiency for financial text analysis and developed strategies for optimizing data center locations using Graph Neural Networks and RL.

I actively implement and analyze state-of-the-art research papers to deepen my understanding and share insights through my blogs.

My research focuses on leveraging self-supervised learning to enable agents to plan and act effectively in dynamic and stochastic environments. Specifically, I am investigating how SSL can enhance Graph Neural Networks and Reinforcement Learning to tackle operations research problems involving complex combinatorial decision-making.

I have implemented various research papers exploring these domains and contributed to building a research community through collaborations and knowledge sharing. By developing agents that can learn graph-structured representations, my goal is to improve their ability to simulate scenarios, optimize planning strategies, and make informed decisions with limited data.

My work on world models and self-supervised techniques aims to make RL more sample-efficient and adaptable to real-world constraints.

I work as a Machine Learning Engineer and Full-Stack Developer at KPMG, where I design and implement AI solutions for real-world challenges. My projects include developing innovative computer vision models for object detection and integrating language models into applications to enhance accessibility and usability for clients.

Additionally, as a Research Assistant at the University of Passau, I focus on developing self-supervised methods for pretraining large language models tailored to financial applications. My role involves building modular libraries for document encoders, collaborating on research papers, and exploring advanced representation learning techniques .