Greetings! I hold a PhD in the field of Scientific Machine Learning, with a research background rooted in engineering cybernetics. My academic training spans mathematics, control theory, systems theory, and deep learning, shaping my interest in the principled understanding and modeling of complex dynamical systems.

In my research, I’m driven to efficiently approximate complex models by integrating established numerical methods with modern artificial intelligence techniques. I am particularly interested in approaches that combine physical insight with data-driven learning to achieve accurate, interpretable, and computationally efficient models.