About Me

I am a Postdoctoral Researcher at University of Hamburg, working in Johannes Lederer’s Research Group. My current research focuses on the mathematical foundations of artificial neural networks, where I aim to deepen our understanding of the underlying principles driving modern machine learning models. Specifically, I am interested in bridging the gap between mathematical theory and the rapid empirical advancements in the field. By developing a rigorous mathematical framework, I believe we can not only justify the widespread application of these models but also identify ways to improve and enhance their performance.

I earned my PhD in Mathematics from University of Wisconsin-Milwaukee, where I was mentored by Gerhard Dikta and Richard Stockbridge. During my doctoral research, I developed a strong foundation in empirical process theory, which I continue to apply in my current research on neural networks.

In my postdoctoral position, I aim to broaden my research expertise and explore potential areas for future collaboration. I am particularly interested in working with researchers exploring theoretical guarantees for neural networks and those in related fields such as mathematical statistics, optimization, and machine learning.

I am always eager to connect with fellow researchers, so feel free to reach out if you’re interested in potential collaborations or discussions on deep learning theory and related topics.