People

I have an interdisciplinary background spanning mathematics (with a focus on optimization), cognitive science, and psychology. My research interests lie at the intersection of perception, computation, and statistics. I’m particularly fascinated by the statistical structure of natural images, including models such as Dead Leaves, and how these relate to low-level visual features and perceptual mechanisms.

I enjoy working across disciplines to build models and simulations that help us understand how sensory information is processed and represented. This involves both theoretical and applied approaches, including data analysis, computational modeling, and the development of (synthetic) image statistics. My work aims to bridge gaps between vision science, machine learning, and cognitive theory.