About me

I am motivated by a desire to use scientific understanding to help address real problems that matter to society.

My background is in theoretical physics, with additional training in cognitive science. For many years, my work focused on how information is processed in physical systems—whether biological or artificial. This perspective has shaped how I approach problems: I am interested in limits and trade-offs, uncertainty, and how systems learn, adapt, and make decisions under real-world constraints.

Today, I apply this way of thinking beyond theory. I work at the intersection of data, modeling, and decision-making, with a growing focus on public health, renewable energy systems, and climate-related challenges. These areas share a common feature: they involve complex, interconnected systems, incomplete data, and significant uncertainty.

More broadly, I am interested in bridging cutting-edge research and practical impact. I enjoy working across disciplines and translating abstract ideas into tools and insights that can inform policy, improve large-scale infrastructure, and support evidence-based decisions. My goal is to contribute to work that is both intellectually rigorous and directly relevant to societal challenges.