Daniel J. Williams

I’m Daniel, a PhD Candidate at Princeton University studying how machine learning can be used to design clean energy systems. Working with Dr. Ryan Adams and Dr. Egemen Kolemen, I conduct research between the Laboratory for Intelligent Probabilistic Systems (LIPS) and the Plasma Control Laboratory. I completed my BS in Computer Science at the University of Maryland, Baltimore County (UMBC) as a Meyerhoff Scholar.

My research focuses on inverse design methods, with an emphasis on building differentiable, GPU-accelerated software for computational geometry, machine learning, and design.

When I am not doing research, I am deeply passionate about promoting science literacy and diversity in STEM. In the future, I aim to work at the intersection of research and policy.

Welcome to my personal website. Here, you can find details about who I am and what I do. I have gained experience in a variety of different scientific fields, coding languages, and technologies, while also trying to do some good in the world along the way.

🔭 Please feel free to reach out with opportunities you believe I’d be a good fit for!