I am a PhD candidate in theoretical computer science at the University of Colorado Boulder, advised by Joshua Grochow and Rafael Frongillo. I am also a Graduate Fellow at the Santa Fe Institute. My research focuses on which problems can be solved efficiently across different models of computation, and which structural properties make certain problems fundamentally hard.
Toward my thesis, I am working on circuit-complexity lower bounds using algebraic, analytic, and combinatorial methods.
In parallel, I practice computational complexity as a constraint-aware, compositional way of thinking about bounded agents. A central lesson of complexity theory is how to design procedures that achieve goals under explicit resource bounds. With collaborators at the Santa Fe Institute, I apply this perspective to human problem-solving, using puzzles as clean testbeds where local rules and global structure are measurable, enabling precise claims about learning and action under constraints.
Prior to my PhD, I received a BSc in Physics (2022) from the University of Leipzig and worked on the thermodynamics of computation beyond bit erasure.