My research lies at the intersection of programmable self-assembly, discrete mathematics and algorithmic information theory. I study how complex structures emerge from simple local interaction rules, with particular interest in symmetry, designability, and the informational complexity of assembly processes.
Programmable Self-Assembly
I am working on programmable self-assembly, with a focus on three-dimensional polycube model. My research explores how complex three-dimensional structures can emerge from simple local interaction rules, and how properties such as symmetry, assembly complexity, and designability shape the space of achievable structures. Using large-scale simulations and theoretical analysis, I study genotype–phenotype maps in self-assembling systems and investigate the fundamental principles that govern minimal assembly design.
Graph Theory and Combinatorics
I am also interested in combinatorial and graph-theoretic problems related to counting and characterizing the different ways discrete structures can be assembled or grown. This includes work on successive vertex orderings of connected graphs, where we derived exact formulas for counting the number of ways a graph can be constructed sequentially while remaining connected at every step.
Earlier Research
My earlier work explored problems in condensed matter and statistical physics, including quantum spin liquids, graphene fractals, Anderson localization, and disordered systems.