Research Interests Theory of Self-Assembly based on stochastic analysis Self-Assembly Applications DNA Computing, DNA Self-Assembly and its applications Self-Assembly processes are fundamental processes central to much of nanotechnology. My research focuses on the stochastic analysis of self-assembly processes, and the applications of self-assembly (especially computing applications). Most of the self-assembly structures studied are related to DNA and biomolecular structures. Developed a discrete model of self-assembly which corresponds to the chemical kinetic theory. This allows self-assembly processes to be simulated in silico. (current research - not yet published.) Developed a model that estimates the final yields of self-assembly processes. The result shows that there is a phase transition in self-assembly: there is a set of parameter that allows the self-assembly to produce no waste in the final state. Developed a model that computes the time to complete two-dimensional tile self-assembly based on Erik Winfree's model. The intermediate shape (during the growth process) of tile self-assembly can be determined based on this model. Introduced an error-correction method for DNA tile self-assembly and analyzed its performance. Introduced a method of determining the final yields of single enzyme networks. (To see the list of related papers, please click here.)