My research is inspired by many fascinating, yet not well understood, phenomena occuring at atomic, molecular and mesocopic scales. For instance, why can random copolymers efficiently stabilize enzymes in organic solvents? how to control the self-assembly of polymer-tethered nanoparticles and DNA-functionalized colloids into micron-sized flawless crystals? why like-charged polydisperse nanoparticles assemble into uniform-sized clusters? The answers to such questions would lead to exciting opportunities for engineering more efficient materials and devices to improve environment-, healthcare- and energy-related applications. With these ultimate goals in mind, I am focusing my current research on (1) developing physical models for better understanding of molecular systems with long-range, many-body interactions, (2) discovering design rules for assembling bio-inspired materials from bottom up using statistical mechanics, molecular simulation and machine learning, and (3) exploring strategies for accelerated sampling in molecular simulation with new sampling algorithms, and with new implementations optimized for hybrid computer platforms including distributed-memory clusters and graphics processing units (GPUs).
