Welcome!

I am currently a postdoctoral research associate in Prof. Zhen-Gang Wang’s research group at Caltech. I specialize in:

a) Chemical Physics of Surfactants and their Interfacial Phenomena, b) Physics of Polymer Self-assembly and Dynamics, and c) Computational Modeling of Rare Events in Chemical Systems.

I obtained my Ph.D. while working in Prof. Arun Yethiraj’s group at the University of Wisconsin, Madison. My Ph.D. thesis focused on the self-assembly of gemini surfactants and the properties of nano-confined water. Soon after completing my Ph.D, I conducted research under the supervision of Prof. Friederike Schmid at the Institute für Physik, Universität Mainz-Germany. During this time, I gained expertise in field theoretic modeling of polymer systems and applied these methods to investigate polymer self-assembly and dynamics.

Through my graduate and postdoctoral research trainings I acquired expertise in various computational tools and theoretical models. These tools ranged from all-atom and coarse-grained particle-based simulations to study molecular properties of the system, to enhanced sampling approaches such as umbrella sampling, metadynamics, replica exchange molecular simulations, and the transition-state path-finding approach called the string method for modeling rare events in chemistry.

Additionally, I utilized equation of state (EoS) approaches like perturbed chain statistical associating fluid theory (PC-SAFT), as well as field-theory-based methods such as self-consistent field theory (SCFT), classical density functional theory (cDFT), and dynamic density functional theory (DDFT) for the mesoscopic characterizations of system properties.

Recently, in collaboration with Prof. Wang’s group and the scientists at Dow Chemical Company, I have been exploring a synergistic approach to combine physics-based molecular models with the machines learning tools to advance the boundaries of computational materials science research.