Research Interests

I use molecular dynamics simulations to understand how molecules move and interact, and to turn that understanding into predictive tools. My work spans method development and application, from the dynamics of liquid water to high-throughput free energy calculations for drug discovery.

Free energy methods for drug discovery

My current work is primarily aimed at developing novel techniques for calculating absolute and relative binding free energies (ABFE and RBFE) of small molecules targeting both protein and nucleic acid systems. Recent directions include:

• Machine learning potentials (MLPs) to correct dihedral parameters for drug-like molecules.
• New free energy workflows built on Amber molecular dynamics for high-throughput screening.

Dynamics of liquids

During my Ph.D. I developed the fluctuation theory for dynamics — a way to calculate the temperature and pressure derivatives of dynamic timescales (such as diffusion and hydrogen-bond exchange) from simulations at a single state point. This work focused on activation energies, hydrogen-bond exchange, and the molecular origins of dynamics in liquid water and aqueous solutions.

Membranes, nanoplastics, and computational spectroscopy

As a postdoc I developed coarse-grained models for how nanoplastic particles interact with and penetrate lipid membranes, along with computational spectroscopy tools for interpreting molecular simulations.