Research Group

Principal Investigator

Dr. Teresa Head-Gordon
Chancellor's Professor

Pitzer Theory Center
Department of Chemistry, Bioengineering, and Chemical and Biomolecular Engineering
University of California, Berkeley

Senior Faculty Scientist
Chemical Sciences Division
Lawrence Berkeley National Laboratory

Contact information:
274 Stanley Hall
Email: thg [at] berkeley [dot] edu

Administrative Assistant

Brian Huang

Office: 214 Gilman Hall
Phone: 510-642-9617

Post-doctoral Scholars

Dr. Maria Tsanai

My research is focused on investigating protein conformations as well as interactions of folded and intrinsically disordered proteins with other proteins, small molecules, nucleic acids and lipid membranes. To this end, I use molecular dynamics simulations, quantum mechanics, free energy calculations and per-residue electrostatic potential calculations.

Dr. Allen LaCour

I am interested in understanding liquid interfaces and their potential for altering chemical reactivity. To this end, I develop models for the experimentally obtained spectra of these interfaces. I am also interested in understanding adsorption thermodynamics at interfaces to better design chemical systems for specific reactions.

Dr. Joseph Heindel

I am interested in physically realistic descriptions of aqueous interfaces with a particular focus on observations of enhanced reactivity in sprayed and emulsified microdroplets. This usually involves a combination of molecular dynamics and high-level electronic structure calculations. I also work on the construction of advanced force fields that aim to quantitatively reproduce an energy decomposition analysis, including all many-body contributions. In the long-term, I hope to combine these advanced force fields with machine learning to bring more physical realism to the exciting field of machine-learned interatomic potentials.

Graduate Students

Oufan Zhang

I apply machine learning to model structural ensembles for disordered proteins and drug discovery.

Eric Wang

My thesis research focuses on developing advanced many-body polarizable force fields (MB-UCB) for biomolecules using energy decomposition analysis (EDA), as well as studying the bio-molecular interactions. I’m also involved in a drug-discovery project where we use deep reinforcement learning to generate viral inhibitors and apply physics-based methods including docking, molecular dynamics and free energy perturbation to evaluate the potency.

Oliver Sun

I am dedicated to investigating the intricate dynamics of protein flexibility within the realm of drug discovery. My research focuses on utilizing computational methodologies, including both classical approaches and deep learning techniques, to evaluate the entropy associated with protein-ligand binding interactions.

Eric Yuan

My research aims to harness the full potential of machine learning models. By leveraging the accuracy and efficiency of these models, we can achieve precise predictions of high-order derivatives without the need for explicit training on them. This capability extends to calculating Hessians on potential energy surfaces, which are essential for optimizing transition states, as well as predicting chemical shifts with ab initio quality and force field efficiency.

Lukas Kim

My research focuses on the development of reactive force fields informed by molecular properties of reactivity, such as the Mayer and Wiberg bond indices. I use a combination of machine learning and empirical models to enable future large-scale and routine studies of reactive systems.

Undergraduate Students

Dorian Bagni

I utilize machine learning and advanced computational techniques to model protein-ligand interactions. My research focuses on developing innovative frameworks to enhance the efficiency and accessibility of tools, thereby accelerating the drug discovery process for scientists.

Visiting Scholars