- In-house "quantum chemical engineer", helping teams across the company find the right quantum-chemical solutions to their problems in machine learning, drug discovery, and force field development- Developed and manages a high-throughput engine for running millions of quantum chemical calculations using multiple different QC engines across a large, multi-site, heterogenous CPU and GPU fleet with minimal human intervention- Force field developer with a focus on next-generation hybrid ML-MM force fields, many-body effects, and unprecedented levels of accuracy to body quantum chemical and condensed-phase references- Mentors and manags junior research scientists on the force fields team

- Characterized a previously unexplained mechanism of magnetic resiliency in the Mn/FeRu$_2$Sn Heusler system by examining the mutual influence of magnetic and chemical ordering- Extended the CASM open-source software package to simulate and fit both discrete and continuous magnetic degrees-of-freedom- Resolved a fundamental disagreement between \textit{ab-initio} and experimental models of the Co/Pt system using machine learning, statistical mechanics techniques, and high-throughput ab-initio calculations- Developed a new method to parameterize cluster expansion Hamiltonians using experimental observables and select a suitably sparse set of descriptors from a field of hundreds or thousands

- Developed and improved course material for senior-year chemical engineering students with a focus on process control and design.- Engaged with and educated undergraduate students in a laboratory setting, providing assistance and guidance and evaluating student performance and progress.

- Planned, constructed, and wrote tooling for the development of a "test set" of reference structures suitable for evaluating the performance of new Density Functional Theory approximations on transition metal binaries- Performed millions of electronic structure calculations, across thousands of crystal structures and a dozen DFT techniques, by developing an extended high-throughput infrastructure, with significant work put towards automatic detection of and recovery from a wide variety of calculation errors- Constructed a new approach to fitting multi-component effective Hamiltonian models of alloys in molecular dynamics simulations using novel machine learning techniques

- Developed and tested rapid prototyping systems for small-scale production of touch screens and touch pads.

- Unified simulation and experimental observations of the buckling of vertically-aligned carbon nanotube pillars by applying computer vision techniques to SEM images to produce a density figure-of-merit

Developed protocols for subcritical water extraction, for use with upstream analysis systems in extraterrestrial rover platforms.