- Supported PK/PD modelling team in conducting virtual clinical trials by updating various model components, data analysis functions, model / data validation functions, and developing new plotting features- Unified data anaylsis methods across backend and plotting, which required recalculation due to selection of subgroups and custom patient criteria, to ensure data quality when generating reports- Developed an equilibrium-based binding primitive which offered significant speed up to models involving fast kinetics when compared to the integration time step- Added significant documentation and test coverage; Developed a testing framework to simplify test generation and reduce the number of deployed bugs- Acted as a liason between scientific and software engineering team members to align the purpose and requirements for new feature requests

- Developed Mathematica code for the analysis of scientific data, following best software practices for documentation and unit testing. Conducted frequent code reviews, wrote design documents, and addressed bugs during on-call shifts.- Collaborated with research scientists to develop tools assisting with the design, analysis, and visualization of mass spectrometry-based proteomics experiments, resulting in more efficient use of laboratory equipment and faster research timelines.- Developed REST API micro-services using Flask for Python, with Docker, Kubernetes, and AWS, for simulating peptide fragmentation and analyzing mass spectrometry data sets.- Integrated new analysis, simulation, and visualizations functions into the front-end product.- Developed and implemented a materials packing algorithm resulting in more efficient use of facility storage space and floor operator time.- Contributed to internal development frameworks and tools, resulting in faster development times, and to the public software development kit, adding functionality for uploading, downloading, and streaming files from Amazon S3, with appropriate authorization, and integrating the uploaded files into the relational database.

- Computational chemist researching metal-organic frameworks (MOFs) and their applications. Dissertation focused on the development of a gas sensing array (electronic nose) for breath-based disease detection.- Conducted high-throughput grand-canonical Monte Carlo simulations, writing Bash and Python scripts to generate and manage jobs.- Using Python, developed a genetic algorithm for the design of optimized gas sensing arrays from a large library of materials. Also developed analytical models and numeric algorithms for the prediction of gas composition given a known sensor array output.- Building upon ASE for Python, developed tools for positioning, modifying, and visualizing molecules and crystalline materials, and generating input files for molecular dynamics simulations.- Other research projects included predicting electrical conductivity in MOFs using density functional theory, elucidating mechanisms of liquid sensing platforms using molecular dynamics, and predicting ligand exchange reactions and topological conversions in MOFs using a molecular dynamics-based toy model.

- Developed nanostructured electrodes and coatings for lithium-metal batteries to control the deposition of lithium and formation of the solid electrolyte interphase.- Developing electrospun polymer separators for lithium-sulfur batteries to minimize poly-sulfide dissolution.- Develop polymeric coating for controlling current density to improve coin cell testing, and investigated swelling due to solvent in the liquid electrolyte.

- Synthesized nanoporous carbon films through deposition of a glucose/silica nanoparticle solution, followed by carbonization, and subsequent etching of the silica- Examined the effects of synthetic conditions and nitrogen doping on film ordering and behavior.

- Developed and refined laboratory equipment used to synthesize nanoparticles for biopharmaceutical research applications via the rapid expansion of a supercritical solution (RESS) of CO2 through a fine-tipped nozzle.- By varying process conditions, nozzle types, and collection methods, we developed an effective and highly reproducible procedure, resulting in a poster presentation at a local technology conference.

- Developed a computational model in MATLAB for comparing various energy storage technologies for use with concentrated solar power plants, focusing specifically on latent heat thermal energy storage using inorganic salts as the phase change materials.- The model spanned hourly to yearly operations and the was used to determine economically efficient operating conditions.