At Cascade we develop software for high-fidelity simulations of fluid flow in complex geometries. My contributions have focused on CFD preprocessing tools (discrete computational geometry, polyhedral unstructured mesh generation based on Voronoi-diagrams), simulation diagnostics & data analytics (in-situ data retrieval, processing of simulation data, image analysis), and cross-platform GUI development. I'm also the resident CAD engineer (SpaceClaim) at Cascade, taking our customers' most complex models and making them "clean".I'm passionate about helping our users leverage our tools to perform simulations that were previously impossible/unsatisfactory in other tools. I enjoy advocating the use of our tools (to anybody!) from professional/commercial applications to personal interest investigations.

Leveraging my experience as a presentation coach at Stanford, I provided a variety of technical communication consulting services to industry professionals. I primarily worked with company executives to develop and create investment pitch slides, executive summaries, and websites. I also supported marketing endeavors through the design and rendering of 3D animations of technical products. These animations have been used by customers to educate both potential clients and potential investors.

Course instructor for E103: Public Speaking which serves undergraduate and graduate students throughout Stanford University (e.g., School of Engineering, Medical School, Graduate School of Business). Through both group and individual tutorials, instructed students in the full range of speaking activities: from impromptu talks to carefully rehearsed formal presentations (both technical and non-technical topics), including instruction on the development and use of visual aids.In addition to course instruction, provided speech and presentation consulting services for graduate students, focusing on specific conference, PhD defense, or academic job interview talks.

Research and application of an uncertainty quantification framework for epistemic model-form uncertainty. Development of new wall-blocking approaches for RANS models based on turbulence anisotropy.Developed and created informational material (presentations and marketing videos) for the Exascale Computing Engineering Center (ECEC) at Stanford. These materials have been used by the Chair of the Mechanical Engineering Dept., the director of the ECEC, and presented at the Super Computing conference (2014).

Modeling numerical simulations of physical processes under uncertainty using both intrusive and non-intrusive sampling-based approaches. Focus on Reynolds-averaged Navier-Stokes (RANS) turbulence model uncertainty in a variety of flows ranging from subsonic to supersonic/hypersonic flows and multi-fluid flows with combustion. Developed a new methodology (intrusive approach) to assess epistemic model-form uncertainty in RANS simulations. C++ implementation of methods in Stanford's large scale, parallel, RANS solver JOE.

Implemented model-form uncertainty quantification capability into Sandia's large scale, parallel, multi-physics simulation software ARIA. Participated in Fluid & Thermal Mechanics Team's Scrum development, including both daily stand-up meetings and sprint reviews.

Sensitivity analysis of the Mars Science Laboratory's (MSL) thermal protection system; investigating the influence of turbulence models, computational meshing strategies and resolutions, and boundary conditions. Simulations using NASA's hypersonic reacting flow solver DPLR were run on the Columbia supercomputing cluster.Developed a chemical kinetics reaction verification and conversion tool. Chemical reaction descriptions (provided in Chemkin format) are evaluated for consistency, and if consistent are converted into a DPLR-readable data format (used to specify chemical reaction rates). Implementation in Python.