Stenomics' EchoPlan software uses computer modeling, big data, analytics, and machine learning to help diagnose and treat heart disease.- Winner of the 2016 ASE Echovation Innovation Challenge (asecho.org/echovation-challenge-2016/team-echoplan)- Invited presenter at 2016 Transcatheter Cardiovascular Therapeutics- Finalist in the 2016 Design of Medical Device Valuation Competition

Senior member and technical lead of R&D team developing stroke and pulmonary embolism algorithms using machine learning. Methods include deep learning, convolutional neural networks, classification, object detection, semantic segmentation, autoencoders, and dimension reduction. Primary developer of multiple FDA-cleared products.

- Develop machine learning algorithms to analyze biological data.- Data and model reduction methods for large-scale data sets.- Statistical modeling and inference methods to understand biological systems.

Independent consulting in machine learning, data analytics, algorithm development, computational geometry, and numerical simulations. Clients include start-ups and publicly traded companies in the life science, data analytics, and medical device sectors.Programming: C++, Matlab/Octave, Java, PythonLibraries: Boost, MPI, OpenCascade, PCLMachine learning: Weka, Scikit, TensorFlowImage processing: ImageJ, ParaViewCAD/CFD: Ansys, Gmsh. OpenFOAM, Overture, Rhino3D, TgridMisc: AWS, high performance computing (HPC), Git, Agile (Jira), RESTful, Json, scripting, statistics, optimization

Hands-on role as creator and developer of core algorithms that analyze large data sets. Computational algorithms identify objects within three-dimensional space and determine differences between CAD models and point clouds.

Senior member of R&D staff focused on cardiovascular flow modeling, computational fluid dynamics (CFD), machine learning/data analysis, and verification and validation of HeartFlow’s software for computing Fractional Flow Reserve from medical images. Work also focused on developing next generation computational technologies and preparation of FDA documentation.

Staff researcher focused on computational algorithms, high performance computing, and mathematical modeling. Projects included: model reduction, analysis of large data sets, shape optimization, fluid dynamics, and mathematical analysis.

Postdoctoral Fellow in Chemical Engineering focused on computer modeling/simulation for engineering applications in fluid dynamics and chemically reacting flows.