Research in the division of healthcare simulation sciences, department of surgeryInvestigated reinforcement learning AI agent actions on a simulated sepsis patientQuantified curvature to define injury pathology in hemorrhage Identified Naloxone requirements for Fentanyl overdose on a virtual patient populationCreated a database for experimental tissue mechanical properties data connected to a websiteusing the Django frameworkCollaborated with clinicians the department of emergency medicine and anesthesiology toinvestigate trauma physiologyCreated the build system for the MoHSES healthcare simulation framework using CMake andBuildbotLed four student teams in the department of biomedical engineeringCreated all course content for the computational physiology course in the masters programon healthcare simulation researchWrote grant proposals totaling 200K dollars over two years, supporting private industry andclinicians across the school of medicinePresented research at SIAM dynamical systems, SIAM life sciences, and American College ofSurgeons Simulation Summing Organized two symposiums on mathematical models of immunology and AI in medicine

* Principal Investigator for the BioGears project* Principal Investigator for the BurnCare burn training application * Lead a multidisciplinary team across 4 different projects, including academia, industry and government * In charge of agile development processes, product roadmap, delivery scheduling, and direct communication with government customers* Led and won multiple research and development funds through Defense Health Agency and Army Research Lab grants* Communicate research progress through multiple conferences and peer reviewed publications, including the BioGears 2020 conference* Oversaw implementation of all models associated with BioGears releases 6.3-7.4* Using Jira for agile work development sprint Planning * Scoping all technical work across multi-divisional team* Managing a team of Engineers to complete technical requirements * Proposal management, business development, and proposal development for future research funding* C++ code implementation, including modern C++ integration, object oriented software design and model implementation* Oversaw all continuous integration development including build bot implementation and slack bot plug in* Physiology modeling design process/development * Cmake for configuration and multi-platform build development for multiple large C++ project* Prototyping and providing community support using Python

* Expanded the BioGears physiology model by adding gastro-intestinal digestion/absorption, diuretic drug, and pain stimulus models* Nominated and won federal innovation award in collaboration with Telemedicine and Advanced Technology Research Center (TATRC) government lab* Updated the BioGears build library to be hosted on Github, modernized development timeline* Won two government contracts totaling 4 million dollars in additional research and development funding* Oversaw implementation of all models associated with BioGears releases 6.1-6.3* Implemented a new renal system model in the BioGears engine with local autoregulation* Updated blood/gas model and matrix circuit solver implementation* Led validation and unit testing of C++ code base* Oversaw Jenkins cloud build testing environment including daily reporting and system validation

Developed problems and solutions to add to their online differential equation product.

* Analyzed how pressure changes induced by heart failure affect the hemodynamic and reabsorption function of the kidney* Taught two semesters of introduction to partial and ordinary differential equations, developed all course materials* Coordinated validation and experimental data with University of Ontario research hospital clinicians* Presented at Experimental Biology 2015 on venous pressure changes on filtration mechanism* Fluid-structure interaction model studying forces on red blood cells during peristaltic pumpingSKILLS USED: PythonFortran Iterative Methods Biological ModelingC++

* Developed a fully coupled fluid-structure interaction code in C++ and Python to test the performance of valveless pumping* Created a new computational valveless pumping mechanism using muscle cells to provide neuro-mechanical forcing in the system* Presented and work at 12 conferences, domestic and abroad, and published results at: IEEE, SIAM, and SICB* Led wet lab organism maintenance and worked with lab-mates to collect particle image velocity data from* Collaborated with colleagues from the Biology department to collect experimental results to validate computational models* Coordinated and planned the applied computational physiology collaborative meetings between the biology and applied mathematics departments* GAAN and HHMI scholar* Taught two courses with full responsibilities: computational linear algebra, and chaos and population dynamicsSKILLS USED: Python Numpy MatplotlibGitOpenMPC++ Visit Paraview Fortran