-Designed novel geospatial anomaly detection and trajectory prediction machine learning algorithms-Implemented predictive Bayesian hierarchical models in Pyro-Implemented vehicle and gun detection algorithms using computer vision models within PyTorch architecture-Created semi-supervised learning workflows to reduce model deployment time and user labeling workload -Designed data wrangling and ETL processes for image processing, geospatial data structures, and automated XML verification

-Created radar algorithms in simulation, spanning from literature review to software implementation-Collaborated with adjacent teams to aid in simulation scalability and debugging-Designed simulation models to emulate environmental effects, such as atmosphere, clutter, weather, and target scintillation-Implemented statistical models of sensor effects and noise-Created design of experiments in simulation to optimize tracking algorithm parameters

-Matured software prototypes of radar phenomenology for simulation product-Developed RF software libraries utilized by other teams-Participated in product demos and technical deep dives with customers

-Responsible for the design, testing, and implementation RF signal processing algorithms-Aided in the creation and implementation of statistical models in support of RF sensor simulation-Developed and maintained flight software and software simulation environment-Created telemetry data analysis software tools-Performed data analysis of flight test telemetry

-Aided chief departmental engineer in developing statistical models to more accurately model Navy weapon systems reliability, and optimize PL/SQL code to reduce calculation times on Navy performance metrics website-Managed contracted software developers to modernize Navy performance metrics website, and streamline business processes-Interfaced with various levels of departmental personnel and developers in reporting, tracking, and enforcing bug resolution-Created algorithms for predictive point estimates of weapon system reliability from time series data in PL/SQL-Utilization of machine learning techniques to automate evaluation of Navy maintenance data.-Participated in studies that utilized stochastic process (Markov and Monte Carlo simulation) methods to create reliability, maintainability, and availability metrics-Maintained Navy cost, part, maintenance, and reliability databases-Engaged in research on methods of evaluation of predictive reliability of highly complex Navy systems.-Performed failure root cause analysis of Navy systems through maintenance and failure data, and authored studies providing recommendations for cost savings and reliability improvements

-Interfaced with customers, engineers, Marketing, Project Managers, and Account Managers to design technical training guides for X-Ray medical device installations, such as posters, video animations, brochures, and presentations used in customer meetings-Utilized Smartsketch and AutoCAD software to create plan views of equipment layouts for X-Ray and MRI medical device multi-platform environment-Collaborated with other team members to create and maintain multi-media training guides, technical documentation, and project installation/maintenance guides-Interpreted technical documents to create 3D renderings of customer installation sites using AutoCAD, Microstation, Modo, and 3D Studio Max software-Conducted internal review of various 3D rendering software platforms in an effort to increase department efficiency and presented findings to management-Led initiative of making software workflow best practices recommendations to management, reducing average project turnaround time by 80%-Designed and created sales brochure used as a nationwide standard sales document by Philips Account Managers