Automated manual file error checking processes using Python scripting reducing checking time by 90%Identified and removed redundant actions in automated tests resulting in over 20 testing hours saved per month

Developed C++ software for end cryptographic units to provide encrypted anti-jam communicationsImplemented time management mode allowing the clock synchronization of communicating devices Automated and wrote hardware software integration test scripts to mimic field use and eliminate manual testing efforts

Investigated the use of wearable smart fabrics for non invasive health monitoring of DVT patientsResearched neural network classifier architectures and training methods to assess Deep Vein Thrombosis risk reduction activities with up to 97% accuracyBuilt a real-time software system that collects data from multiple independent sensors, extracts specified features, and performs activity classification

Developed C++ software for an internal research and development eort to detect high frequency radio transmissions and geolocate the source in real-time Modified the inertial navigational system sensor API to reduce query latency for the latest data values by 35% by removing unused measurements and optimizing data streamingBuilt interpolation algorithms that synchronized multi-sensor data to common timestamps

Analyzed system level power requirements for US Navy shipboard radar components ensuring maximum operating capabilities during equipment failure

Deep Vein Thrombosis (DVT) ProjectCollected human data following institutional review board(IRB) protocolsDeveloped Matlab scripts to parse raw data and extract usable featuresCreated a Matlab neural network and trained classifiers to distinguish activity statesContributed to a Git repository used by team membersBellyband Device ProjectConducted data collection on radio-frequency identification(RFID) signal strengthCreated Python and Matlab algorithms to remove electromagnetic interference from recorded data