Peter D. Email & Phone Number

● Refactored an organically grown codebase that had been impossible to maintain and providedinconsistent operation.● Implemented an internals based characterization technique (FSKMinor) in Python thatoperates on the first 0.5s of data to reduce the list of signal candidates that undergo fullinternals processing. ○ Performs subband tuning, demodulation, timing recovery, and correlation with aknown repeating bit pattern. ○ Reduced the computation load of an important signal class by 15%.● Modified an existing Python cyclostationary processing component to support cyclic raterefinement and multi-stage processing. ○ Enabled center frequency agnostic processing for an important class of ~800 signals.● Developed a Line Decoder in C++ based on M2Extra’s line decoding methodology. ○ Implemented as a Threedb datasource component to support efficient operation withthe datasource-based FSKMinor implementation. ○ Utilized Boost Python to enable seamless interoperability between my C++ LineDecoder and our Python-based systems.● Routinely performed signal analysis on PRED snapshots using M2Extra and X-Midas, steppingthrough the full demodulation process to validate and debug system results.● Created robust Python logging and unit tests, as well as detailed Confluence documentation,for all aforementioned tasking.

Sterling, Virginia, United States

● Maintained and developed a distributed message passing web application hosted on Amazon Web Services (AWS) GOVCloud.● Tracked down and fixed memory leaks using Eclipse Memory Analyzer (MAT), performed load testing of critical web applications using JMeter, and developed unit tests using JUnit. ○Refactored a 15 year old inherited codebase with little to no documentation.● Monitored Amazon’s Simple Service Queue (SQS) to ensure proper message passing behavior between software components. Tracked down any sources of error and rectified them.

King Of Prussia, Pennsylvania, United States

● Achieved MF-TDMA capability for a proprietary software defined radio (SDR) by developing a C++ signal processor that dynamically shifts transmission frequency.● Improved frequency shift runtime by 92.5% through algorithm & data structure optimization.● Further enhanced the SDR’s signal processing capability by providing compatibility with GNU Radio (GR) through the creation of a GR C++ module that interfaces with the SDR via API calls.● Reduced onboarding and development time by creating Confluence wiki pages with pre-built virtual machines (VMs) and instructions for secure network access. ● Collaborated on a Scrum team using Agile techniques, tools such as Jira and Confluence, and a software development process that included Git, code reviews, and merge techniques.