Backend software engineer working in Python to build features, services, and data infrastructure with tools such as FastAPI, MongoDB, and Azure to support distributed sensing networks.

Doing a variety of things at the Labs!

• Software Development: creating ETL pipelines to take packet level data collected from my automated instruments talking to embedded sensing suites or data stored in proprietary file formats, parsing measurements, and uploading to SQL databases that I create the schemas for. Then I create scripts to pull from the database to automate analysis and visualization of key signals. This work is done primarily in Python and SQL with some Cpp code.

• R&D: Owning the design of a proprietary minimalist eddy current based proximity sensor. This involves things like deriving transfer functions to characterize for inductor thermal variance, identifying key drivers of performance for the nonlinear displacement to sensing relationship, optimizing our frequency counting algorithm constrained by our sampling rate, and quantifying end product error and performance. Analysis and documentation done in Jupyter notebooks and data is stored to a SQL database I made for full transparency.

• Getting my hands dirty: Assisting with bring up and debugging PCBs by leveraging my working knowledge of the FPGA firmware and onboard analog circuitry. This involves a swath of instruments such as oscilloscopes, logic analyzers for SPI debugging, LCR meters, DMMs, and many more toys. Frequently I’m diving into the raw byte data of packets to root cause an issue.

I designed an open source high throughput automated leaf area measurement device powered by a Raspberry Pi that:

• Utilized a GUI in Python that allows you to interact with the system via touchscreen

• Captured images of plants on a 100x100mm Petri dish in a 3d printed enclosure designed in Solidworks

• Simultaneously displayed the processed the leaf area image and saved leaf area data to a .csv file that synced with your google drive

https://github.com/HugeCoderGuy/LightsCameraPlants

This internship with the Vision Automation team in the Supply Chain Operations Automation group focused on data analytics (SQL & Tableau) but also brushed up on project management (handling stakeholder expectations) and product development (user interviews & requirements).

Sandia Engineering Design Award Winner

At the heart of Lawrence Livermore National Laboratory’s National Ignition Facility lies the Target Line Replaceable Unit (LRU), which holds the laser’s target in place. Formerly, the design of the LRU was constrained by the need to assemble the component inside the NIF. In our project, we create an assembly and test stand allowing the new LRU to be built and evaluated externally before installation in the NIF. Our stand will enable a new LRU design as well as eliminate the waiting time associated with assembling the LRU internally.