Interned across Rotary & Mission Systems and Missiles & Fire Control on the F-35 program. Built a computer-vision pipeline that qualified a new EOTS frame material at 78% lower unit cost.

Interned across two divisions, Rotary and Mission Systems (RMS) and Missiles and Fire Control (MFC), contributing to the F-35 program.

EOTS window frame material

• Analyzed material exposure test data from an Air Force research facility, writing scripts to analyze video footage of material degradation during high-velocity rain erosion testing.
• Built a Python computer-vision pipeline using color segmentation to quantify coating delamination, and used MATLAB to evaluate performance.
• Used the results to qualify a new F-35 EOTS frame material, cutting unit cost by 78% (over $70,000 in annual savings) while maintaining RCS compliance.

Machine learning for pilot selection

Proposed an ML classification system for military pilot training and helped architect the project, which aimed to identify pilots suited for an accelerated fighter pilot training stream. Designed custom simulation environments for automated specialization-track assignment, defined the data parameters, and interviewed veteran instructor pilots.

Integrated Learning Environment

Validated the web architecture’s ability to consolidate simulator telemetry for the Royal Australian Air Force (RAAF). Read the Lockheed Martin feature.

Promotional video

Cast as a student pilot in a promotional video filmed at the Sikorsky Training Academy with Black Hawk helicopter assets.