Nicholas Bishop

Developed a satellite constellation optimizer toolkit

• Used nondominated genetic sorting algorithms (NSGA-III) as the optimization algorithm
• Designed fast geometric vision calculations between satellites and points on Earth with 1% accuracy (benchmarked against STK)
• Used MATLAB Compiler SDK to create a deployable Python application of the toolkit

Attempted to solve an open satellite scheduling optimization problem using neuro-evolution of augmented topologies (NEAT)

• Used NEAT to combine neural networks and reinforcement learning to create new strategies of tracking satellites
• Benchmarked new strategies against known ones

Developed an interactive Tableau dashboard as a debugging tool for analysts handling complex RAID simulations

• Manipulated data of discrete event occurrences in simulations to create visualizations that the original data did not lend itself to show

Accepted to the SAIC early career Technical Leadership Program. Gathered skills from several job rotations within the program, including performing modeling and simulation and software development on several different contracts

Applied machine learning techniques on 2014 Medicare dataset to predict average income in a zip code from quantity and types of healthcare services provided

• Used neural networks and other methods found in scikit-learn

Starting with zero knowledge of LabVIEW and Arduino systems, created a robust, automated data acquisition and bandpass filter system which operated within the necessary constraints of error to dynamically change the wavelength of light in a nonlinear optic setup

• Created automated benchmarking and error correction

Synthesize new quantum materials to characterize and analyze properties at low temperatures

• Adjusted presentation of complex concepts to an audience of lesser understanding
• Found and built relationships with new clientele