My primary professional tool sets are C++, C#, Python, and MATLAB. Beyond the languages themselves, I work with many popular libraries including Boost, Numpy, Pandas, Scikit-Learn, Matplotlib, TensorFlow, Eigen, Google Test and Google Mock. Finally, I also pride myself on being formally trained in UML, industrial design patterns, and software architecture. I rapidly make myself essential to any team working at the cutting edge of computer vision, machine learning, or robotics, fitting any role from traditional software development, to data processing, analysis, and machine learning.
Presently, I am working under the guidance of Frank Delgado and Matthew Noyes at NASA Johnson Space Center’s Hybrid Reality Lab on the Pupillary Response Classification Project (PRCP). The aim of the PRCP is to develop a recurrent neural network (RNN) that can deduce an astronaut’s mental effort by observing the diameter of the subject’s retina. In order to achieve this, I am implementing a library for extracting, cleaning, normalizing, and classifying pupillary response data. This work will empower NASA’s Flight Surgeons to preemptively manage crew mental health and stress levels.