- Utilized a previously unused method to calculate the resummation of large logarithms in the probabilityof producing Charm quarks in events at the LHC.- Used standard techniques to calculate the cross section for Charm quark production, with a W Boson,at Leading Order and Next-to-Leading Order in the strong coupling constant.- Combined two calculations, of large logarithms and production cross section, to increase precision ofCharm quark production to higher than any previous calculation.- Implemented and tested previously unused methods for generating particle final state configurations at the LHC.- Merged our calculation into a larger C++ event generator code base solving several subtle problems involving data types and data transfer between several parts of the generator.- Validated calculations in various importance regions by running our generator on one of several largecomputing clusters at Lawrence-Berkeley National Lab.

- Developed novel methods to characterize thermal and visible cameras and provide a live, overlayed image of the two fields of view.- Used OpenCV to process images from several cameras and transform them to meet user-interface needs and constraints. - Created a code base to find, measure and track brightness of LED's with the computer vision library OpenCV and Python.- Developed and utilized a workflow to measure temperature changes inside a microwave cavity with thermal image data.- Using the machine learing library Keras, with GPU accelerated Tensorflow, trained an artificial neural network, with thermal images and LED brightness, to predict temperatures in a microwave cavity.

- Developed and implemented drivers for capturing and storing visible and infrared camera images. Thiswas done both with Python and using the library Boost to wrap C++ drivers with Python.- Trained convolutional neural nets to detect the boiling transition of various liquids with the Pythonlibraray Keras.- Implemented a client/server architecture in Python, with no previous knowledge of client/server systems, that allowed two Raspberry Pi’s to receive and run commands sent from a desktop computer.- Trained linear and nonlinear regression fitting, in Python, to calibrate an infrared camera to one degree C accuracy.- Utilized the computer vision library OpenCV for identifying and tracking contours created by ”hotspots”in an infrared camera and correlating overlapping fields of view of multiple cameras.- Created systems for calculating/plotting the temperature over time, of various regions in a infrared camera feed.- Wrote control systems to monitor infrared camera feeds to achieve and maintain temperature in a microwave oven.