Train a variety of reinforcement learning models.Identify, document, and correct AI generated code.

We implemented quantum machine learning algorithms on data collected from the Large Hadron Collider to demonstrate the efficacy of quantum machine learning algorithms compared to classical and deep machine learning algorithms. Using Qiskit, we were able to train a model that classifies particles with a 95% success rate using four qubits.

I assisted the research activities in Dr. Linke’s Strontium ion trap for Quantum Networking. I joined the lab shortly after its inception and was responsible for the implementation of the control system utilizing ARTIQ. I designed and managed the repository that held all of the lab’s software. Once the lab was operational, I wrote experimental code sequences that manipulated Strontium ions based on feedback from multiple sensors with microsecond accuracy. I also wrote code that took in data from multiple sensors and displayed it in a useful format for the researchers. My code will facilitate the research performed in the lab, and I expect to be included on research papers forthcoming shortly by the lab’s graduate student investigators who are supervised by Dr. Linke. I also wrote extensive documentation to ensure that the physicists would be able to develop and deploy software in the environment I created. In addition to my software responsibilities, I assisted wherever I could in building the experiment including vacuum chamber work, optics alignment, and miscellaneous lab tasks.

Previously a Software Engineering intern at M3D LLC. At M3D, I was responsible for firmware programming 3D printers, I added unteathered printing support to M3D's printers using an SD card, speed controlled the fan, worked on an internal shipping app, and conducted material tests on new filaments and control boards. At M3D I used C, C++, and C#.