Jacob Carroll

Background

About Jacob Carroll

I have a strong educational background in physics and statistics, with a Doctor of Philosophy in Statistical Physics, a Master of Science in Physics, and Bachelor's degrees in Physics and Mathematics. My technical skills encompass a range of programming languages such as Python, C++, R, and JavaScript, as well as various software and computational methods relevant to machine learning, artificial intelligence, and physics research.In terms of experience, I have worked as a Machine Learning/AI Engineer at Lockheed Martin Space since September 2021, where I have been involved in the development of AI/ML capabilities, including ATR, NLP, and ontology-based reasoning. I have also worked as a Software Engineer at Lockheed Martin Space from June 2019 to September 2021, where I led a team in designing and implementing flight and simulation software for the Janus SIMPLEx mission. Additionally, I developed modules for simulating components of the deep space probe Lucy and worked on C++ simulation architecture and models for GPS satellites.As a Graduate Researcher at Virginia Tech's Center for Soft Matter and Biological Physics, I programmed neural network software, simulated large-scale networks of biologically inspired neuron models, and conducted analysis using tools like SciPy and R. I also developed software to simulate ligand-receptor bonds and analyzed the simulation results.During my research internships at Los Alamos National Lab in 2018 and 2017, I designed and trained convolutional neural networks for image de-noising, analyzed their performance, and explored the effects of perturbations. I also worked on highly parallelized convolutional neural networks for sparse image reconstructions.In addition to my research and engineering roles, I served as a Graduate Teaching Assistant at Virginia Tech, mentoring undergraduate students and assisting with physics experiments and tutoring.My publications demonstrate my research contributions in the field of statistical physics and neural networks, and I have received several honors and awards for my work, including Outstanding Poster Award, Ray F. Tipsword Graduate Scholarship, and First Place Short Talk Award, among others.