About Me

    Hello! My name is Jim Slone. I am a Senior Undergraduate Student at William & Mary studying Physics and Data Science. I am endlessly fascinated by Computational Physics, Machine Learning, and Scientific Research.

    Currently, I am working as a Research Assistant in the William & Mary Physics Department under the supervision of Prof. Saskia Mordijck. My research focuses on using Machine Learning Techniques to infer Experimental Transport Conditions in Tokamak Reactors. This project has allowed me to wear many hats, diving into Computational Modeling, Numerical Methods, High-Performance Computing, Convolutional Neural Networks, Autoencoders, Generative ML, Reinforcement Learning, Uncertainty Quantification, Bayesian Optimization, and more.

    In addition to my research, I am also a Teaching Assistant for the Data Science Department at William & Mary under Prof. Daniel Vasiliu, where I help with Data 301: Applied Machine Learning. I write class materials, write the homeworks and exams, hold office hours twice a week to help students, and answer students questions online.

    In my free time, I enjoy working on personal coding projects, playing with my pets (both cats and bunnies!) and watching YouTube lectures/documentaries. I always enjoy learning new things and strive to be as well-rounded as possible!

    I am graduating in May 2026 and am currently applying to graduate schools, with a primary focus on Machine Learning Application to Plasma Physics. If you have any questions about me or my work, feel free to reach out! I tend to check my email fairly often and respond quickly: jvslone@wm.edu.

    Feel free to browse this website. Enjoy your stay!