Tokamak fusion reactors produce vast amounts of information rich data. Traditional approaches to data analysis struggle to cope with the scale of the data produced. In this project we aim to apply techniques from randomized numerical to beat the curse of dimensionality. Interested students should have a solid understanding of linear algebra, probability, and be happy coding in MATLAB or Python.

This project is eligible for a matching fund stipend from the Data Science Institute. This is not a guarantee of payment, and the total amount is subject to available funding.

Faculty Advisor

  • Professor: James Anderson
  • Center/Lab: Anderson Group
  • Location: Mudd 1007
  • The Anderson group develops theory and algorithms for the analysis, design, and control of large-scale cyber-physical systems.

Project Timeline

  • Earliest starting date: 9/6/21
  • End date: 6/30/22
  • Number of hours per week of research expected during Fall 2021: ~5
  • Number of hours per week of research expected during Summer 2022: ~12

Candidate requirements

  • Skill sets: Coding, linear algebra, probability. Must be comfortable with math.
  • Student eligibility: freshman, sophomore, junior, senior, master’s
  • International students on F1 or J1 visa: eligible
  • Academic Credit Possible: Yes