Nico Christianson

I am a fourth-year Ph.D. student in Computing and Mathematical Sciences at Caltech, where I am fortunate to be advised by Adam Wierman and Steven Low. My research interests lie broadly in online algorithms, learning, and optimization, with an emphasis on developing learning-augmented algorithms with provable guarantees for problems in energy systems, carbon-aware computing, and sustainability. My work is supported by an NSF Graduate Research Fellowship.

Before Caltech, I received an A.B. in applied math from Harvard. While there, I worked with Boris Kozinsky on ionic transport, and with Dani Bassett at UPenn on applied network science.

selected publications

  1. Optimal Robustness-Consistency Tradeoffs for Learning-Augmented
    Metrical Task Systems
    N. Christianson, J. Shen, and A. Wierman
    International Conference on Artificial Intelligence and Statistics 2023
  2. The Online Pause and Resume Problem:
    Optimal Algorithms and An Application to Carbon-Aware Load Shifting
    A. Lechowicz, N. Christianson, J. Zuo, and 4 more authors
    ACM SIGMETRICS/IFIP Performance 2024
  3. SustainGym: Reinforcement Learning Environments for Sustainable Energy Systems
    C. Yeh, V. Li, R. Datta, J. Arroyo, N. Christianson, and 7 more authors
    Neural Information Processing Systems Datasets and Benchmarks Track 2023
  4. Chasing convex bodies and functions with black-box advice
    N. Christianson, T. Handina, and A. Wierman
    Conference on Learning Theory 2022