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
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Optimal Robustness-Consistency Tradeoffs for Learning-Augmented
Metrical Task SystemsInternational Conference on Artificial Intelligence and Statistics 2023 -
The Online Pause and Resume Problem:
Optimal Algorithms and An Application to Carbon-Aware Load ShiftingACM SIGMETRICS/IFIP Performance 2024 -
SustainGym: Reinforcement Learning Environments for Sustainable Energy SystemsNeural Information Processing Systems Datasets and Benchmarks Track 2023
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Chasing convex bodies and functions with black-box adviceConference on Learning Theory 2022