I am a fourth-year Ph.D. student in computer science at Harvard University, advised by Madhu Sudan. In 2022, I graduated from Columbia University, where I double-majored in Mathematics and Computer Science and worked with Xi Chen. My research is supported by an NDSEG Fellowship.
My research is in theoretical computer science and probability, with a focus on sublinear algorithms, random graphs, property testing, and average-case complexity.
I will be on the job market in Fall 2026.
My email is cmarcussen [at] g.harvard.edu.
[CV] [Google Scholar]
Learning and Testing Convex Functions [paper]
with Renato Ferreira Pinto Jr., Elchanan Mossel, and Shivam Nadimpalli.
Quality control in sublinear time: a case study via random graphs [paper]
with Ronitt Rubinfeld and Madhu Sudan.
Finding the root in random nearest neighbor trees [paper]
with Anna Brandenberger, Elchanan Mossel, and Madhu Sudan.
Random Structures & Algorithms, 2026
A Fast Coloring Oracle for Average Case Hypergraphs [paper]
with Edward Pyne, Ronitt Rubinfeld, Asaf Shapira, and Shlomo Tauber.
RANDOM 2025 (International Conference on Randomization and Computation)
Characterizing the Distinguishability of Product Distributions through Multicalibration [paper] [slides]
with Aaron (Louie) Putterman and Salil Vadhan.
CCC 2025 (Computational Complexity Conference)
Errors are Robustly Tamed in Cumulative Knowledge Processes [paper] [slides]
with Anna Brandenberger, Elchanan Mossel, and Madhu Sudan.
PNAS 2025 (Proceedings of the National Academy of Sciences)
COLT 2024 (Conference on Learning Theory)
Uniformity Testing over Hypergrids with Subcube Conditioning [paper] [slides]
with Xi Chen.
SODA 2024 (Symposium on Discrete Algorithms)
All author names are listed alphabetically, as is the convention in theoretical computer science and mathematics.
At Harvard:
At Columbia, I was a Teaching Assistant for the following courses:
Other: