Fabian Spaeh

A picture of me

Fifth-year PhD student in computer science at Boston University advised by Alina Ene. I am broadly interested in optimization and currently working on learning-augmented algorithms for online allocation problems, submodular maximization, and opinion dynamics. Previously, I completed a bachelor’s and master’s degree in computer science at the University of Konstanz. You can contact me by email via fspaeh at bu dot edu.

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Publications and Manuscripts

publications
[1]
  1. Ristache, F. Spaeh, and C. Tsourakakis, “Wiser than the wisest of crowds: The Asch effect and polarization revisited.” ECML PKDD 2024, doi: 10.48550/arXiv.2406.07805.
[2]
  1. Spaeh, K. Sotiropoulos, and C. Tsourakakis, “ULTRA-MC: A unified approach to learning mixtures of markov chains via hitting times.” In submission, doi: 10.48550/arXiv.2405.15094.
[3]
  1. Spaeh and C. Tsourakakis, “Markovletics: Methods and a novel application for learning continuous-time markov chain mixtures.” WWW 2024, doi: 10.48550/arXiv.2402.17730.
[4]
  1. Spaeh, A. Ene, and H. L. Nguyen, “Online and streaming algorithms for constrained k-submodular maximization.” In submission, doi: 10.48550/arXiv.2305.16013.
[5]
  1. Spaeh and A. Ene, “Online ad allocation with predictions.” NeurIPS 2023, doi: 10.48550/arXiv.2302.01827.
[6]
  1. Spaeh and C. Tsourakakis, “Learning mixtures of markov chains with quality guarantees.” WWW 2023, doi: 10.1145/3543507.3583524.
[7]
  1. Spaeh and S. Kosub, “Global evaluation for decision tree learning.” arXiv, 2022, doi: 10.48550/ARXIV.2208.04828.
[8]
  1. Hepp, F. Spaeh, A. Schönhals, P. Ehret, and B. Gipp, “Exploring potentials and challenges of blockchain-based public key infrastructures.” IEEE INFOCOM Workshops, 2019, doi: https://doi.org/10.1109/INFCOMW.2019.8845169.

Teaching

In 2022, I received a Teaching Fellow Excellence Award from the Computer Science Department.

Presentations

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