Fourth-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, take a
look at my CV, or follow me on Github.
publications
[1]
- Spaeh and C. Tsourakakis, “Learning mixtures of
continuous-time markov chains.” In submission.
[2]
- Spaeh, A. Ene, and H. L. Nguyen, “Online and streaming
algorithms for constrained k-submodular maximization.” In
submission, doi: 10.48550/arXiv.2305.16013.
[4]
- Spaeh and C. Tsourakakis, “Learning mixtures of markov chains
with quality guarantees.” WWW 2023, doi: 10.1145/3543507.3583524.
[6]
- Hepp, F. Spaeh, A. Schönhals, P. Ehret, and B. Gipp,
“Exploring potentials and challenges of blockchain-based public
key infrastructures.” IEEE INFOCOM Workshops, 2019.
Teaching
In 2022, I received a Teaching Fellow Excellence Award from the
Computer Science Department.
- CS 537 -
Randomness in Computing (Sofya Raskhodnikova). Graduate Class. Fall 2021
and Fall 2022
- CS
531 - Advanced Optimization Algorithms (Alina Ene). Graduate Class.
Spring 2022 and Fall 2023
Presentations
- Online Ad Allocation with Predictions.
Northeastern University CS Theory Seminar. 2023. Talk
- Online Ad Allocation with Predictions.
Boston University Algorithms and Theory Seminar. 2023. Talk
- Learning Mixtures of Markov Chains with Quality
Guarantees.
WWW 2023. Talk
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