Stefan Neumann
Assistant Prof. Dr.techn. / BSc MSc
Research Focus
- Information Systems Engineering: 51%
- Logic and Computation: 49%
Research Areas
- Data Mining, Machine Learning, Graph Algorithms, social network analysis, Combinatorial Optimization, Theoretical Compurter Science, Algorithms and Data Structures
About
My research focus is on algorithms for data science and for social network analysis. In particular, I am interested in the following topics:
Foundations of data science: I develop practical data science algorithms with provable guarantees. I am particularly interested in the beyond worst-case analysis of algorithms.
Social network analysis: I study how interventions, such as timeline algorithms, influence the polarization and the disagreement in (online) social networks.
I am also generally interested in graph algorithms and (dynamic) data structures.
For more information, please see my homepage https://neumannstefan.com/.
Role
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Assistant Professor
Machine Learning, E194-06
Courses
2024W
- Bachelor Thesis in Computer Science / 194.112 / PR
- Fundamentals of Digital Systems / 192.134 / VU
- Project in Computer Science 1 / 194.145 / PR
- Seminar for PhD Students / 194.110 / SE
2025S
- Bachelor Thesis in Computer Science / 194.112 / PR
- Project in Computer Science 1 / 194.145 / PR
Projects
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Industrial Master's Thesis: LLM-based Automated Root-Cause Analysis for Unexpected System Behavior
2024 – 2025 / AVL List GmbH -
Towards Trustworthy Recommendation Systems for Online Social Networks
2023 – 2030 / Vienna Science and Technology Fund (WWTF)
Publications
- Sublinear-Time Opinion Estimation in the Friedkin--Johnsen Model / Neumann, S., Dong, Y., & Peng, P. (2024). Sublinear-Time Opinion Estimation in the Friedkin--Johnsen Model. Proceedings of the ACM on Computer Graphics and Interactive Techniques, 8(3), 2563–2571. https://doi.org/10.1145/3589334.3645572