About
I am a doctoral researcher in the Computational Network Sciences Group at RWTH Aachen University. My research interests include Network Science, Complex Systems and Computational Social Sciences. In particular, I focus on the statistical and dynamical analysis of Social Networks with topics ranging from opinion dynamics on hypergraphs to the effects of systematic errors and bias on rankings in social networks.
I am the Social Secretary of the Women in Network Science Society (WiNS) which aims to foster opportunities for the education, employment, and career advancement of women and non-binary genders in network science. Reach out to me if you want to participate in events, want to know more about the society or have any other suggestions or requests!
Interests
- Network Science
- Complex Systems
- Computational Social Sciences
Education
MSc in Mathematical Modelling and Scientific Computing, 2019
University of Oxford
BSc in Mathematics, 2017
University of Bonn
BSc in Psychology, 2021
University of Bonn
Recent News
[23/09/21] I gave a talk at NetGCoop 2021 (originally NetGCoop 2020) on our conference paper on Opinion dynamics with Multi-Body Interactions
[13/09/21] New preprint out: It was a pleasure to work on consensus dynamics on temporal hypergraphs with Renaud Lambiotte and Michael Schaub. Check it out!
[19/08/21] My advisor Michael Schaub and I have been interviewed for an article in Quanta Magazine on higher-order networks.
[02/07/21] I am co-organising this year’s HONS satellite at Networks 2021 which will focus on Higher-order models in Social Systems. Join us for a great line-up of speakers on July 2nd!
[31/06/21-01/07/21] Join us for the first-ever Women in Network Science (WiNS) Satellite happening as part of Networks 2021.
Projects
Higher-order networks
Modelling bias and systematic errors in networks
CoRisk Index
Recent & Upcoming Talks
Oxford Networks Seminar
Featured Publications
Consensus dynamics on temporal hypergraphs
In this preprint, we investigate consensus dynamics on temporal hypergraphs that encode network systems with time-dependent, multi-way interactions.
Consensus Dynamics and Opinion Formation on Hypergraphs
In this chapter, we derive and analyse models for consensus dynamics on hypergraphs.
Multibody interactions and nonlinear consensus dynamics on networked systems
In this work, we derive and analyze models for consensus dynamics on hypergraphs, where nodes interact in groups rather than in pairs. Our work reveals that multibody dynamical effects that go beyond rescaled pairwise interactions can appear only if the interaction function is nonlinear.
Recent Publications
Modelling Non-Linear Consensus Dynamics on Hypergraphs
Systematic edge uncertainty in attributed social networks and its effects on rankings of minority nodes
Contact
- neuhaeuser@cs.rwth-aachen.de
- Ahornstraße 55
52074 Aachen - Department of Computer Science, Building E3