Scholar
Lutz Oettershagen
Google Scholar ID: NnaJPcMAAAAJ
Assistant Professor at University of Liverpool
Citations & Impact
Citations
191
H-index
8
i10-index
6
Publications
20
Co-authors
12
list available
Contact
Publications
Resume (English only)
Academic Achievements
- Paper: 'Fair Minimum Labeling: Efficient Temporal Network Activations for Reachability and Equity', NeurIPS 2025
- Paper: 'Streaming Stochastic Submodular Maximization with On-Demand User Requests', NeurIPS 2025
- Paper: 'An Edge-Based Decomposition Framework for Temporal Networks', WSDM 2025
- Paper: 'Consistent Strong Triadic Closure in Multilayer Networks', 2024
- Paper: 'Finding Densest Subgraphs with Edge-Color Constraints', WWW 2024
- Paper: 'A Higher-Order Temporal H-Index for Evolving Networks', KDD 2023
- Paper: 'An Index For Temporal Closeness Computation in Evolving Graphs', SDM 2023
- Paper: 'A Temporal Graphlet Kernel For Classifying Dissemination in Evolving Networks', SDM 2023
- Paper: 'Inferring Tie Strength in Temporal Networks', ECML PKDD 2022
- Paper: 'Temporal Walk Centrality: Ranking Nodes in Evolving Networks', WWW 2022
- Paper: 'Spatio-Temporal Top-k Similarity Search for Trajectories in Graphs', 2021
- Paper: 'Efficient Top-k Temporal Closeness Calculation in Temporal Networks', ICDM 2020
- Paper: 'Temporal Graph Kernels for Classifying Dissemination Processes', SDM 2020
- Paper: 'On the Enumeration of Bicriteria Temporal Paths', TAMC 2019
- Paper: 'The Crossing Number of Semi-Pair-Seq-Shellable Drawings of Complete Graphs', Canadian Conference, 2019
Education
- PhD, University of Bonn, Germany, Advisor: Prof. Dr. Petra Mutzel
Background
- Assistant professor at Liverpool University, UK. Primary research areas include algorithmic data analysis, graph data mining, and machine learning for graphs. Focuses on mathematical and computational foundations as well as the engineering and application of efficient algorithmic data analysis on (dynamic) graphs to solve real-world problems. His work focuses on the computational analysis of static and temporal networks, designing and analyzing methods for obtaining new knowledge from complex networks.
Miscellany
- Erdős number is at most 3 (via Giuseppe F. Italiano → Craig A. Tovey → Paul Erdős).
