I am an lecturer (assistant professor in US terms) at Liverpool University, Liverpool, UK.
My primary research areas are algorithmic data analysis, graph data mining, and machine learning for graphs. I put a strong focus on mathematical and computational foundations as well as the engineering and application of efficient algorithmic data analysis on (dynamic) graphs for solving real-world problems. My work focuses on the computational analysis of static and temporal networks. In my research, I design and analyze methods for obtaining new knowledge from complex networks.
Until the end of June 2024, I was a postdoctoral researcher at the KTH Royal Institute of Technology, Stockholm, Sweden, working with Prof. Dr. Aristides Gionis. Before that, I was a postdoctoral researcher at the Lamarr Institut and the University of Bonn in Bonn, Germany, working with Prof. Dr. Petra Mutzel.
Quick links to find me:
Google Scholar
DBLP
KTH Website
My Erdős number is at most 3 (via Giuseppe F. Italiano → Craig A. Tovey → Paul Erdős).
You can find my CV here.
An Edge-Based Decomposition Framework for Temporal Networks
Lutz Oettershagen, Athanasios L. Konstantinidis, Giuseppe F. Italiano
ACM International Conference on Web Search and Data Mining (WSDM), 2025
arXiv:2309.11843 (code)
Consistent Strong Triadic Closure in Multilayer Networks
Lutz Oettershagen, Athanasios L. Konstantinidis, Fariba Ranjbarh, Giuseppe F. Italiano, 2024
arXiv:2409.08405 (code)
Finding Densest Subgraphs with Edge-Color Constraints
Lutz Oettershagen, Honglian Wang, Aristides Gionis
The ACM Web Conference (WWW), 2024
arXiv:2402.09124 (code)
A Higher-Order Temporal H-Index for Evolving Networks
Lutz Oettershagen, Nils M. Kriege, Petra Mutzel
ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2023
arXiv:2305.16001 (slides) (code)
An Index For Temporal Closeness Computation in Evolving Graphs
Lutz Oettershagen, Petra Mutzel
SIAM International Conference on Data Mining (SDM), 2023
arXiv:2111.10095 (slides) (code)
A Temporal Graphlet Kernel For Classifying Dissemination in Evolving Networks
Lutz Oettershagen, Nils M. Kriege, Claude Jordan, Petra Mutzel
SIAM International Conference on Data Mining (SDM), 2023
arXiv:2209.07332 (slides) (code)
Inferring Tie Strength in Temporal Networks
Lutz Oettershagen, Athanasios L. Konstantinidis, Giuseppe F. Italiano
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML PKDD), 2022
arXiv:2206.11705 (slides) (code)
Temporal Walk Centrality: Ranking Nodes in Evolving Networks
Lutz Oettershagen, Petra Mutzel and Nils Kriege
The ACM Web Conference (WWW), 2022
arXiv:2202.03706 (slides) (code)
Spatio-Temporal Top-k Similarity Search for Trajectories in Graphs
Lutz Oettershagen, Anne Driemel, Petra Mutzel, 2021
arXiv:2009.06778 (code)
Efficient Top-k Temporal Closeness Calculation in Temporal Networks
Lutz Oettershagen, Petra Mutzel
IEEE International Conference on Data Mining (ICDM), 2020
(slides) (code)
Temporal Graph Kernels for Classifying Dissemination Processes
Lutz Oettershagen, Nils Kriege, Christopher Morris, Petra Mutzel
SIAM International Conference on Data Mining (SDM), 2020
arXiv:1911.05496 (code)
On the Enumeration of Bicriteria Temporal Paths
Petra Mutzel, Lutz Oettershagen
Theory and Applications of Models of Computation (TAMC), 2019
arXiv:1812.02507
The Crossing Number of Semi-Pair-Seq-Shellable Drawings of Complete Graphs
Petra Mutzel, Lutz Oettershagen
Canadian Conference on Computational Geometry (CCCG), 2018
arXiv:1805.06780
The Crossing Number of Seq-Shellable Drawings of Complete Graphs
Petra Mutzel, Lutz Oettershagen
International Workshop on Combinatorial Algorithms (IWOCA), 2018
arXiv:1803.07515
Inferring Tie Strength in Temporal Networks
Lutz Oettershagen, Athanasios L. Konstantinidis, Giuseppe F. Italiano
Data Mining and Knowledge Discovery, Springer, 2025.
arXiv:2206.11705
Computing Top-k Temporal Closeness in Temporal Networks
Lutz Oettershagen, Petra Mutzel
Knowledge and Information Systems, Springer, 2022
Classifying Dissemination Processes in Temporal Graphs
Lutz Oettershagen, Nils Kriege, Christopher Morris, Petra Mutzel
Big Data, Mary Ann Liebert, 2020
TGLib: An Open-Source Library for Temporal Graph Analysis
Lutz Oettershagen, Petra Mutzel
ICDM’22 Open Project Forum, 2022
arXiv:2209.12587
A Temporal Graphlet Kernel For Classifying Dissemination in Evolving Networks
Lutz Oettershagen, Nils M. Kriege, Claude Jordan, Petra Mutzel
18th International Workshop on Mining and Learning with Graphs, 2022
arXiv:2209.07332
Best paper award
I am developing and maintaining the open-source library TGLib for analyzing and processing temporal graphs.
Upcoming tutorial on Mining Temporal Networks together with Aristides Gionis and Ilie Sarpe at SDM 2025.
Our tutorial on Mining Temporal Networks together with Aristides Gionis and Ilie Sarpe presented at the WebConf’24.
Please refer to my CV for an overview of my teaching experiences.