I am a postdoctoral researcher at the KTH Royal Institute of Technology, Stockholm, Sweden, working with Prof. Dr. Aristides Gionis. Until the end of March 2023, I was a postdoctoral researcher at the Lamarr Institut and the University of Bonn, Bonn, Germany, working with Prof. Dr. Petra Mutzel.
My primary research area is graph data mining, algorithms for data analysis, 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 temporal networks, i.e., graph structures that change their topology over time. Prominent examples are dynamic social networks in which participants build and end friendships over time, communication networks like email networks in which emails correspond to instantaneous connections between users, or human contact networks modeling face-to-face contacts. In my research, I design and analyze methods for obtaining new knowledge from temporal networks.
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.
Our tutorial on Mining Temporal Networks together with Aristides Gionis and Ilie Sarpe got accepted at the WebConf’24.
Finding Densest Subgraphs with Edge-Color Constraints
Lutz Oettershagen, Honglian Wang, Aristides Gionis
The ACM Web Conference (WWW), 2024
arXiv:2402.09124 (code)
Temporal Network Core Decomposition and Community Search
Lutz Oettershagen, Athanasios L. Konstantinidis, Giuseppe F. Italiano, 2023
arXiv:2309.11843 (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
Under review.
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.
Please refer to my CV for an overview of my teaching experiences.