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Research Interests

Anything graphs, e.g.,
  • graph algorithms,
  • graph theory, and
  • graph mining.
Anything at the interface between computer science and the social sciences.
Answering questions about domain data, especially when the data is stubborn.
As a recovering lawyer, I sometimes do legal data science projects, too.

Publications

  • Differentially Describing Groups of Graphs (with Sebastian Dalleiger and Jilles Vreeken).
    Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2022), to appear.
    (15% acceptance rate)
    Preprint
    Given a set of graphs and a partition of these graphs into groups, we introduce Gragra (Graph group analysis) to discover what graphs in one group have in common, how they systematically differ from graphs in other groups, and how multiple groups of graphs are related.

  • Law Smells: Defining and Detecting Problematic Patterns in Legal Drafting (with Janis Beckedorf, Maximilian Böther, Dirk Hartung, and Daniel Martin Katz).
    Preprint
    Also presented as an Extended Abstract at ProLaLa@POPL 2022.
    Building on the computer science concept of code smells, we initiate the systematic study of law smells (i.e., patterns in legal texts that pose threats to the comprehensibility and maintainability of the law), introduce a comprehensive law smell detection toolkit, and demonstrate its utility on twenty-two years of legislation from the United States Code.

  • Simplify Your Law: Using Information Theory to Deduplicate Legal Documents (with Jyotsna Singh and Holger Spamann).
    Proceedings of the IEEE International Conference on Data Mining Workshops (ICDMW 2021), 631–638.
    Preprint | Replication Material
    We introduce the duplicated phrase detection problem for legal texts and propose the Dupex (Duplicated phrase extractor) algorithm to solve it, leveraging the Minimum Description Length principle to identify a set of duplicated phrases that together best compress the input text.

  • Graph Similarity Description: How Are These Graphs Similar? (with Jilles Vreeken).
    Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2021), 185–195.
    (15.4% acceptance rate)
    PDF | Replication Material | Code
    We treat graph similarity assessment as a description problem, rather than as a measurement problem. Having formalized this problem as a model selection task using the Minimum Description Length principle, we propose Momo (Model of models), which solves the problem by breaking it into two parts and introducing efficient algorithms for each.

  • Measuring Law Over Time: A Network Analytical Framework with an Application to Statutes and Regulations in the United States and Germany (with Janis Beckedorf, Michael Bommarito, Dirk Hartung, and Daniel Martin Katz).
    Frontiers in Physics 9 (2021), 269:1–269:31.
    PDF | Appendix
    Also presented as an Extended Abstract at Complex Networks 2021.
    We present a comprehensive framework for analyzing legal documents as multi-dimensional, dynamic document networks and demonstrate its utility by applying it to an original dataset of statutes and regulations from two different countries, the United States and Germany, spanning more than twenty years (1998–2019).

  • A Breezing Proof of the KMW Bound (with Christoph Lenzen).
    Proceedings of the Fourth SIAM Symposium on Simplicity in Algorithms (SOSA 2021), 184–195.
    (29.4% acceptance rate)
    PDF (Conference Version) | PDF (Extended Version)
    We give a simple and (in the extended version) fully self-contained proof of the KMW lower bound, proving a hardness result for several fundamental graph problems in the LOCAL model of distributed computing.

  • Complex Societies and the Growth of the Law (with Janis Beckedorf, Dirk Hartung, and Daniel Martin Katz).
    Sci. Rep. 10 (2020), 18737:1–18737:14.
    PDF | Appendix
    Also presented as a non-archival paper at NLLP@KDD 2020.
    We examine 25 years of statutory legislation in the United States and Germany through the lens of network science, finding that the main driver behind the growth of the law in both jurisdictions is the expansion of the welfare state, backed by an expansion of the tax state.

  • Das Wertpapierhandelsgesetz (1994–2019): Eine quantitative juristische Studie (with Andreas Martin Fleckner).
    Festschrift 25 Jahre WpHG (2019), 53–85.
    PDF | Appendix
    A legal data science project investigating the evolution of Germany's Securities Trading Act over the first 25 years of its lifetime.

  • Juristische Netzwerkforschung: Modellierung, Quantifizierung und Visualisierung relationaler Daten im Recht.
    XVIII, 376 p. Tübingen: Mohr Siebeck (2019).
    PDF | Appendix
    Awards: Otto Hahn Medal of the Max Planck Society (2020), Bucerius Law School Dissertation Award (2018)
    My legal dissertation. I introduce network science to the German legal discourse and explore what "legal network science" could mean. This is how I got into graphs.

  • Quantitative Rechtswissenschaft: Sammlung, Analyse und Kommunikation juristischer Daten (with Andreas Martin Fleckner).
    Juristenzeitung 73 (2018), 379–389.
    PDF | Appendix
    We explain what legal data analysis is and discuss how German legal research could profit from it.

Teaching

  • 2021 (Winter Semester)
    Lecturer, Ideas of Informatics (Saarland University, with Kurt Mehlhorn)
  • 2020 (Winter Semester)
    Lecturer, Ideas of Informatics (Saarland University, with Kurt Mehlhorn)
    Teaching Assistant, Theory of Distributed Systems (Saarland University)
  • 2019–2022 (Various Trimesters)
    Lecturer, Introduction to Informatics (Bucerius Law School)
  • 2018–2021 (Summer Semesters)
    Lecturer, Programming for Lawyers (University of Heidelberg, with Janis Beckedorf and Philipp Sahrmann)
  • 2018 (Winter Semester)
    Tutor, Data Networks (Saarland University)
  • 2017 (Winter Semester)
    Tutor, Introduction to Informatics (LMU Munich)
  • 2017–2019 (Various Trimesters)
    Lecturer, Introduction to Programming (Bucerius Law School, with Philipp Sahrmann)

Education

  • 2020–Present
    Ph.D. Student in Computer Science (MPI for Informatics)
  • 2020
    M.Sc. in Computer Science (Saarland University)
  • 2018
    B.Sc. in Computer Science (LMU Munich)
  • 2018
    Ph.D. in Law (Bucerius Law School – Thesis Written at the MPI for Tax Law and Public Finance)
  • 2015
    First Legal State Exam (HansOLG)