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Kaiserstraße 21
66386 St. Ingbert (Germany)


Dr. Dániel Marx ist tenured Faculty am CISPA. Er promovierte 2005 an der Budapest University of Technology and Economics in Ungarn. Danach hatte er Postdoc- und Gastforscherpositionen in Berlin, Budapest und Tel Aviv. Von 2012 bis 2019 war er am Institute for Computer Science and Control der Hungarian Academy of Sciences, wo er die Gruppe Parameterized Algorithms and Complexity gründete. Förderung erhielt er durch einen ERC Starting und Consolidator Grant. 2019 wurde er leitender Wissenschaftler am Max-Planck-Institut für Informatik in Saarbrücken und wechselte 2020 als tenured Faculty ans CISPA. Dániel ist bekannt für seine theoretischen Arbeiten zu Algorithmen und unteren Grenzwerten für eine Vielzahl an Problemen.

CV: Letzte vier Stationen

Seit 2020
Faculty am CISPA Helmholtz-Zentrum für Informationssicherheit
2019 - 2020
Senior researcher - Max-Planck-Institut für Informatik, Saarbrücken
2012 - 2019
Senior research fellow - Institut für Informatik und Steuerung, Ungarische Akademie der Wissenschaften (MTA SZTAKI), Ungarn
2010 - 2011
Humboldt Research Fellowship for Experienced Researchers - Institut für Informatik, Humboldt-Universität zu Berlin, Germany, Host: Prof. Martin Grohe
Postdoc researcher - Blavatnik School of Computer Science, Tel Aviv University, Israel, Host: Prof. Noga Alon

Veröffentlichungen von Dániel Marx

Jahr 2022

Konferenz / Medium

SODA 2022 - ACM/SIAM Symposium on Discrete AlgorithmsSODA 2022 - ACM/SIAM Symposium on Discrete Algorithms

Jahr 2021

Konferenz / Medium

PODS'21: Proceedings of the 40th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database SystemsJune 202140th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database System

Konferenz / Medium

2nd Symposium on Foundations of Responsible Computing (FORC 2021)2nd Symposium on Foundations of Responsible Computing, FORC 2021, June 9-11, 2021, Virtual Conference

Jahr 2020

Konferenz / Medium

28th Annual European Symposium on Algorithms (ESA 2020)ESA 2020

Konferenz / Medium

28th Annual European Symposium on Algorithms (ESA 2020)ESA 2020

Lehre von Dániel Marx

Winter 2021/22

Parameterized Algorithms

This course is about designing fast algorithms for NP-hard graph theoretic problems, where the running time depends on multiple parameters of the input. For example, while a database may contain a very large amount of data, the size of the database queries is typically extremely small in comparison. The aim would be to obtain algorithms that have a small dependence on the database size, but possibly a larger dependence on the query size. Such an algorithm would be fast when the queries are small.

We will see several algorithmic techniques to design fast algorithms for NP-hard problems in this setting, called Fixed Parameter Tractable (FPT) algorithms, as well as an overview of the lower-bound methods. We will also learn about preprocessing or data-reduction algorithms in this setting, called Kernelization algorithms, which run in polynomial time and reduce a given instance of a NP-hard problem to an equivalent but much smaller instance.


Two hours of lectures every week and two hours of tutorials every other week.

Lectures: Tuesday, 10:15-12:00, online over Zoom

First lecture: October 19, 2021


Basic knowledge of algorithms, graph theory and probability will be assumed.

Date Topic Material Reference (see below) Exercise Due
October 19  L01: Introduction I Slides Video  1, 3.1, 3.2, 3.3    


Reference Textbook

"Parameterized Algorithms" by Cygan et al. (see this for free pdf of the book from the authors).