Marius Lindauer

Marius Lindauer

 Junior Research Group Lead: Automated Algorithm Design

Postal address:
Institut für Informatik
Albert-Ludwigs-Universität Freiburg
Sekretariat Nebel/GKI
Georges-Köhler-Allee 052
79110 Freiburg, Germany
Building 074, Room 00-015
48.014458, 7.831083 (DD)
+49 761 203-67883

Research Statement

My main research focus lies on the performance tuning of any kind of algorithm (e.g., SAT solvers or machine learning algorithms) using cutting edge techniques from machine learning and optimization. A well-known, but also a tedious, time-consuming and error-prone way to optimize performance (e.g., runtime or prediction loss) is to tune the algorithm’s (hyper-) parameters. To lift the burden on developers and users, I develop methods to automate the process of parameter tuning and algorithm selection for a given problem at hand (e.g., a machine learning dataset, or a set of SAT formulas). To this end, I provide ready-to-use, push-button software that enables users to optimize their software in an easy and efficient way.




  • SMAC v3: automatic tuning of parameter configurations on any kind of algorithms (algorithm configurator)
  • PIMP : analysis of parameter importance for parameterized algorithms
  • AutoFolio: state-of-the-art, robust algorithm selection framework
  • SpyBugC: automatic detection of bugs in configuration spaces
  • SpySMAC: an easy-to-use toolkit (primarily designed for SAT solvers) to optimize parameter configurations and analyze the outcome
  • FlexFolio: automatic selection of well-performing configurations for a problem at hand (algorithm selection; successor of claspfolio)
  • AClib: library of algorithm configuration benchmarks
  • ASlib: library of algorithm selection benchmarks
  • piclasp: a toolkit for performance tuning of the parameters of the state-of-the-art ASP solver clasp
  • Parallel Portfolios: automatic construction of parallel portfolio solvers via algorithm configuration
  • claspfolio: a portfolio based automated parameter configurator for the state-of-the-art ASP solver clasp
  • Aspeed: using cutting-edge combinatorial optimization based on answer set programming to determine a well-performing schedule of algorithms (discontinued)
  • xorro: Sampling of answer sets (discontinued)
  • Centurio: general game playing project in Potsdam (discontinued)



  • 2017: Reinforcement Learning (Lecture)
  • 2017: Machine Learning for Automated Algorithm Design (Lecture)
  • 2017: Advanced Deep Learning (Seminar)
  • 2016: Algorithm Configuration: A Hands-on Tutorial (tutorial at AAAI'16)
  • 2015: Machine Learning and Optimization for Algorithm Design (lecture)
  • 2015: Automated Parameter tuning (practical training)
  • 2014: AI for Automated Algorithm Design (seminar)
  • 2014: Automated Parameter Tuning and Algorithm Configuration (seminar)
  • 2013: Stochastic Optimization (lecture)
  • 2012: AI for Games (part of lecture "Knowledge Representation and Reasoning")
  • 2011: Applied Logic (teaching assistant)
  • 2008+2010+2011: practical class about Answer Set Programming (winter term)
  • 2009: AI for Games (seminar)
  • 2009-2013 : practical class about General Game Playing (each summer term)
  • 2006-2009: tutorial class about Theoretical Informatics

Short CV

  • since 2017: Research group lead at the University of Freiburg
  • 2014-2017: Postdoctoral research fellow at the University of Freiburg
  • 2015: Phd in computer science at the University of Potsdam
  • 2010: Master of Science in computer science at the University of Potsdam
  • 2008: Bachelor of Science in computer science at the University of Potsdam
  • 2005: High school graduation (Abitur) in Berlin