Chair holder

Research Interests

Data Science
Machine Learning
Automated Algorithm Selection & Configuration
(Automated Machine Learning)
Optimization:
- Continuous (Black-Box) Optimization
- Multi-Objective Optimization
- Vehicle Routing
Benchmarking:
- Exploratory Landscape Analysis
- Visualization
- (Statistical) Performance Assessment
Interpretability of Algorithmic (Search and/or Decisions) Behavior
(Interpretable Machine Learning, Explainable AI)

Networks / Memberships

Coordinating founding member:

Benchmarking Network
COSEAL (Configuration and Selection of Algorithms)

Member and/or Supporter:

ACM SigEVO (Special Interest Group on Genetic and Evolutionary Computation der Association for Computing Machinery)
CLAIRE (Confederation of Laboratories for Artificial Intelligence Research in Europe)
DStatG (German Statistical Society)
ERCIS (European Research Center for Information Systems)
GfKl (Data Science Society)
GI (Computer Science Society)
IEEE CIS Task Force on Benchmarking

Publications

78 Entries

2020

A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithmsBossek, J., Kerschke, P. & Trautmann, H., Mar 2020, In: Applied soft computing : the official journal of the World Federation on Soft Computing (WFSC). 88, 105901Electronic (full-text) versionResearch output: Contribution to journal > Research article
Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson ProblemSeiler, M., Pohl, J., Bossek, J., Kerschke, P. & Trautmann, H., 2020, Parallel Problem Solving from Nature – PPSN XVIElectronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Evolving Sampling Strategies for One-Shot Optimization TasksBossek, J., Doerr, C., Kerschke, P., Neumann, A. & Neumann, F., 2020, Parallel Problem Solving from Nature – PPSN XVIElectronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
One PLOT to Show Them All: Visualization of Efficient Sets in Multi-objective LandscapesSchäpermeier, L., Grimme, C. & Kerschke, P., 2020, 16th International Conference on Parallel Problem Solving from NatureElectronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution

2019

Search Dynamics on Multimodal Multiobjective ProblemsKerschke, P., Wang, H., Preuss, M., Grimme, C., Deutz, A. H., Trautmann, H. & Emmerich, M. T. M., Dec 2019, In: Evolutionary Computation. 27, 4, p. 577–609Electronic (full-text) versionResearch output: Contribution to journal > Research article
OpenML: An R package to connect to the machine learning platform OpenMLCasalicchio, G., Bossek, J., Lang, M., Kirchhoff, D., Kerschke, P., Hofner, B., Seibold, H. & 2 others, Sep 2019, In: Computational statistics. 34, p. 977–991Electronic (full-text) versionResearch output: Contribution to journal > Research article
Evolving diverse TSP instances by means of novel and creative mutation operatorsBossek, J., Kerschke, P., Neumann, A., Wagner, M., Neumann, F. & Trautmann, H., 27 Aug 2019, 15th ACM/SIGEVO Conference on Foundations of Genetic Algorithms - FOGA '19. p. 58-71Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Exploratory Landscape AnalysisKerschke, P. & Preuss, M., 13 Jul 2019, GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion. p. 1137–1155Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Exploring the MLDA benchmark on the nevergrad platformRapin, J., Gallagher, M., Kerschke, P., Preuss, M. & Teytaud, O., 13 Jul 2019, Genetic and Evolutionary Computation Conference (GECCO) CompanionElectronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Making a case for (Hyper-)parameter tuning as benchmark problemsDoerr, C., Dreo, J. & Kerschke, P., 13 Jul 2019, Genetic and Evolutionary Computation Conference (GECCO) CompanionElectronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Single- and multi-objective game-benchmark for evolutionary algorithmsVolz, V., Naujoks, B., Kerschke, P. & Tušar, T., 13 Jul 2019, Genetic and Evolutionary Computation Conference (GECCO)Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Automated Algorithm Selection: Survey and PerspectivesKerschke, P., Hoos, H. H., Neumann, F. & Trautmann, H., Mar 2019, In: Evolutionary Computation. 27, 1, p. 3–45Electronic (full-text) versionResearch output: Contribution to journal > Research article
Automated Algorithm Selection on Continuous Black-Box Problems by Combining Exploratory Landscape Analysis and Machine LearningKerschke, P. & Trautmann, H., Mar 2019, In: Evolutionary Computation. 27, 1, p. 99–127Electronic (full-text) versionResearch output: Contribution to journal > Research article
Comprehensive Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems Using the R-Package FlaccoKerschke, P. & Trautmann, H., 2019, Studies in Classification, Data Analysis, and Knowledge OrganizationElectronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Chapter in book/Anthology/Report
Multimodality in Multi-objective Optimization – More Boon than Bane?Grimme, C., Kerschke, P. & Trautmann, H., 2019, 10th International Conference on Evolutionary Multi-Criterion OptimizationElectronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Sliding to the global optimum: How to benefit from non-global optima in multimodal multi-objective optimizationGrimme, C., Kerschke, P., Emmerich, M. T. M., Preuss, M., Deutz, A. H. & Trautmann, H., 2019, International Global Optimization Workshop (LeGO 2018)Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution

2018

Leveraging TSP Solver Complementarity through Machine LearningKerschke, P., Kotthoff, L., Bossek, J., Hoos, H. H. & Trautmann, H., Dec 2018, In: Evolutionary Computation. 26, 4, p. 597–620Electronic (full-text) versionResearch output: Contribution to journal > Research article
Parameterization of state-of-the-art performance indicators: a robustness study based on inexact TSP solversKerschke, P., Bossek, J. & Trautmann, H., 6 Jul 2018, Genetic and Evolutionary Computation Conference (GECCO) CompanionElectronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution

2017

Exploratory landscape analysis: Advanced Tutorial at GECCO 2017Kerschke, P. & Preuss, M., 15 Jul 2017, Genetic and Evolutionary Computation Conference (GECCO) CompanionElectronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
flaccogui: Exploratory Landscape Analysis for EveryoneHanster, C. & Kerschke, P., 15 Jul 2017, GECCO '17: Proceedings of the Genetic and Evolutionary Computation Conference Companion. p. 1215–1222Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
An Expedition to Multimodal Multi-objective Optimization LandscapesKerschke, P. & Grimme, C., 19 Feb 2017, 9th International Conference on Evolutionary Multi-Criterion OptimizationElectronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution

2016

ASlib: A benchmark library for algorithm selectionBischl, B., Kerschke, P., Kotthoff, L., Lindauer, M., Malitsky, Y., Fréchette, A., Hoos, H. H. & 4 others, 2016, In: Artificial intelligence. 237, p. 41-58Electronic (full-text) versionResearch output: Contribution to journal > Research article
Low-Budget Exploratory Landscape Analysis on Multiple Peaks ModelsKerschke, P., Preuss, M., Wessing, S. & Trautmann, H., 2016, Proceedings of the Genetic and Evolutionary Computation Conference 2016Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Modelling interventions in INGARCH processesLiboschik, T., Kerschke, P., Fokianos, K. & Fried, R., 2016, In: International Journal of Computer Mathematics. 93, 4, p. 640-657Electronic (full-text) versionResearch output: Contribution to journal > Research article
The R-package FLACCO for exploratory landscape analysis with applications to multi-objective optimization problemsKerschke, P. & Trautmann, H., 2016, 2016 IEEE Congress on Evolutionary Computation (CEC). Institute of Electrical and Electronics Engineers (IEEE)Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution

Professional Career

since 2021:
Chair for Big Data Analytics in Transportation,
"Friedrich List" Faculty of Transport and Traffic Sciences, Technische Universität Dresden, Dresden, Germany
since 2019:
Lecturer in the Master Degree Program IT-Management,
WWU Weiterbildung, Münster, Germany
since 2019:
Lecturer in the Certificate Degree Program Data Science,
WWU Weiterbildung, Münster, Germany
2017 - 2021:
Postdoctoral Researcher at the Chair of Data Science: Statistics & Optimization,
Department of Information Systems, University of Münster, Münster, Germany
2017 - 2020:
Lecturer in the Degree Program Business Administration and Taxes,
University of Applied Sciences Münster, Münster, Germany
2013 - 2017:
Research Associate at the Chair of Data Science: Statistics & Optimization,
Department of Information Systems, University of Münster, Münster, Germany

Education

2013 - 2017:
Doctoral Studies (Dr. rer. pol.) at the Department of Information Systems,
School of Business and Economics, University of Münster, Münster, Germany
- Title of PhD Thesis: Automated and Feature-Based Problem Characterization and Algorithm Selection Through Machine Learning
2010 - 2013:
Data Science (M.Sc.), TU Dortmund University, Dortmund, Germany
2011:
Semester Abroad (ERASMUS) at the University of Bergen, Bergen, Norway
2007 - 2010:
Data Analysis and Management (B.Sc.), TU Dortmund University, Dortmund, Germany

Awards and Prizes

07/2025:
Nominated for the Best Paper Award in the ECOM Track of GECCO (2025),
Organizing Committee of GECCO 2025
- Nominated Publication:
  Jonathan Heins, Darrell Whitley and Pascal Kerschke (2025). To Repair or Not to Repair? Investigating the Importance of AB-Cycles for the State-of-the-Art TSP Heuristic EAX. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), ACM.
  Preprint available on arXiv: https://www.arxiv.org/abs/2505.00803
09/2024:
PPSN XVIII Best Paper Award (2024),
University of Applied Sciences Upper Austria and Organizing Committee of PPSN XVIII
- Awarded Publication:
  Lennart Schäpermeier and Pascal Kerschke (2024). Reinvestigating the R2 Indicator: Achieving Pareto Compliance by Integration. International Conference on Parallel Problem Solving from Nature (PPSN XVIII), S. 202 - 216, Springer.
09/2021:
Runner-Up of the FOGA XVI Best Paper Award (2021),
FH Vorarlberg and Organizing Committee of FOGA XVI
- Nominated Publication:
  Jonathan Heins, Jakob Bossek, Janina Pohl, Moritz Seiler, Heike Trautmann and Pascal Kerschke (2021). On the Potential of Normalized TSP Features for Automated Algorithm Selection. 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms (FOGA XVI), pp. 1 - 15, ACM.
12/2018:
Dissertation Prize of the School of Business and Economics,
University of Münster, Münster, Germany
09/2018:
Invited Young Researcher at the 6th Heidelberg Laureate Forum,
Heidelberg Laureate Forum Foundation
09/2016:
PPSN XIV Best Paper Award (2016),
Edinburgh Napier University and Organizing Committee of PPSN XIV
- Awarded Publication:
  Pascal Kerschke, Hao Wang, Mike Preuss, Christian Grimme, André Deutz, Heike Trautmann, Michael Emmerich (2016). Towards Analyzing Multimodality of Continuous Multiobjective Landscapes. International Conference on Parallel Problem Solving from Nature (PPSN XIV), pp. 962 - 972, Springer.

Chair holder

2020

2019

2018

2017

2016

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