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

61 Entries

2024

Physical Layer Security: Learning-Aided Attack Detection based on 5G NR SRSNinnemann, J., Rauschert, F., Schwarzbach, P., Kerschke, P. & Michler, O., 30 Sep 2024, 2024 IEEE Conference on Communications and Network Security (CNS). p. 1-6Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Dancing to the State of the Art?: How Candidate Lists Influence LKH for Solving the Traveling Salesperson ProblemHeins, J., Schäpermeier, L., Kerschke, P. & Whitley, D., 7 Sep 2024, Parallel Problem Solving from Nature – PPSN XVIII: 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14–18, 2024, Proceedings, Part I. Affenzeller, M., Winkler, S. M., Kononova, A. V., Bäck, T., Trautmann, H., Tušar, T. & Machado, P. (eds.).p. 100-115, 16 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Reinvestigating the R2 Indicator: Achieving Pareto Compliance by IntegrationSchäpermeier, L. & Kerschke, P., 7 Sep 2024, Parallel Problem Solving from Nature – PPSN XVIII: 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14–18, 2024, Proceedings, Part IV. Affenzeller, M., Winkler, S. M., Kononova, A. V., Bäck, T., Trautmann, H., Tušar, T. & Machado, P. (eds.).p. 202-216, 15 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box OptimizationDietrich, K., Vermetten, D., Doerr, C. & Kerschke, P., 14 Jul 2024, Proceedings of the Genetic and Evolutionary Computation Conference. Association for Computing Machinery (ACM), p. 1007 - 1016, 10 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution

2023

Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape FeaturesPrager, R. P., Dietrich, K., Schneider, L., Schäpermeier, L., Bischl, B., Kerschke, P., Trautmann, H. & 1 others, 30 Aug 2023, FOGA '23: Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms. p. 129-139, 11 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Evaluation of Algorithms from the Nevergrad Toolbox on the Strictly Box-Constrained SBOX-COST Benchmarking SuiteDietrich, K. & Kerschke, P., 15 Jul 2023, GECCO 2023 Companion - Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion. 4 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
GECCO 2023 Tutorial: Exploratory Landscape AnalysisKerschke, P. & Preuss, M., 15 Jul 2023, GECCO '23 Companion: Proceedings of the Companion Conference on Genetic and Evolutionary Computation. p. 990–1007, 18 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Tools for Landscape Analysis of Optimisation Problems in Procedural Content Generation for GamesVolz, V., Naujoks, B., Kerschke, P. & Tušar, T., Mar 2023, In: Applied soft computing : the official journal of the World Federation on Soft Computing (WFSC). 136, 110121Electronic (full-text) versionResearch output: Contribution to journal > Research article
A study on the effects of normalized TSP features for automated algorithm selectionHeins, J., Bossek, J., Pohl, J., Seiler, M., Trautmann, H. & Kerschke, P., Jan 2023, In: Theoretical computer science : the journal of the EATCS. 940, B, p. 123-145, 23 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
Peak-A-Boo! Generating Multi-objective Multiple Peaks Benchmark Problems with Precise Pareto SetsSchäpermeier, L., Kerschke, P., Grimme, C. & Trautmann, H., 2023, Evolutionary Multi-Criterion Optimization - 12th International Conference, EMO 2023, Proceedings. Emmerich, M., Deutz, A., Wang, H., Kononova, A. V., Naujoks, B., Li, K., Miettinen, K. & Yevseyeva, I. (eds.).14 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution

2022

Mixture of Decision Trees for Interpretable Machine LearningBrüggenjürgen, S., Schaaf, N., Kerschke, P. & Huber, M. F., Dec 2022, Proceedings - 21st IEEE International Conference on Machine Learning and Applications, ICMLA 2022. Wani, M. A., Kantardzic, M., Palade, V., Neagu, D., Yang, L. & Chan, K. (eds.).p. 1175-1182, 8 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Plotting Impossible? Surveying Visualization Methods for Continuous Multi-Objective Benchmark ProblemsSchäpermeier, L., Grimme, C. & Kerschke, P., Dec 2022, In: Congress on Evolutionary Computation (CEC). 26, 6, p. 1306-1320, 15 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
Process-Oriented Stream Classification Pipeline: A Literature ReviewClever, L., Pohl, J. S., Bossek, J., Kerschke, P. & Trautmann, H., 9 Sep 2022, In: Applied sciences. 12, 18, 9094Electronic (full-text) versionResearch output: Contribution to journal > Research article
The objective that freed me: a multi-objective local search approach for continuous single-objective optimizationAspar, P., Steinhoff, V., Schäpermeier, L., Kerschke, P., Trautmann, H. & Grimme, C., 5 Sep 2022, In: Natural computing : an innovative journal bridging biosciences and computer sciences ; an international journal. 22, 2, p. 271 - 285, 15 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
A collection of deep learning-based feature-free approaches for characterizing single-objective continuous fitness landscapesSeiler, M. V., Prager, R. P., Kerschke, P. & Trautmann, H., 8 Jul 2022, GECCO 2022 - Proceedings of the 2022 Genetic and Evolutionary Computation Conference. p. 657-665, 9 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
MOLE: Digging Tunnels Through Multimodal Multi-objective LandscapesSchäpermeier, L., Grimme, C. & Kerschke, P., 8 Jul 2022, GECCO 2022 - Proceedings of the 2022 Genetic and Evolutionary Computation Conference. p. 592-600, 9 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Estimation of component reliability from superposed renewal processes by means of latent variablesRodrigues, A., Kerschke, P., Pereira, C. A. D. B., Trautmann, H., Wagner, C., Hellingrath, B. & Polpo, A., Mar 2022, In: Computational statistics. 37, 1, p. 355–379, 25 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
Automated Algorithm Selection in Single-Objective Continuous Optimization: A Comparative Study of Deep Learning and Landscape Analysis MethodsPrager, R. P., Seiler, M. V., Trautmann, H. & Kerschke, P., 2022, Parallel Problem Solving from Nature – PPSN XVII - 17th International Conference, PPSN 2022, Proceedings. Rudolph, G., Kononova, A. V., Aguirre, H., Kerschke, P., Ochoa, G. & Tušar, T. (eds.).p. 3-17, 15 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization ProblemsHeins, J., Rook, J., Schäpermeier, L., Kerschke, P., Bossek, J. & Trautmann, H., 2022, 17th International Conference on Parallel Problem Solving from Nature. 15 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
HPO × ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape AnalysisSchneider, L., Schäpermeier, L., Prager, R. P., Bischl, B., Trautmann, H. & Kerschke, P., 2022, Parallel Problem Solving from Nature – PPSN XVII - 17th International Conference, PPSN 2022, Proceedings. Rudolph, G., Kononova, A. V., Aguirre, H., Kerschke, P., Ochoa, G. & Tušar, T. (eds.).p. 575-589, 15 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Parallel Problem Solving from Nature – PPSN XVII: 17th International Conference, PPSN 2022, Dortmund, Germany, September 10–14, 2022, Proceedings, Part IRudolph, G., Kononova, A. V., Aguirre, H., Kerschke, P., Ochoa, G. & Tušar, T., 2022, Springer, ChamElectronic (full-text) versionResearch output: Book/Report/Anthology > Monograph

2021

Towards Feature-Free Automated Algorithm Selection for Single-Objective Continuous Black-Box OptimizationPrager, R. P., Seiler, M. V., Trautmann, H. & Kerschke, P., 5 Dec 2021, 2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - ProceedingsElectronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimizationGrimme, C., Kerschke, P., Aspar, P., Trautmann, H., Preuss, M., Deutz, A. H., Wang, H. & 1 others, Dec 2021, In: Computers and Operations Research. 136, 105489Electronic (full-text) versionResearch output: Contribution to journal > Research article
On the potential of normalized TSP features for automated algorithm selectionHeins, J., Bossek, J., Pohl, J., Seiler, M., Trautmann, H. & Kerschke, P., 6 Sep 2021, FOGA 2021 - Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic AlgorithmsElectronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Lifting the Multimodality-Fog in Continuous Multi-objective OptimizationKerschke, P. & Grimme, C., 2021, Natural Computing Series. p. 89-111, 23 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Chapter in book/Anthology/Report

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

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

2024

2023

2022

2021

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