Chair holder

Professor
NameMr Prof. Dr. rer. pol. Pascal Kerschke
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Chair of Big Data Analytics in Transportation
Chair of Big Data Analytics in Transportation
Visiting address:
Bürozentrum Falkenbrunnen (FAL), Room 005a (Ground Floor) Würzburger Str. 35
01187 Dresden
Office hours:
by appointment
- 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)
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)
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DStatG (German Statistical Society)
- ERCIS (European Research Center for Information Systems)
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GfKl (Data Science Society)
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GI (Computer Science Society)
- IEEE CIS Task Force on Benchmarking
2025
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Clearing the Combinatorial Fog: Tracing the Hidden Paths of TSP Heuristics , 27 Jun 2025, Proceedings of the 18th ACM/SIGEVO Conference on Foundations of Genetic AlgorithmsResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
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To Repair or Not to Repair? Investigating the Importance of AB-Cycles for the State-of-the-Art TSP Heuristic EAX , 19 Mar 2025, Proceedings of the Genetic and Evolutionary Computation ConferenceResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
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Deep-ELA: Deep Exploratory Landscape Analysis with Self-Supervised Pretrained Transformers for Single- and Multi-Objective Continuous Optimization Problems , 2025, In: Evolutionary Computation. p. 1-27, 27 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Efficient Flat Yard Shunting via Instance-Aware Optimization , 2025Research output: Contribution to conferences > Presentation slides
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Size matters: Adapting HEROS to ensure usability in large flat yards , 2025Research output: Contribution to conferences > Poster
2024
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Physical Layer Security: Learning-Aided Attack Detection based on 5G NR SRS , 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
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Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal Optimization , 11 Sep 2024, In: IEEE transactions on evolutionary computation : a publication of the IEEE Neural Networks CouncilElectronic (full-text) versionResearch output: Contribution to journal > Research article
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Dancing to the State of the Art?: How Candidate Lists Influence LKH for Solving the Traveling Salesperson Problem , 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
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Reinvestigating the R2 Indicator: Achieving Pareto Compliance by Integration , 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
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Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization , 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
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Enhancing Emergency Response Efficiency via Deep Reinforcement Learning: A Novel Model for Dynamic Dispatching , 2024Research output: Contribution to conferences > Presentation slides
2023
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Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape Features , 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
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Evaluation of Algorithms from the Nevergrad Toolbox on the Strictly Box-Constrained SBOX-COST Benchmarking Suite , 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
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GECCO 2023 Tutorial: Exploratory Landscape Analysis , 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
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Tools for Landscape Analysis of Optimisation Problems in Procedural Content Generation for Games , 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
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A study on the effects of normalized TSP features for automated algorithm selection , 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
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Peak-A-Boo! Generating Multi-objective Multiple Peaks Benchmark Problems with Precise Pareto Sets , 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
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Mixture of Decision Trees for Interpretable Machine Learning , 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
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Plotting Impossible? Surveying Visualization Methods for Continuous Multi-Objective Benchmark Problems , Dec 2022, In: IEEE transactions on evolutionary computation : a publication of the IEEE Neural Networks Council. 26, 6, p. 1306-1320, 15 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Process-Oriented Stream Classification Pipeline: A Literature Review , 9 Sep 2022, In: Applied sciences. 12, 18, 9094Electronic (full-text) versionResearch output: Contribution to journal > Review article
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The objective that freed me: a multi-objective local search approach for continuous single-objective optimization , 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
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A collection of deep learning-based feature-free approaches for characterizing single-objective continuous fitness landscapes , 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
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MOLE: Digging Tunnels Through Multimodal Multi-objective Landscapes , 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
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Estimation of component reliability from superposed renewal processes by means of latent variables , Mar 2022, In: Computational statistics. 37, 1, p. 355–379, 25 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Automated Algorithm Selection in Single-Objective Continuous Optimization: A Comparative Study of Deep Learning and Landscape Analysis Methods , 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
- 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
- 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
- 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
- Nominated Publication:
- 09/2024:
PPSN XVIII Best Paper Award (2024),
University of Applied Sciences Upper Austria and Organizing Committee of PPSN XVIII -
09/2021:
Runner-Up of the FOGA XVI Best Paper Award (2021),
FH Vorarlberg and Organizing Committee of FOGA XVI - 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