Chair holder

• 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)

• 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 

• 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

• 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.