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Prof. Dr. Jörn Grahl

Prof. Dr. Jörn Grahl - Professor for Digital Transformation and Analytics

Research focuses

Digital Transformation, Data Science and Business Analytics, Network Analysis, Digital Experimentation, Machine Learning

Curriculum Vitae

  • 03/2009 - 05/2015 Johannes Gutenberg-University (JGU) Mainz „Akademischer Rat auf Zeit“, Department of Information Systems & Business Administration
  • 09/2011 - 12/2011 Center for Complex Network Research (Prof. Albert-László Barabási), Northeastern University, Boston, MA, USA
  • 04/2008 - 03/2009 Software developer
  • 2005 - 04/2008 University of Mannheim Research Assistant, Department of Logistics, Prof. Stefan Minner, Dr. rer. pol. (summa cum laude) Title of dissertation: „Estimation of distribution algorithms in logistics: Analysis, design, and application.”
  • 2004 University of Mannheim, Doctoral student, full scholarship (“LGFG-Stipendium”) Chair of General Mgmt. and Information Systems, Prof. Armin Heinzl
  • 12/2003 University of Mannheim, Diploma in Business Administration, Majors: Business Informatics, Operational Research, Econometrics
  • 2001 University of Passau, Intermediate exam in Business Administration

Selected Publications

  • Grahl, J., Dittmar, D. und Minner, S. (2014) “Metaheuristics for placing strategic safety stock with differentiated service times” Forthcoming – Annals of OR
  • Probst, M., Rothlauf, F., Grahl, J. (2014) „An Implicitly Parallel EDA Based on Restricted Boltzmann Machines“,” Forthcoming in: Proceedings of the 16th annual conference on genetic and Evolutionary computation – ACM GECCO '14. Vancouver, Canada: ACM Press.
  • Schneider, M., Grahl, J., Francas, D. und Vigo, D. (2013) “A problem-adjusted genetic algorithm for flexibility design“ International Journal of Production Economics 141(1), 56-65.
  • Bosman, P.A.N., Grahl, J. und Thierens, D. (2013) “Benchmarking parameter-free AMaLGaM on functions with and without noise” Evolutionary Computation Journal 21(3), 445-469.
  • Kobro-Flatmoen, A., Langdon, G., Wright, C., Block, J., Gilarranz, L. J., Lever, J. J., Rohr, R. P., Fortuna, M. A., Kamfonik, D, Grahl, J., Young, M., Poddar, K., Barrows, N., Sagy, O., Daversa, D. R., Iyer, R. und Gupta, A. (2012) ”NextGenVoices – Results” Science 335(6064), 36-38.
  • Heimbach, I., Grahl, J. und Rothlauf, F. (2012) ”The effects of state-dependent human behavior on the design of a serial line” Journal of Business Economics 82(7-8), 745-762.
  • Grahl, J. und Rothlauf, F. (2012) “Social contagion: Seeding strategies under incomplete information” S. Aral, F. Provost und A. Sundararajan (Hg.): Proceedings of the 4th Workshop on information in networks, New York, N.Y.
  • Grahl, J., Sand, B., Schneider, M. und Schwind, M. (2011) “Publication network analysis of an academic family in information systems” In: A. Heinzl, P.
  • Buxmann, O. Wendt und T. Weitzel (Hg.): Theory-guided modeling and empiricism in information systems research. Heidelberg: Physica-Verlag, 1-13.
  • Bosman, P.A.N. und Grahl, J. (2008) ”Matching inductive search bias and problem structure in continuous Estimation-of-Distribution Algorithms” European Journal of Operational Research 185(3), 1246-1264.
  • Grahl, J., Minner, S., Bosman, P.A.N. (2008) ”Learning structure illuminates black boxes – An introduction to estimation of distribution algorithms” In: P. Siarry und Z. Michalewicz (Hg.): Advances in metaheuristics for hard optimization. Berlin, Heidelberg: Springer (Natural Computing Series), 365-395.
  • Grahl, J., Minner, S., Rothlauf, F. (2008) “Decomposition of dynamic single-product and multi-product lotsizing problems and scalability of EDAs” In: A. Fink und F. Rothlauf (Hg.): Advances in computational intelligence in transport, logistics, supply chain management, Berlin, Heidelberg: Springer (Studies in Computational Intelligence Bd. 144), 231-251.
  • Bosman, P.A.N., Grahl, J. und Rothlauf, F. (2007) ”SDR - A better trigger for adaptive variance scaling in normal EDAs” In: H. Lipson (Hg.): Proceedings of the 9th annual conference on genetic and Evolutionary computation – ACM GECCO '07. New York, N.Y.: ACM Press, 492-499.
  • Grahl, J., Bosman, P.A.N. und Minner, S. (2007) “Convergence phases, variance trajectories, and runtime analysis of continuous EDAs” In: H. Lipson (Hg.): Proceedings of the 9th annual conference on genetic and Evolutionary computation – ACM GECCO '07. New York, N.Y.: ACM Press, 516-522.
  • Grahl, J., Bosman, P.A.N. und Rothlauf, F. (2006) ”The correlation-triggered adaptive variance scaling IDEA” In: M. Cattolico (Hg.): Proceedings of the 8th annual conference on genetic and Evolutionary computation - ACM GECCO '06. New York, N.Y.: ACM Press, 397-404.
  • Grahl, J., Minner, S. und Rothlauf, F. (2005) “Behaviour of UMDAc with truncation selection on monotonous functions” In: Proceedings of the IEEE Congress on Evolutionary computation, IEEE CEC 2005: IEEE, 2553-2559.
  • Grahl, J. und Rothlauf, F. (2004) ”PolyEDA: Combining estimation of distribution algorithms and linear inequality constraints” In: T. Kanade, J. Kittler, J. M. Kleinberg, F. Mattern, J. C. Mitchell, M. Naor und O. Nierstrasz (Hg.): Proceedings of the 6th annual conference on genetic and Evolutionary computation – ACM GECCO '04, Berlin, Heidelberg: Springer