Hochschule Karlsruhe Hochschule Karlsruhe - University of Applied Sciences
Hochschule Karlsruhe Hochschule Karlsruhe - University of Applied Sciences
Die HKA

Prof. Dr. Bernd Scheuermann

Fakultät für Wirtschaftswissenschaften
Professor für Wirtschaftsinformatik

Institut für Angewandte Forschung
Professor für Wirtschaftsinformatik

Vita

seit 09/2014
Professor für Wirtschaftsinformatik, Hochschule Karlsruhe 

06/2006-08/2014
Senior Researcher und Projektleiter, SAP SE

05/2012-08/2014
Lehrbeauftragter, Duale Hochschule Baden-Württemberg, DHBW Karlsruhe

10/2011-02/2012
Lehrbeauftragter, Hochschule Karlsruhe

02/2001-04/2004
Mehrfache Aufenthalte als Research Fellow, University of New South Wales, Sydney, Australien

10/2003-12/2005
Promotion zum Dr. rer. pol., Karlsruher Institut für Technologie (KIT)

08/1999-03/2006
Wissenschaftlicher Mitarbeiter am Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB), Karlsruher Institut für Technologie (KIT)

09/1998-04/1999
Auslandssemester, University of Newcastle, Australien

10/1993-07/1999
Studium Wirtschaftsingenieurwesen, Karlsruher Institut für Technologie (KIT)

 

Lehre

  • Enterprise Resource Planning
  • Integrierte Standardsoftware
  • Bionics

Forschung

Forschungsgebiete:

  • Enterprise Systems
  • Access Control Management
  • Fraud-Detection in IT Systems
  • Bio-inspired Optimization Algorithms
  • Parallel Computing
  • Dynamically Reconfigurable Architectures

Forschungsprojekte:

Laufende Drittmittel-Projekte:

  • Dynamische Optimierung: Industrieprojekt mit SIVIS GmbH Karlsruhe
  • KOEX: Kollaboratives Machine Learning zur Erkennung von Fraud und Risiken in ERP-Systemen. Gefördert durch das BMBF im Programm KMU-Innovativ.

Abgeschlossene Projekte:

  • AutoBer: Automatisierter Aufbau von sicheren und verständlichen Berechtigungskonzepten für ERP-Systeme. Gefördert durch das BMBF im Programm KMU-Innovativ.
  • XtreemOS: Enabling Linux for the Grid. EU-funded project.
  • ADVANCE: Asynchronous and Dynamic Virtualisation through performance ANalysis to support Concurrency Engineering. EU-funded project.
  • eBadge: Development of Novel ICT tools for integrated Balancing Market Enabling Aggregated Demand Response and Distributed Generation Capacity. EU-funded project.
  • SAP IoT Enablement. SAP project.
  • Big Data in Bio-inspired Optimization Using SAP HANA. Funded by HPI Future SOC Lab.
  • OPTREK: Optimierung auf dynamisch rekonfigurierbaren Rechnerarchitekturen. Gefördert durch DFG.
  • VIROR: Virtuelle Hochschule Oberrhein

Veröffentlichungen

  • O. Diessel, H. ElGindy, M. Middendorf, H. Schmeck, and B. Scheuermann(*). Dynamic scheduling on partially reconfigurable FPGAs. IEE Proceedings - Computers and Digital Techniques. Special issue on reconfigurable systems, 147(3):181–188, 2000. (*) published as “B. Schmidt”
  • H. ElGindy, M. Middendorf, H. Schmeck, and B. Scheuermann(*). Task rearrangement on partially reconfigurable FPGAs with restricted buffer. In Field-Programmable Logic and Applications. Proceedings of the 10th International Conference, FPL 2000, volume 1896 of LNCS, pages 379–388. Springer-Verlag, 2000. (*) published as “B. Schmidt”
  • H. ElGindy, M. Middendorf, H. Schmeck, and B. Scheuermann(*). An evolutionary approach to dynamic task scheduling on FPGAs with restricted buffer. Journal of Parallel and Distributed Computing, 62(9):1407–1420, 2002. (*) published as “B. Schmidt”
  • O. Diessel, H. ElGindy, M. Middendorf, M. Guntsch, B. Scheuermann, H. Schmeck,  and K. So. Population based ant colony optimization on FPGA. In Proceedings of the IEEE International Conference on Field-Programmable Technology (FPT), pages 125–132, IEEE Computer Society, 2002.
  • B. Scheuermann, K. So, M. Guntsch, M. Middendorf, O. Diessel, H. ElGindy, and H. Schmeck. FPGA implementation of population-based ant colony optimization. In Proceedings of the Dagstuhl Seminar (03301) Dynamically Reconfigurable Architectures, URL: www.dagstuhl.de/03301/Materials, 2003.
  • B. Scheuermann, M. Guntsch, M. Middendorf, and H. Schmeck. Time-scattered heuristic for the hardware implementation of population-based ACO. In Ant colony Optimization and Swarm Intelligence. Proceedings of the ANTS 2004 conference, volume 3172 of LNCS, pages 250–261, Springer-Verlag, 2004.
  • B. Scheuermann, K. So, M. Guntsch, M. Middendorf, O. Diessel, H. ElGindy, and H. Schmeck. FPGA implementation of population-based ant colony optimization. Applied Soft Computing, 4:303–322, 2004.
  • B. Scheuermann and M. Middendorf. Counter-based ant colony optimization as a hardware-oriented meta-heuristic. In Applications of Evolutionary Computing. Proceedings of EvoWorkshops 2005, volume 3449 of LNCS, pages 235–244, Springer-Verlag, 2005.
  • B. Scheuermann. Ant Colony Optimization on Runtime Reconfigurable Architectures. Dissertation. Universität Karlsruhe (TH), Institut für Angewandte Informatik und Formale Beschreibungsverfahren, 2005.
  • B. Scheuermann, S. Janson, M. Middendorf. Hardware-oriented ant colony optimization. Journal of Systems Architecture, 53(7): 386-402, 2007.
  • E. Y. Yang, B. Matthews, A. D. Lakhani, Y. Jégou, C. Morin, O. David Sánchez, C. Franke, P. Robinson, A. Hohl, B. Scheuermann, D. Vladusic, H. Yu, A. Qin, R. Lee, E. Focht, M. Coppola. Virtual Organization Management in XtreemOS: an Overview. CoreGRID 2007: 73-82, 2007.
  • C. Franke, A. Hohl, P. Robinson, B. Scheuermann. On Business Grid Demands and Approaches. Workshop Series on Grid Economics and Business Models GECON 2007: 124-135, 2007.
  • B. Scheuermann. Hybrid Database System using Runtime Reconfigurable Hardware. US Patent grant number: 7,974,967, publication number: US-2009-0259644, Chinese      Patent  Application 200910134892.3, India: 865/CHE/2009, European: 09005306.7
  • M. Middendorf and B. Scheuermann. Perspectives of extending runtime reconfigurable computing to the enterprise application domain. In Prof. Of the IEEE International Conference on Industrial Informatics, IEEE, 2010.
  • B. Scheuermann. Design of a reconfigurable hybrid database system. Proc. of the International IEEE Symposium on Field-Programmable Custom Computing Machines (FCCM 2010), pages 247-250, IEEE Computer Society, 2010.
  • R. Talyansky, B. Scheuermann, B. Kolbeck and J. Stender. Trace-Driven Performance Evaluation of Distributed File Systems under Enterprise Application Workload. Technical Report. SAP SE and Zuse Institut Berling, arXiv:1001.2931, 2010.
  • W. Cheng, B. Scheuermann, and M. Middendorf. Quick-ACO: Accelerating ant decisions and pheromone updates in ACO. In Proc. of the 11th European Conference on Evolutionary Computation in Combinatorial Optimisation (EvoCOP), LNCS 6622, 238-249, Springer, 2011.
  • B. Scheuermann, B. T. Iraneus, K. Hammond, A. Shafarenko, C. Jesshope, H. Hertlein, V. Wieser, H. Schöner, B. Moser, and R. Kirner. Concurrent Software Engineering on Multicore Systems Supported by Statistical Performance Analysis. Software Compentece Center Hagenberg, Technical Report , 2011.
  • B. Scheuermann. On Applying Runtime Reconfigurable Architectures to the Domain of Enterprise Computing. SAP Community Network, SDN Article DOC-22684, 2012.
  • C. Grelck, K. Hammond, H. Hertlein, P. Hölzenspies, C. Jesshope, R. Kirner, B. Scheuermann, A. Shafarenko, I. te Boekhorst, and V. Wieser. Engineering Concurrent Software Guided by Statistical Performance Analysis. Applications, Tools and Techniques on the Road to Exascale Computing, pages 385-396, IOS Press, 2012.
  • W. Cheng, F. Penczek, C. Grelck, R. Kirner, B. Scheuermann. A.Shafarenko: Modeling streams-based variants of ant colony optimisation for parallel systems — A Dataflow-driven Approach Using S-Net, in Proc. of the 7th International Conference on High-Performance and Embedded Architectures and Compilers (HiPEAC), 2012.
  • B. Scheuermann. On Multicore Software Engineering in the Enterprise Computing Domain. SAP Community Network, SDN Article DOC-31690, 2012.
  • F. Penczek, W. Cheng, C. Grelck, R. Kirner, B. Scheuermann, A. Shafarenko. A Data-Flow Based Coordination Approach to Concurrent Software Engineering. Proc. of Data-Flow Execution Models for Extreme Scale Computing (DFM 2012), IEEE, 2012.
  • B. Scheuermann, E. Weinknecht. On the Potential of Big Data Boosting Bio-inspired Optimization. A Study Using SAP HANA. In C. Meinel, A. Polze, G. Oswald, R. Strotmann, U. Seibold, B. Schulzki. Proc. of the HPI Future SOC Lab Day 2015. Hasso-Plattner-Institut (HPI), 2015.
  • W. Cheng, J. Jordan, B. Scheuermann, and J. Weber. Towards Predictive Analytics for Dynamic Evolutionary Optimization. In C. Meinel, A. Polze, G. Oswald, R. Strotmann, U. Seibold, B. Schulzki. Proc. of the HPI Future SOC Lab Day 2016. Hasso-Plattner-Institut (HPI), 2016.
  • W. Cheng, J. Jordan, B. Scheuermann. Advanced Dynamic Evolutionary Computing Using SAP HANA. In C. Meinel, A. Polze, G. Oswald, R. Strotmann, U. Seibold, B. Schulzki. Proc. of the HPI Future SOC Lab Day 2016. Hasso-Plattner-Institut (HPI), 2016.
  • J. Jordan, W. Cheng, B. Scheuermann. Advancing Dynamic Evolutionary Optimization Using In-Memory Database Technology. In G. Squillero, K. Sim: Applications of Evolutionary Computation, Proc. of the 20th European Conference on EvoApplications 2017, Part 2, Lecture Notes in Computer Science, vol. 10200, pp. 156-172, Springer Verlag, 2017.
  • S. Anderer, M. Halbich, B. Scheuermann, S. Mostaghim. Towards Real-Time Fleet-Event-Handling for the Dynamic Vehicle Routing Problem. In C.  Sabourin, J.  Merelo, U. O'Reilly, K. Madani, K. Warwick. Proc. of the 9th International Joint Conference on Computational Intelligence – IJCCI, pp. 35-44, 2017.
  • S. Anderer, T.-H. Vu, B. Scheuermann, S. Mostaghim. Meta Heuristics for Dynamic Machine Scheduling — A Review of Research Efforts and Industrial Requirements. Proc. of the 10th International Joint Conference on Computational Intelligence – IJCCI, 2018.
  • C. Drumm, M. Knigge, B. Scheuermann, S. Weidner. Einstieg in SAP ERP. Geschäftsprozesse, Komponenten, Zusammenhänge. Erklärt am Beispielunternehmen Global Bike. Rheinwerk-Verlag, 2019.
  • S. Anderer, D. Kreppein, B. Scheuermann, S. Mostaghim. The addRole-EA - A New Evolutionary Algorithm for the Role Mining Problem. In J. Merelo, J. Garibaldi, C. Wagner, T. Bäck, K. Madani, K. Warwick. Proceedings of the 12th International Joint Conference on Computational Intelligence (IJCCI), pp. 155-166, 2020.
  • S. Anderer, B. Scheuermann, S. Mostaghim, P. Bauerle, M. Beil. RMPlib: A Library of Benchmarks for the Role Mining Problem. In J. Lobo, R. Di Pietro, O. Chowdhury, H.  Hu: Proceedings of The ACM Symposium on Access Control Models and Technologies (SACMAT 2021), pp. 3-13, Association for Computing Machinery (ACM), 2021.
  • S. Anderer, T. Kempter, B. Scheuermann, S. Mostaghim. The Dynamic Role Mining Problem – Role Mining in Dynamically Changing Business Environments. Proceedings of the 13th International Joint Conference on Computational Intelligence (IJCCI), pp. 37-48, 2021.
  • S. Anderer, B. Scheuermann, S. Mostaghim. Evolutionary Optimization of Roles for Access Control in Enterprise Resource Planning Systems. In Computational Intelligence. Springer Nature, to appear, 2022.
  • S. Anderer, F. Schrader, B. Scheuermann, S. Mostaghim. Evolutionary Algorithms for the Constrained Two-Level Role Mining Problem. Proc. of the 22nd European Conference on Evolutionary Computation in Combinatorial Optimisation (EvoCOP), In: L. Pérez Cáceres and S. Verel. Evolutionary Computation in Combinatorial Optimization. Springer, pp. 79-94, 2022.
  • S. Anderer, T. Kempter, B. Scheuermann, S. Mostaghim. Dynamic Optimization of Role Concepts for Role Based Access Control using Evolutionary Algorithms. In Computational Intelligence. Springer Nature, submitted 2022.
  • E. W. Lima Silva, H. A. Dantas do Nascimento, J. P. Felix, H. Longo, B. Scheuermann. A Systematic Literature Review of Solution-Space Visualization Approaches in the Context of Optimization Problems. IV2022 - 26th International Conference Information Visualisation, IEEE, pp. 48-53, 2022. doi: 10.1109/IV56949.2022.00017
  • S. Anderer, A. Sahin, B. Scheuermann and S. Mostaghim. On Using Authorization Traces to Support Role Mining with Evolutionary Algorithms. Proceedings of the 14th International Joint Conference on Computational Intelligence (IJCCI), pp. 121–132, 2022.
  • J. Schnepf, P. Vetter, T. Temel, B. Scheuermann and L. Schmidt-Thieme. On the Potential of Using ERP Business and System Data for Fraud Detection. 2022 IEEE International Conference on Big Data (Big Data), Osaka, Japan, IEEE, 2022, pp. 3081-3091, doi: 10.1109/BigData55660.2022.10020785.
  • C. Drumm, B. Scheuermann, S. Weidner. Einstieg in SAP S/4HANA. Geschäftsprozesse, Anwendungen, Zusammenhänge – Erklärt am Beispielunternehmen Global Bike. Rheinwerk-Verlag, 2022.

Interessen

Lehrbücher:

  • Einstieg in SAP S/4HANA
    Geschäftsprozesse, Anwendungen, Zusammenhänge – Erklärt am Beispielunternehmen Global Bike
    von Christian Drumm, Bernd Scheuermann, Stefan Weidner
    Rheinwerk-Verlag, November 2022
  • Einstieg in SAP ERP
    Geschäftsprozesse, Komponenten, Zusammenhänge – Erklärt am Beispielunternehmen Global Bike
    von Christian Drumm, Marlene Knigge, Bernd Scheuermann, Stefan Weidner
    Rheinwerk-Verlag, 2019

Kontakt

Prof. Dr. Bernd Scheuermann
bernd.scheuermannspam prevention@h-ka.de


Fakultät für Wirtschaftswissenschaften
Professor für Wirtschaftsinformatik
Tel.: +49 721 925-1963

Sprechzeiten :
Nach vorheriger Terminvereinbarung per E-Mail.

Raum K-101C


Institut für Angewandte Forschung
Professor für Wirtschaftsinformatik
Tel.: +49 721 925 1963

Sprechzeiten :
Nach vorheriger Terminvereinbarung per E-Mail.

Raum K101c