Dominik Fischer, M.Sc.

Post Doctoral fellow

Dr. Dominik Fischer

Faculty of Computer Science
Chair of Computational Intelligence
Universitätsplatz 2, 39106 Magdeburg, G29-020


"All models are wrong, some are useful! Insight is the goal, not numbers! " - C.B.


Research Interests

  • Evolutionary Algorithms, Complex Systems and Network Theory
  • Collective Behavior, Intelligent Systems and Swarm Intelligence
  • Managerial, Organizational and Social Cognition



  • 06/2017 – 09/2020: Doctoral Candidate, title of the dissertation: “Essays on Reliability of Intelligent Systems, Cognition in Organization Theory and Digitalization in Financial Accounting”
  • 03/2018 – 04/2018: Research fellow at the University of Wisconsin, Madison, USA.
  • 04/2015 – 05/2017: Otto-von-Guerike-University of Magdeburg, Master of Science in Data- and Knowledge-Engineering.
  • 10/2011 – 03/2015: Deggendorf Institute of Technology, Bachelor of Science in Information Systems.
  • 08/2008 – 08/2011: Software developer at idowapro, Straubing and Landshut idowapro is an internet agency of the newspaper group “Straubinger Tagblatt / Landshuter Zeitung”
  • 10/2006 – 07/2008: Berufsfachschule für EDV-Berufe Plattling, Specialized Computer Scientist – Software Development (COC)


Research & Publications

  • Fischer, D., 2020. Measuring the Collective Mind in Organizations. Working paper
    • Accepted for the “AoM Cognition in the Rough Workshop, Boston, 2019”
    • Accepted for the “Frontiers in MOC, Singapore, 2020” (cancelled).
    • Accepted for the “EURAM Conference, Dublin, 2020”.
    • Accepted for the "Organization Theory Winter Workshop, 2020".
  • Fischer D, Mostaghim S, Albantakis L. How cognitive and environmental constraints influence the reliability of simulated animats in groups. Huk M, editor. PLoS One. 2020;15: e0228879. doi:10.1371/journal.pone.0228879
  • Downar, B., Fischer D., 2019. Wirtschaftsprüfung im Zeitalter der Digitalisierung. In R. Obermeier, ed. Industrie 4.0 als unternehmerische Gestaltungsaufgabe. Springer Gabler, pp. 753–779.
  • Fischer, D., Mostaghim, S. & Albantakis, L., 2018. How swarm size during evolution impacts the behavior, generalizability, and brain complexity of animats performing a spatial navigation task. GECCO 2018. Available at:
  • Richter, W.-D. & Fischer, D., 2016. Journal Entry Testing - Ein praxisorientierter Ansatz unter Verwendung der Netzwerkstruktur. In G. Herde, ed. GoBD und Big Data - Neue Herausforderungen für die digitale Datenanalyse. Erich Schmidt Verlag Berlin, pp. 85–106.
  • Herde, G. & Fischer, D., 2015. Performance Measurement of Audit Software Tools. Bavarian Journal of Applied Sciences, 1(1), pp. 27–39.



  • 2019/07/01: European Group for Organization Studies Pre-Colloquium PhD Workshop,Edinburgh, Scotland, “Measuring the Collective Mind in Organizations”.
  • 2018/11/09: TEDxDIT, Deggendorf, Germany, “Minds and Machines”.
  • 2018/10/27: BAYERN 2, Zündfunk Netzkongress, München, Germany, „Der Weg nach Westworld: Kann es künstliches Bewusstsein geben?“ ([en] The path to westworld: Is artificial consciousness possible?).
  • 2018/07/18: Genetic and Evolutionary Computation Conference, Kyoto, Japan, “How swarm size during evolution impacts the behavior, generalizability, and brain complexity of animats performing a spatial navigation task”.
  • 2017/06/19: International Computer Auditing Education Association, London, UK, „Evidence-Based Decisions using Big Data Analytics – A Innovative Course for Schools of Management”, with Prof. Dr. Georg Herde.
  • 2014/02/22: International Conference on Accounting and Information Technology, Chiayi, Taiwan, „Performance Measurement of Audit Software Tools”.




  • (@TUM) “Evidence Based Decisions Using Big Data Analytics”, including course development.

  • (@TUM) “Fundamentals of Business Administration”.

  • (@TUM) “Topics in General Management (Business Simulation Game)”.


Supervised Master Theses:


  • Advanced Natural Language Processing for cognitive bias detection in financial reports.

  • An experimental model and implementation of the blockchain technology into financial accounting.

  • Concept for a blockchain-based cross-company financial accounting system.

  • Implementing a prototype for graph-based continuous auditing.

  • IT Target Operating Model 4.0: The role of IT in digital transformation.

  • Natural Language Processing for sentiment analysis of financial reports.

  • Machine learning for bankruptcy detection based on textual data.

  • Modeling a multi-agent environment to represent fraudulent behavior.

  • Predictive analytics in the manufacturing environment: A case of teaching machine learning algorithms.

  • The practical application of Process Mining for analysis, improvement and continuous monitoring of business processes.


Supervised Bachelor Theses:


  • Comparison and evaluation of current innovations for the digital transformation in external auditing.

  • Current state and outlook on the development of data analysis with the focus on applications in audit and accounting.

  • Digital transformation in traditional financial businesses: The accountant as a preventer or promoter?

  • Organizations in a digital future – implications from High Reliability Organizations.

  • The potential of digital innovations in financial audit and accounting.

  • Using graph metrics to support Journal Entry Testing.

Last Modification: 14.11.2021 - Contact Person: Webmaster