Prof. Dr. Dagmar Monett
Professor of Computer Science
Berlin School of Economics and Law, Germany

Current research interests

Current topics:

  • Artificial Intelligence (e.g. AI subfields like machine learning and knowledge-based systems)
  • Understanding and defining intelligence and the boundaries of its dicourse
  • AI ethics, AI responsibly, Digital ethics, Digital education ethics
  • Computer Science education, Robotics in education
  • Distributed AI, agents and multiagent systems
  • Optimization, metaheuristics, and soft computing (e.g. evolutionary computation, artificial neural networks)

For a list with my publications and talks click on the tab Papers+Talks!

Follow me on LinkedIn or @dmonett on Twitter, where I used to post and tweet, resp., about these and other research topics!

Other research interests

Other topics, also related to the ongoing teaching:

  • E-Learning
  • Software engineering, Agile software development, eXtreme Programming
  • Social media analysis, social networks, blogosphere, new media

Related to the projects I was involved in and directed by Prof. Andreas Griewank, Mathematics at the Humboldt University of Berlin, Germany:

  • Automatic/Algorithmic differentiation
  • Differential algebraic equations

Related to the projects I was involved in and directed by Prof. Hans-Dieter Burkhard, Computer Science at the Humboldt University of Berlin, Germany:

  • Socionics (Sociology + Computer Science)

Related to the projects I was involved in at the Center of Biomaterials, Havana, Cuba:

  • Parameter estimation, inverse problems, mathematical modelling of chemical processes

Ongoing and past projects

AI, AI ethics, AI responsibly:

  • A permanent, ongoing research project from the perspective of an AI insider, covering different topics related to the implications (both positive and negative) of the design, implementation, testing, deployment, and use of AI, as well as of the misunderstandings and issues derived from AI illiteracy, AI hype, anthropomorphism, misguiding narratives, ahistoricism, and a long list of unnecessary ballast the field carries since its foundation.
  • AI promises, fallacies, and pitfalls: Inhibitors and stepping-stones for progress in Artificial Intelligence. Sabbatical semester, Oct/2022-March/2023.


  • Tracking the Evolution of (machine) Intelligence: An Intelligence Catalog-guided mapping of scientific research. Oct/2019-March/2020.
  • Defining Intelligence: Overcoming fundamental problems of intelligence research. Sabbatical semester, Oct/2018-March/2019.
  • International research survey “Defining (machine) Intelligence”: Final data post-processing and analysis. Apr-Sept/2018.

AI, Robotics, Technology, Big Data:

Education, Higher Education, E-Learning, EdTech:

  • AIRI Education: AI fundamentals according to AIRI and their applications in higher education (together with my colleague Prof. Dr. Claudia Lemke). Apr/2022-Sept/2022.
  • Das TAL-Modell im Unterricht der agilen Softwareentwicklung: Formalisierung des Modells und praktischer Einsatz der Interaktionsdynamik zwischen dem Lehren (T), dem Lernen (L) und dem Anwenden (A) des Gelernten in agilen Softwareentwicklungskursen (short: The TAL model in Agile Software Development Education). Sabbatical semester, Oct/2014-March/2015.
  • eLearning und eAssessment: Erweiterung der eLearning-Plattform Moodle um moderne an die HWR angepasste Evaluierungs- und Prüfungsfunktionen (eLearning und eAssessment: Extending the eLearning platform Moodle with modern, HWR-customized evaluation and test functionalities). Apr-Dec/2012.