Biography and publications

Below my biography and my publications on my human-AI interaction research, in particular on Explainable AI.


Jasper van der Waa is a researcher on human-AI interaction mixing fundamental and applied research.

Jasper van der Waa, born 1991 in the Netherlands, studied Artificial Intelligence at the Radboud University in Nijmegen. After his master’s focused on interactive machine learning, he started at TNO in 2016. TNO is the Dutch research institute for applied research, where Jasper’s research revolves around optimizing the human-AI interaction by expanding the AI’s functionality through the identification of requirements and development of new algorithms and technologies. In 2018 he started with his PhD research at the Technical University of Delft on the topic of explainable AI for improving the human-AI collaboration. His unique position allows him to collaborate closely with companies and government institutes to identify the most pressing issues that can be solved with explainable AI while collaborating with universities to address these issues through research.

He worked with financial institutes (ABN Amro, Achmea), AI companies (Xomnia, Enjin), healthcare institutes (Curium), the Dutch government (Ministry of Defence, Ministry of Internal Affairs, Employee Insurance Agency) and other research institutes (NLR, Marin). He also acted as liaison between the Technical University of Delft and the Ministry of Defence (KMA) on moral value elicitation. Furthermore he participates in NATO meetings (SCI-335 SRM) and roundtable discussions on the topic of AI in relation to current and future (European) regulations.

Aside from his collaboration with various parties, he organizes several community events such as summer schools, hackathons, presentation sessions and panel discussions that revolve around human-AI interaction. Furthermore, he is the founder of two opensource projects and their communities. The first is MATRX, a tool to accelerate human-machine teaming research by offering a platform to evaluate and test that research in various tasks. The second is the XAI Toolbox that aims to standardize and ease the use of the responsible application of explainable AI technologies.

His goal in all of these efforts is to enable effective and responsible human-AI collaboration and build and sustain communities that share this goal.

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List of publications

  1. 2022

  2. An Optimum Well Control Using Reinforcement Learning And Policy Transfer; Application To Production Optimization And Slugging Control

    J. Poort, P. Shoeibi Omrani, T. Mannucci & J. van der Waa.

  3. Actionable Explanations for Contestable AI

    J. van der Waa, J. van Diggelen, M. Neerincx & C. Jonker. Journal of Artificial Intelligence Research

  4. Towards FAIR Explainable AI: a standardized ontology for mapping XAI solutions to use cases, explanations, and AI systems

    A. Adhikari, E. Wenink, J. van der Waa, C. Bouter, I. Tolios & S. Raaijmakers. Conference on Pervasive Technologies Related to Assistive Environments

  5. Intelligent Operator Support Concepts for Shore Control Centres

    H. van den Broek & J. van der Waa. International Conference on Maritime Autonomous Surface Ships

  6. Dynamic task allocation algorithms within intelligent operator support concepts for shore control centres

    T. Brug, J. van der Waa, V. Maccatrozzo & H. van den Broek. Conference on Computer Applications and Information Technology in the Maritime Industries

  7. The FATE system iterated: Fair, Transparent and Explainable Decision Making in a Juridical Case

    M. de Boer, S. Vethman, R. Bakker, A. Adhikari, M. Marcus, J. de Greeff, J. van der Waa, T. Schoonderwoerd, I. Tolios, E. van Zoelen, F. Hillerström & B. Kamphorst. AAAI Spring Symposium on Machine Learning and Knowledge Engineering for Hybrid Intelligence

  8. 2021

  9. 2020

  10. 2019

  11. 2018

  12. 2017

  13. 2015

  14. 2013

Complete list of publications

Did you know about?

  • XAI for human-AI collaboration

    As a sufficient understanding is needed to for humans to use AI systems responsibly and collaborate with them effectively, we need to research what explanations an AI should provide to support this.

    My PhD research
  • Community and opensource projects

    To ensure AI systems are applied and used responsible and effectively, I believe that research and industry communities should to be brought together. Through several projects I aim to create and support those communities.

    Personal projects
  • Research at TNO

    At TNO I participate and lead several projects in the domain of human-AI interaction.

    My work at TNO