Meet our experts

Dr Stephanie Kemna

Principal Research Scientist, AI

Principal Research Scientist in the Digital Assurance Program in Group Research and Development leveraging extensive experience developing adaptive behaviours, autonomy and mission planning for aquatic robots, including autonomous underwater vehicles (AUVs) and Autonomous Surface Vehicles (ASVs). She is passionate about working with AI and robotics, particularly on the development of autonomous systems.

About Dr Kemna

Stephanie is currently working on simulation-based testing for the assurance of complex systems, utilizing AI methods for smart testing and developing methods for testing systems with AI components. 

Her focus is on smart testing and developing tools for using and testing AI-based simulation models in the Simulation Trust Center (STC). Her interests also include explainable AI and autonomous systems, especially autonomous underwater and surface vehicles, given her extensive background in developing software for and working with these systems. She is also excited to work on research projects with industry partners, where DNV develops new tools for the assurance and testing of autonomous systems, enabling their safe and responsible introduction to the real world. 

Her expertise includes autonomous systems and artificial intelligence, robotics software and sensors, path and mission planning, multi-robot and multi-agent systems, machine learning, and simulations and simulation-based testing.

 

Get to know all of DNV's Digital Trust experts

Dr Stephanie Kemna

I enjoy working with AI and robotics, particularly in the development of autonomous systems. I’m excited to be involved in creating digital trust concepts and strategies to ensure the assurance of AI-enabled assets, enabling trustworthy and responsible use of AI.

  • Dr Stephanie Kemna

Developing tools for using and testing AI-based simulation models in the DNV’s Simulation Trust Center (STC). The STC is a cloud-based software for secure collaboration to run co-simulations of systems, enabling simulation-based testing for development, integration and assurance of complex systems. 

 

Involvement in multiple research projects within DNV, including SIMPLEX: “The role of SIMulation in assurance of intelligent and comPLEX systems”, on the development of smart testing methods in simulation-based testing, for the assurance of autonomous ferries. 

Glomsrud, J. A., Kemna, S., Vasanthan, C., Zhao, L., McGeorge, D., Pedersen, T. A., Torben, T. R., Rokseth, B., Nguyen, D. T. (2024). “Modular assurance of an Autonomous Ferry using Contract-Based Design and Simulation-based Verification Principles”, In MTEC/ICMASS 2024, pp. 1-12.

 

Bellou, N., Gambardella, C., Karantzalos, K., Monteiro, J. G., Canning-Clode, J., Kemna, S., Arrietta-Giron, C. A. & Lemmen, C. (2021). “Global assessment of innovative solutions to tackle marine litter.” Nature Sustainability, 4(6), pp. 516-524.

 

Arnegaard, O. T., Leira, F. S., Helgesen, H. H., Kemna, S., & Johansen, T. A. (2021). “Detection of objects on the ocean surface from a UAV with visual and thermal cameras: A machine learning approach.” In 2021 International Conference on Unmanned Aircraft Systems (ICUAS), pp. 81-90. 

 

Kemna, S., & Sukhatme, G. S. (2018). “Surfacing strategies for multi-robot adaptive informative sampling with a surface-based data hub.” In OCEANS 2018 MTS/IEEE Charleston, pp. 1-10. 

 

Kemna, S., Rogers, J. G., Nieto-Granda, C., Young, S., & Sukhatme, G. S. (2017). “Multi-robot coordination through dynamic Voronoi partitioning for informative adaptive sampling in communication-constrained environments.” In 2017 IEEE International Conference on Robotics and Automation (ICRA), pp. 2124-2130. 

 

See full overview of papers and publications on Google Scholar.

NATO STO Centre for Maritime Research & Experimentation

Consultant/Scientist

Maritime Robotics AS 

Research Manager, Software Engineer & Project Manager 

University of Southern California 

PhD Computer Science

University of Groningen 

BSc & MSc Artificial Intelligence