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Dr Christian Agrell

Programme Director Digital Assurance

Dr Agrell leverages extensive experience within developing trustworthy AI, particularly for high-risk and safety-critical systems in an industrial context. He is driven by a passion for the intersection of machine learning, uncertainty quantification, physics-based and data-driven simulation, assurance of complex systems, and risk.

About Dr Agrell 

Christian currently leads the Digital Assurance Programme of DNV’s Research and Development unit. This programme developed the recommended practice for assurance of AI-enabled systems (DNV-RP-0671) and focuses on digital transformation, AI development, uncertainty quantification, risk modelling, and assurance of AI.  

He currently leads research and strategic initiatives focused on the trustworthy and responsible use of AI in high-risk and safety-critical domains. This includes developing AI solutions that must perform reliably under demanding conditions, and designing ways to demonstrate that AI-enabled systems remain safe, secure, and dependable in real-world industrial settings.  

Christian holds a PhD in mathematics with a specialization in probabilistic machine learning, and has extensive experience in developing solutions across sectors such as energy and maritime. His work aims to revolutionize the ability of organizations with high-risk infrastructure, such as those in the energy sector, to adopt AI in a safe and reliable manner, enabling increased innovation and significant efficiencies.

 

Get to know all of DNV's Digital Trust experts

christian agrell

I am passionate about supporting industries in developing trustworthy AI for high-risk and safety-critical systems. This ensures that organizations with high-risk infrastructure, like those in the energy sector, can safely and reliably adopt AI, driving innovation and efficiency.

  • Dr Christian Agrell

  • He is active in the development of tools and methods for compliance with AI regulation, like the EU AI Act.  
  • Experience from a range of projects within the energy and maritime sectors  
  • Technical lead on machine learning and data science  
  • Technical lead on risk and reliability analysis  
  • Christian is active in the scientific community, focusing his research on topics such as: Probabilistic Machine Learning, Reinforcement Learning, Deep learning, Bayesian networks, Generative AI, Digital Twins, Surrogate modelling, Uncertainty Quantification, Gaussian Processes, Stochastic analysis. 

 

Agrell, C., Rognlien Dahl, K. and Hafver, A. (2023) ‘Optimal sequential decision making with probabilistic digital twins: Theoretical foundations’, SN Applied Sciences, 5(4), p. 114. 

 

Hafver, A., Agrell, C. and Vanem, E. (2022) ‘Environmental contours as Voronoi cells’, Extremes, 25(3), pp. 451-486. 

 

Agrell, C. and Dahl, K.R. (2021) ‘Sequential Bayesian optimal experimental design for structural reliability analysis’, Statistics and Computing, 31(3), p. 27. 

 

Gramstad, O., Agrell, C., Bitner-Gregersen, E., Guo, B., Ruth, E. and Vanem, E. (2020) ‘Sequential sampling method using Gaussian process regression for estimating extreme structural response’, Marine Structures, 72, p. 102780. 

 

Agrell, C. (2019) ‘Gaussian processes with linear operator inequality constraints’, Journal of Machine Learning Research, 20(135), pp. 1-36. 

 

See full overview of papers and publications on Google Scholar. 

 

DNV 

Senior Engineer

  • Specialist on risk, reliability and data science in projects for customers in the energy sector 
  • Software developer for DNV’s risk management software applications  
  • Developed design codes and best practices for offshore pipelines, in collaboration with industry partners through joint industry projects (JIPs). 65 % of all offshore pipelines worldwide are designed according to these

University of Oslo 

PhD, Mathematics

University of Oslo 

MSc, Mathematics

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