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13 December 2023

The award goes to....  

PhD Student Axel Christfort and Supervisor Associate Professor Tijs Slaats from the University of Copenhagen won the Process Discovery Contest at the 5th International Conference on Process Mining with their DisCoveR miner.

In a remarkable achievement, PhD student Axel Christfort and his supervisor, Associate Professor Tijs Slaats, won the Process Discovery Contest at the 5th International Conference on Process Mining.

Their cutting-edge DisCoveR miner produced the most accurate models and stood as the sole algorithm to successfully complete discovery and classification tasks within the stipulated time.

Process discovery algorithms play a crucial role in analyzing event logs, generating human-readable models that elucidate the behavior captured in the log. This includes understanding how individuals sequence activities in their work processes. The ICPM Conference, organizers of the Process Discovery Contest, evaluate submissions based on accuracy, requiring participants to mine models for a diverse range of logs and correctly classify corresponding ground truth traces.

This is the third prize in the Process Discovery Contest for the Process Modelling and Intelligence group from the Department of Computer Science, University of Copenhagen. In 2021, they secured awards for the best overall and the best imperative miner. The DisCoveR miner.

DisCoveR originated from a M.Sc. thesis by Viktorija Sali and Andrew Tristan Parli, supervised by Professor Slaats. The algorithm has undergone further refinement by Industrial PhD Student Christoffer Olling Back from ServiceNow, with ongoing enhancements by Axel Christfort. Funding from Independent Research Fund Denmark, DIREC – Digital Research Centre Denmark, and Innovation Fund Denmark has been instrumental in supporting this groundbreaking work.

Axel Christfort and Tijs Slaats are nominated Process Discovery Contest Winners

The industrial application of DisCoveR has been demonstrated through its implementation by DCR Solutions. The algorithm’s efficacy and utility have been validated in real-world scenarios, emphasizing its practical significance. Ongoing contributions from PhD Vlad Paul Cosma and Professor Thomas Hildebrandt have further extended and improved the miner, adding to its robustness.

Looking ahead, the Process Modelling and Intelligence group is eager to build upon these achievements to secure additional funding and foster novel collaborations. The team is already gearing up for the next iteration of ICPM, aiming to continue their winning streak and further advance the field of process discovery.


Associate Professor Tijs Slaats is the project manager of the DIREC project ‘AI and Blockchain for complex business processes’.

Together with industry, the project aims to develop methods and tools that enable the industry to develop new efficient solutions for exploiting the huge amount of business data generated by enterprise and blockchain systems, with a specific focus on tools and responsible methods for the use of process insights for business intelligence and transformation.