Marwan Hassani

Marwan Hassani is an Assistant Professor at Eindhoven University of Technology's Department of Mathematics and Computer Science, affiliated with the Process Analytics and EAISI Foundational groups. He leads the streaming process mining research group and the Customer Journey track at the Data Science Center Eindhoven (DSC/e). His academic background includes a PhD from RWTH Aachen University (2015) and postdoctoral research there until 2016.

Research focuses on unsupervised learning methods for streaming event data, including clustering, outlier detection, and sequential pattern mining, with applications in customer journey optimization and real-time process analytics. Over 65 publications span data mining, process mining, and related areas. He serves on program committees for ECML/PKDD, SDM, and journals like KAIS and DAMI, co-chairing multiple events.

Key technical contributions include PrefixCDD for concept drift detection, BFSPMiner for sequential pattern mining, and autoencoder-based anomaly detection systems. His work addresses GDPR compliance in business processes and traffic flow prediction using contrastive learning. Awards include a 2025 Best Paper Award at ACM SIGAPP.

• Education: PhD in Computer Science (RWTH Aachen, 2015)
• Projects: Led GDPR compliance project (2018-2021), developed BPR4GDPR framework
• Teaching: Advanced Process Mining, Foundations of Data Analytics
• Editorial roles: Guest editor for Data & Knowledge Engineering, editorial board member for Process Science

Research aligns with UN SDGs through contributions to efficient resource management and privacy-preserving analytics.