Rate My Professor Martin Hentschel

Martin Hentschel is an Associate Professor in the Department of Computer Science at the IT University of Copenhagen, heading the Data-intensive Systems and Applications research group within the DASYA Lab of the Data, Systems, and Robotics section. He earned his BSc, MSc, and PhD degrees in computer science from ETH Zurich, Switzerland, following studies at TU Dresden, Germany. Before entering academia, Hentschel worked as a Principal Software Engineer at Snowflake, contributing to security features, metadata management, and performance optimizations, while also founding and establishing the company's engineering site in Berlin, Germany. Prior to Snowflake, he was employed at Microsoft, developing components for the Bing search engine. His transition from industry to academia brings practical expertise in large-scale data systems to his teaching and research roles at ITU.

Hentschel's research centers on database systems, open data and metadata formats, and data management in general, with applications in cloud environments and scientific workflows. He serves as Principal Investigator for the project 'Open Data Management for Scientific Innovation,' funded by the Novo Nordisk Foundation and running from 2025 to 2028, in collaboration with Peter Sestoft and Alexander T. B. Pedersen. His recent publications include 'Benchmarking Role-Based Access Control in Data Management Systems' (2025, TPC Technology Conference, with M. C. Hansen and P. Tözün), 'Building a Data Management System for the Cloud: Lessons Learned and Future Directions' (2025, Datenbank-Spektrum, with J. Dees, F. Funke, M. Heimel, and I. Oukid), 'Reminiscences on Influential Papers' (2025, SIGMOD Record, with V. Braganholo), and 'Workshop on Advances in Cloud Data Management' (2025, with J. Giceva and T. Ziegler). Hentschel supervises PhD fellows, such as Alexander Bilde Pedersen on open data formats and metadata, and contributes to workshops and conferences on cloud data management, drawing from his Snowflake experience to advance resource-aware data systems and access control benchmarking.