Daniel Lindner

Dr. Daniel Lindner is a researcher at the Information Systems Group of the Hasso Plattner Institute. His work focuses on integrating data dependencies into database query optimization through unsupervised discovery techniques and advanced optimization methods.

• Research Area: Data Profiling, Query Optimization, Data Quality
• Teaching: Lecturer for 'Develop Your Own Database' (Summer 2022, 2023, 2025) and 'Advanced Data Profiling' (Winter 2023/24)
• Contact: daniel.lindner@hpi.de | Room F-2.07 | +49 (331) 5509-3475

His research aligns with the group's projects including Metanome (Big Data Profiling), Metis (Data Quality Assessment), and KITQAR (Data Quality for AI Applications). Recent work explores workload-driven data encoding trade-offs and CXL memory integration for database systems.

Key contributions include publishing in venues like SIGMOD, CIDR, and EDBT. He co-supervised Niklas Riekenbrauck's 2023 master's thesis on CXL-attached memory buffer management.