• Learning Conditional Marked Event Sequences with Mixed Data Types
  Felix Draxler, Yang Meng, Kai Nelson, Lukas Laskowski, Yibo Yang, Theofanis Karaletsos, Stephan Mandt
  Proceedings of the 38th Conference on Neural Information Processing Systems (NeurIPS), 2025 — Spotlight
  [Project]
• Burr: A Benchmark for Ontology Learning from Relational Databases
  Lukas Laskowski, Michael Hladik, Jan Portisch, Fabian Panse, Felix Naumann
  Proceedings of the ACM SIGMOD/PODS International Conference on Management of Data (SIGMOD), 2026
• PRISMA: A Privacy-Preserving Schema Matcher using Functional Dependencies
  Jan-Eric Hellenberg, Fabian Dustin Mahling, Lukas Laskowski, Felix Naumann, Matteo Paganelli, Fabian Panse
  28th International Conference on Extending Database Technology (EDBT)
  [Paper]
• GorillaVision – Open-Set Re-Identification of Wild Gorillas
  Lukas Laskowski, Rohan Sawahn, Maximilian Schall, Dante Wasmuht, Magdalena Bermejo, Gerard De Melo. Camera traps, AI, and Ecology, 2023
  [Paper]  [Project Page] 
• Explainable Data Matching: Selecting Representative Pairs with Active Learning Pair-Selection Strategies
  Lukas Laskowski, Florian Sold. Proceedings of the Conference on Database Systems for Business, Technology, and Web (BTW), 2023
  [Paper]  [DOI:10.18420/BTW2023-77]
• Frost: A Platform for Benchmarking and Exploring Data Matching Results (industry paper)
  Martin Graf, Lukas Laskowski, Florian Papsdorf, Florian Sold, Roland Gremmelspacher, Felix Naumann, Fabian Panse. PVLDB 15:(12), 2022
  [Paper]  [Project Page] 

Seminars:

• Data Cleaning & Integration (WS 23/24)
• Entity Resolution Datasets Dashboard (SS 24)
• DBStrange: Exploring the Multiverse of Entity Resolution Datasets (WS 24/25)
• Table Representation Learning (WS 24/25)
• Advanced Data Profiling: Classifying Genuiness (WS 25/26)

Masterprojects:

• DBStrange: Exploring the Multiverse of Entity Resolution Datasets (SS 24)
• Constrained-based Schema Matching (WS 23/24)

Masterthesis Supervision:

• David Kuska: Image-Primary Retrieval-Augmented Generation: Combining Visual and Textual Features for Multimodal RAG
• Tim Riedel: Foundational Models for Flight Data