Martin Aumüller

Martin Aumüller is a Lecturer in Theoretical Computer Science Algorithms at the IT University of Copenhagen. He serves as Head of Education and Master of Software Design, focusing on algorithm engineering, differential privacy, and similarity search.

Research interests include:

• Algorithm engineering for high-dimensional data
• Locality-sensitive hashing and nearest neighbor search
• Privacy-preserving machine learning
• Fairness in approximate search algorithms
• Benchmarking and evaluation of similarity search tools

Publications trends highlight his work on approximate nearest neighbor search, privacy-preserving techniques, clustering algorithms, and scalable outlier detection in high-dimensional spaces. His recent projects (2024-2025) focus on fairness, differential privacy, and efficient indexing.

Grants and projects:

• DIREC (2020-2025): Digital Research Centre Denmark (Innovation Fund Denmark)
• DIREC: Bias and Benefit of Approximate Nearest Neighbor Search (2022-2025): Principal Investigator (Innovation Fund Denmark)
• BARC (2017-2024): Basic Algorithms Research Copenhagen (Villum Fonden)
• SSS (2014-2019): Scalable Similarity Search (European Commission)