News:
- I'm co-organizing the 2nd Workshop on Vector Databases (VecDB) at VLDB'26.
Research
I enjoy designing and evaluating algorithms that bridge theory and practice, with a focus on:
- Similarity Search & Benchmarking: Algorithms for high-dimensional nearest neighbor search (puffinn, danny), community benchmarks (ann-benchmarks, big-ann-benchmarks, vector-index-benchmark) that define research practices, and understanding what makes search methods work in practice.
- Differential Privacy: Private algorithms for sparse vectors, mean estimation, and approximate range counting with strong formal guarantees.
Selected Publications
- ANN-Benchmarks: A Benchmarking Tool for Approximate Nearest Neighbor Algorithms, Inf. Syst., 2020
- PUFFINN: Parameterless and Universally Fast FInding of Nearest Neighbors, ESA 2019
- Sampling near neighbors in search for fairness, Commun. ACM, 2022
- Differentially Private Sparse Vectors with Low Error, Optimal Space, and Fast Access, CCS 2021
- Distance-Sensitive Hashing, PODS 2018
See the full list of publications for all details.
Research projects
- Benefit and Bias of Approximate Nearest Neighbor search [2022-2025, PI, finished]
- MMX-VR: Multimedia Metadata Exploration in Virtual Reality [2023-2026, co-PI]
Team
If you're interested in working with me, feel free to reach out. I'm always happy to discuss new ideas and collaboration opportunities.
- Finished PhD students
- 2023: Christian Janos Lebeda (co-supervised with Rasmus Pagh, now postdoc at INRIA, France)
- 2025: Camilla Birch Okkels (co-supervised with Arthur Zimek)
- 2026: Fabrizio Boninsegna (at UniPD, co-supervised with Francesco Silvestri)
- Research assistants
- Alexander Theodor Bilde Pedersen (2025)
- Viktor Bello Thomsen (2024-2025)
- Scientific Visitors
- David Procházka (visiting PhD student, 2025)
- Atsuki Sato (visiting PhD student, 2026)
Code & Challenges
Most code is available on GitHub. Selected projects:
- ann-benchmarks: The de-facto standard for benchmarking approximate nearest neighbor search algorithms. [Paper]
- big-ann-benchmarks: Benchmarking approximate nearest neighbor search on billion-scale and with modern workloads. [Paper NeurIPS'21 Challenge], [Paper NeurIPS'23 Challenge]
- vector-index-benchmark: ann-benchmarks++: Benchmarking ANN on modern datasets, with better visualization, and better support for HPC environments. [Paper]
- puffinn: Nearest neighbor search with guarantees. [Paper]
- danny: Distributed similarity join using LSH. [Paper]
Challenges
- 2026: SISAP Indexing Challenge
- 2025: SISAP Indexing Challenge: Report
- 2024: SISAP Indexing Challenge: Report
- 2023: NeurIPS Practical Vector Search challenge: Report, Code
- 2023: SISAP Indexing Challenge: Report
- 2021: NeurIPS Billion-Scale ANN Challenge: Report, Code
Invited Talks, Tutorials, Workshops
- Algorithm Engineering for High-Dimensional Similarity Search at SEA'20 (Slides, Recording)
- Neural Search in Action at CVPR'23 (Slides, Recording)
- High-dimensional Approximate Nearest Neighbor Search: Applications, Algorithms, Current Challenges at DAMVISEH at SDU Odense, 2025 (Slides)
- I co-organized the first workshop on vector databases (VecDB) at ICML'25
Teaching
Current courses at IT University of Copenhagen
- Algorithmic Problem Solving (Bachelor + Master) (Spring 2021, 2022, 2023, 2024, 2025, 2026)
- Applied Algorithms (Master's level) (Autumn 2018, 2019, 2020, 2023, 2024, 2025, 2026)
Previous courses
- Introduction to Programming (Bachelor + Master) (Autumn 2018, 2019, 2020, 2021, 2022, 2023)
- Introduction to Data Science and Programming (Autumn 2024)
- Algorithms and Data Structures (Bachelor + Master) (Summer 2020, 2021)
- Algorithmic Fairness, Accountability, and Ethics (Master) (Spring 2022, 2023, 2024)
- Spring 2018, First-Year Project: Map of Denmark. Visualization, Navigation, Searching, and Route Planning (Bachelor's level)
- Autumn 2017, Programming Workshop (Master's level)
- Spring 2017, Algorithm Design Project (Master's level)
- Fall 2016, Introduction to Programming Workshop (Master's level)
- Spring 2016, Advanced Algorithms Seminar (Master's level)
Classes at Technische Universität Ilmenau (in German)
- Winter 2015 Tutorials: Efficient Algorithms, Foundations and Methods of Cryptography
- Summer 2015 Tutorials: Algorithms and Data Structures
- Winter 2014 Tutorials: Efficient Algorithms
- Summer 2014 Tutorials: Algorithms and Data Structures
- Winter 2013 Tutorials: Efficient Algorithms, Complexity Theory
- Summer 2013 Tutorials: Efficient Algorithms (Undergraduate)
- Winter 2012 Tutorials: Efficient Algorithms, Complexity Theory/Approximation Algorithms
- Summer 2012: Lecture and Tutorial: Efficient Algorithms (Undergraduate)
Algorithm Visualizations
Oldies but goldies?
Academic Service
Programme committees & Organization
- ALENEX 2027
- VLDB'26 VecDB Workshop (co-chair)
- SEA 2026 (PC co-chair)
- ICML'25 VecDB Workshop (co-chair)
- ESA 2025 (Track S)
- SISAP 2024
- CIKM 2024
- LATIN 2022
- ICMR 2021/2022/2023 Reproducibility (co-chair)
- SISAP 2020 (co-chair)
- SISAP 2019
- MM 2019 Reproducibility
- EDML 2019
- MMM 2019
- ESA 2018 (Track B)
- SEA 2018