Research

• Papers
• CV
• Research projects
  • Benefit and Bias of Approximate Nearest Neighbor search [2022-2025, PI]
  • MMX-VR: Multimedia Metadata Exploration in Virtual Reality [2023-2026, co-PI]
• Programm commitees: SEA 2018, ESA 2018 (Track B), MMM 2019, EDML 2019, MM 2019 Reproducibility, SISAP 2019, SISAP 2020 (co-chair), ICMR 2021/2022 Reproducibility (co-chair), LATIN 2022.
• Invited talks: SEA 2020
• PhD students: Christian Janos Lebeda (co-supervised with Rasmus Pagh), Camilla Birch Okkels
• Thesis topics for students
• Code: Most 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. Paper
  • danny: Distributed similarity join using LSH. Paper
  • puffinn: Nearest neighbor search with guarantees. Paper

Teaching

Algorithm Visualizations

• Auction Matching
• Cuckoo Hashing

Classes at IT University of Copenhagen

• Algorithmic Fairness, Accountability, and Ethics (Master) (Spring 2022, 2023)
• Algorithmic Problem Solving (Bachelor + Master) (Spring 2021, 2022, 2023)
• Algorithms and Data Structures (Bachelor + Master) (Summer 2020, 2021)
• Applied Algorithms (Master’s level) (Autumn 2018, 2019, 2020, 2023)
• Introduction to Programming (Bachelor + Master) (Autumn 2018, 2019, 2020, 2021, 2022, 2023)
• Older:
  • 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 (Student’s Evaluation)
• Winter 2014 Tutorials: Efficient Algorithms (Student’s Evaluation)
• Summer 2014 Tutorials: Algorithms and Data Structures (Student’s Evaluation)
• Winter 2013 Tutorials: Efficient Algorithms (Student’s Evaluation), Complexity Theory
• Summer 2013 Tutorials: Efficient Algorithms (Undergraduate) (Student’s Evaluation)
• Winter 2012 Tutorials: Efficient Algorithms (Student’s Evaluation), Complexity Theory/Approximation Algorithms
• Summer 2012: Lecture and Tutorial: Efficient Algorithms (Undergraduate) (Lecture Evaluation, Seminar Evaluation)