Algorithms and Complexity

The Algorithms and Complexity (AC) section tries to understand how efficiently computers can solve combinatorial problems. Most of the work is theoretical using the power of mathematics, yet we have a strong track record of impact on the real world, e.g., focusing some of our attention on problems recurring in machine learning and related applied areas.

Research Themes

The Algorithms & Complexity (AC) section at the Department of Computer Science (DIKU) focuses on the fundamental limits and possibilities of efficient computation. We explore core topics in theoretical computer science, including data structures, graph algorithms, computational complexity, and algorithmic paradigms.

While our research is rooted in mathematical theory, it often leads to practical breakthroughs—especially in areas such as algorithm design for massive data, optimization, and theoretical foundations of machine learning. The section also hosts the Basic Algorithms Research Copenhagen (BARC) centre and contributes actively to both teaching and international research communities.

Led by Professor Mikkel Thorup, the AC section brings together an international team of researchers dedicated to advancing our understanding of computation through deep, rigorous, and impactful work.

Research Groups and Centres

Research groups

Dynamic and Static Graph Algorithms and Data Structures

Centres

We have two main centres: Basic Algorithms Research in Copenhagen (BARC) supported by the VILLUM foundation and Danish Center for Big Data Analytics driven Innovation (DABAI) supported by the Innovation Fund Denmark. BARC has a theoretical focus and involves researchers from both KU and ITU. DABAI is more focused on data analysis and industry. In collaboration, DABAI propels relevant discoveries from BARC to reach beyond its theoretical core, and to impact science and industry.

Basic Algorithms Research Copenhagen (BARC)
Danish Center for Big Data Analytics driven Innovation (DABAI)

Teaching

The Algorithms & Complexity (AC) teaches in courses offered in the Bachelor and Master programs, advancing from core algorithmic principles to cutting-edge theoretical research.