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Computational Science and Technology
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Division of Computational Science and Technology

Computational Science and Technology is a multidisciplinary field that uses advanced computing methodologies to understand and solve complex problems. The division develops methods, computing environments and data analysis capabilities to solve scientific questions in a multi-disciplinary setting shaping the future of computing.

Research areas

Computational Biology and Machine Learning in Biomedicine

We are located at SciLifeLab, Sweden’s main centre for high-throughput biology, and work on computational problems in molecular biology, primarily related to evolution and genomics.

Biological Physics and Systems Biology

Research projects within the group consists of Quantum Thermodynamics and heat in open quantum systems, non-equilibrium physics on the meso-scale and inverse statistical mechanics.

Computational Brain Science

We perform research on (i) computational modelling of biological brain function and on (ii) developing theory, algorithms and software for building computer systems that can perform brain-like functions.

Numerical Methods

The research in numerical methods combines fundamental research in mathematics and computer science, with applied research in interdisciplinary projects across different research environments, with industry and society.

Parallel Computing

We investigate the possibility of extending the Message Passing Interface (MPI) to support streaming and communication-offloading models on supercomputers to support scientific applications with irregular fine-grained communication.

Visualization

There are three subtopics in Visualization at KTH: visualization and data analysis, interactive virtual characters and computer game technologies and human-centered visualization.

 Meet the division

Recent publications

[1]
D. Araújo De Medeiros, "Emerging Paradigms in the Convergence of Cloud and High-Performance Computing," Licentiate thesis Stockholm, Sweden : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2023:80, 2023.
[2]
D. Araújo De Medeiros et al., "Kub : Enabling Elastic HPC Workloads on Containerized Environments," in Proceedings of the 35th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), 2023.
[3]
I. Carannante, "Computational Modelling and Topological Analysis of the striatal microcircuitry in health and Parkinson's disease," Doctoral thesis : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2023:82, 2023.

News

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A new methodology can accelerate the diagnosis and possibly treatment of patients, helping return the brain to more healthy activity. Photo: Format Arw/Unsplash

Better data analysis can improve treatment of Parkinson’s disease

More accurate data help understand how extensive local brain networks are affected in patients.

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Boy sitting by a desk writing on a piece of paper.
A new study shows the important role dopamine plays when we are learning new tasks. Dopamine cells send much more detailed information to other brain cells than what is previously known. Photo: Santi Vedri/Unsplash

The hidden computational role of dopamine in the brain

Neuromodulators in the brain shape our ability to learn much better than previously thought

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Photo: Andrik Langfield, Unsplash

Researchers unlock the secret to the brain's working memory

New insights from brain science can lead to the development of artificial intelligence possessing cognitive abilities similar to humans.

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Calendar

Page responsible:Web editors at EECS
Belongs to: Computational Science and Technology
Last changed: Nov 06, 2023