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Division of Software and Computer Systems

The Division of Software and Computer Systems (SCS) is a part of the School of Electrical Engineering and Computer Science. More precisely we are a part of the Department of Computer Science (CS).

KTH Kista moves to KTH Campus

The activities at KTH Kista will gradually be moved to the KTH Campus from the spring semester of 2025. The move will give researchers, teachers and students more community, better resources and closer cooperation.

Read more about KTH Kista's move to KTH Campus (internal web)

Research areas and groups

Machine Learning and Computational Health

Data Science: Machine Learning

Research on algorithms and systems for data analysis, machine learning and data mining. We work in healthcare, drug development, climate research, vehicle maintenance and social networking.

GALE - Graph Analytics and Learning Environments

GALE: Graph Analytics and Network Learning

Focuses on bridging the gap between Machine Learning and Distributed Systems to address the challenges posed by centralized AI services.

GALE - Graph Analytics and Network Learning

Programming languages and modelling

We investigate programming languages and modelling languages, cyber-physical systems, model based computer systems, compilers and machine leärning.

Programming languages and modelling

Software Engineering

Software Development with Clouds and Artificial Intelligence

We research Software technology for Cloud computing, and also AI techniques for instance for for health care and smart cities.

Data Systems Lab

We focus on data-driven system design with applications in serverless computing, distributed databases, AI, data stream platforms, graph query systems, and acceleration using emerging new hardware and methods.

Data Systems Lab

Distributed and Parallel Systems

Distributed and Parallel Systems

We develop large distributed systems and algorithms in data intelligent cloud services, big data and data analysis systems.

Networked Systems Security

Networked Systems Security

We make networked systems trustworthy by shielding them and their users from attacks and abuse. Our research solving security and privacy problems..

Network Systems

Network Systems

Our main research focus is making it easy to develop and manage key societal Network Systems that meet their objectives. Classic examples include: high performance, high reliability, and low-power.

News

A programmable switch that was used in the research.
A programmable switch that was used in the research.

New cybersecurity analysis solution leads to significant reduction in energy consumption

By offloading calculations for complex cybersecurity analyses to network accelerators, energy consumption can be reduced by over 30 times, according to Mariano Scazzariello, a postdoctoral researcher ...

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Making data accessible - despite server and network issues

A software developed by KTH has enabled cloud services to be easier to build and more resilient to failures. “I wanted to make fault-tolerant systems easy to build and use, contrary to what is ofte...

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Sonia Horchidan and Paris Carbone

Elevated credibility in AI-generated information

A new graph database management system is under development at KTH. Using graph technology in combination with artificial intelligence (AI), the system could assist in planning everything from healthc...

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Meet the division

Recent publications

[1]
B. Lindqvist and A. Podobas, "Algorithms for Fast Spiking Neural Network Simulation on FPGAs," IEEE Access, vol. 12, pp. 150334-150353, 2024.
[2]
B. Baudry et al., "Generative AI to Generate Test Data Generators," IEEE Software, vol. 41, no. 6, pp. 55-64, 2024.
[3]
S. Karimi, S. Asadi and A. H. Payberah, "BaziGooshi : A Hybrid Model of Reinforcement Learning for Generalization in Gameplay," IEEE Transactions on Games, vol. 16, no. 3, pp. 722-734, 2024.
Full list in the KTH publications portal

Vision and mission

The goal of the division SCS is to continue strong research and education on fundamental aspects of software technology and computer systems, central areas within Computer Science. We have a focus on cloud computing, networked systems, security in networked systems, social networks, time aware systems, data science, and applied AI as well as Software Engineering.