Research Areas

Simula's research focuses on five main research areas within Information and Communication Technology.

Communication systems

The research of communication systems works to leverage the opportunities and reduce the malfunctions and associated risks with modern communication systems. Today's digital society means that nearly every activity, from buying a coffee to filing your taxes, is connected to the internet. Daily life is at once more efficient and more vulnerable. Researchers in this area are mapping the geographic distribution of cloud services that increasingly span beyond national borders as one example. Evolving the management of software development and how to successfully digitise the public sector are also current investigations.

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Cryptography research increases security expertise. Our researchers design and analyse cryptographic schemes for secure communication and computation, evaluate the security of their implementation, and develop techniques for efficient, secure and reliable communications, networking, storage and retrieval of information. For example, creating tools that can keep online sensitive information secure, such as with electronic voting and blockchain applications.

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Scientific Computing

Research in scientific computing allows us to describe reality through mathematical models and computer simulations. Combining machine learning, physics and high-performance computing, we research both theoretical foundations and applications of these models. For example, understanding the human body, such as the brain or how the heart might alter its functioning after a heart attack.

Software engineering

The research in software engineering supports the complex software systems that society relies upon so that they are robust, reliable, safe and secure. This goes for today’s systems and for the quantum systems of the future. Researchers use artificial intelligence, machine learning, test self-healing software and more to validate autonomous software, such as cargo machinery, industrial robots and self-driving cars.

Machine Learning

As a research area, machine learning foundations are mathematical, ranging from the experimental study of algorithms to real-life applications such as the development of methods and tools to resolve issues in human health, technology and society. Examples of this include the development of cancer screening tools that take into account individual risks, fertility research and sports technology.

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