"Simula and SimulaMet had in total of 7 projects in this application round, proving that hard work, great employees, and great research yield results," says Lekve.
The four projects are:
DeCipher: Data-driven Framework for Personalised Cancer Screening(Valeriya Naumova and Evrim Acar)
The objective of the DeCipher project is to develop an artificial intelligence framework for personalized cancer screening, with a particular focus on cervical cancer, by utilizing existing registries and health data intelligently. These advances will enable more accurate cancer screening and integration of data-driven techniques into biomedical domains.
SimulaMet is the coordinator with Cancer Registry Norway, Karolinska University, Lawrence Livermore National Lab as partners.
"The DeCipher project will develop novel data-driven tools for personalized cancer screening. If successful, already in the short term, the results will empower women to make better-informed health-related decisions together with healthcare professionals" says Senior Research Scientist and project leader Valeriya Naumova.
SciML: Scientific Computing & Machine Learning(Kent-Andre Mardal and Simon Funke)
The overall ambition of the SciML project is to develop novel mathematics with corresponding software tools towards reliable formulations of solution strategies at the interface between scientific computing and data science. Secondary objectives are to strengthen the AI community in Norway with expertise at the interface between scientific computing and data science.
The coordinator is Simula with UiO as a partner.
“As machine-learning has become mainstream we do believe it is important with scrutiny to ensure a robust usage in mission-critical applications in medicine or military. In our project, we will look at how traditional and high-performance techniques in scientific computing can be combined with learning techniques in an accurate and efficient manner. We are grateful to NFR for their substantial support on this project where we focus on long-term and theoretical aspects of learning” says Adjunct Research Scientist Kent Andre Mardal.
Qu-Test: Enabling Future Dependable Ubiquitous Services and Data with Novel Testing Methods for Quantum Programs(Shaukat Ali and Tao Yue)
The ambition of Qu-Test is to develop radically new methods for automated and systematic testing of quantum programs, based on a rigorous theoretical foundation with the ultimate goal of supporting future ubiquitous services and data related to QC applications to guarantee their dependability. To allow for testing complex quantum programs with a minimal amount of QC resources, the project will also propose novel quantum optimization algorithms.
Simula is the coordinator with the University of Malaga, University of Maryland, Durham University as partners.
"Considering that we are new to quantum computing, it is a remarkable achievement for us to secure funding for this project, as highlighted by the proposal reviewers: "This is an opportunity for a Norwegian organization to lead the way and establish the initial foundation for an emerging research field ahead of others" says Chief Research Scientist Shaukat Ali.
cureIT: Adaptive Immunity for Software: Making Systems and Services Autonomously Self-Healing(Leon Moonen)
The overall goal of the cureIT project is to significantly increase dependability, robustness, and resilience of ICT by devising novel methods and techniques that will help software engineers create smart, self-healing software systems and services. In particular, it aims to build an artificial immune system for software systems that, similar to the biological immune system, acts as an adaptive (i.e. learning) mechanism that can autonomously detect, diagnose and contain unanticipated faults while the system is in operation.
The coordinator is Simula with Edinburgh Napier University, University of Maryland and Centre for Molecular Medicine Norway as partners.
"I am very excited that the cureIT proposal is funded because it enables us to do innovative interdisciplinary research into bio-inspired data-driven techniques that will help create resilient self-healing software systems," says project leader and Chief Research Scientist Leon Moonen.