RCN funding for NORA-partners
Earlier this year Research Council of Norway (RCN) announced 270 MNOK for research on digital innovation. Several NORA-partners responded to this call and many of them have now been awarded funding for their research projects from RCN. Here is a presentation of some of the projects.
One of these projects is University of Oslo (UiO) project Bio-inspired neural networks for AI applications with Prof. Anders Malthe-Sørenssen (Dept. of Physics, UiO), Ass. Prof. Marianne Fyhn (Dept. of Biosciences, UiO) and Prof. Gaute Einevoll (Dept. of Physics, UiO) as main applicants. The projects has been awarded 16 MNOK over a five-year period. While artificial intelligence (AI) supersedes human skills in some fields, the brain is still far superior in many areas, being more energy efficient, needing fewer examples to learn, it can learn complex tasks easier, and it can transfer knowledge from one task to another. This project will transfer recent knowledge of brain processes to develop a next generation of machine learning methods, opening for new scientific and technological developments.
SciML– Scientific Computing & Machine Learning with Prof. Kent-Andre Mardal (UiO/Simula) as the main applicant is another project that has received funding from RCN. The project looks at partial differential equations (PDEs) which have been studied for centuries. PDEs have seen an impressive utilization in scientific computing (SC) during the last sixty years due to increasingly powerful computers. At the same time, in the last ten years, there has been a huge development in the use of machine learning (ML) techniques. ML has demonstrated a wide range of successes due to both high-performance computing and vast amounts of available data. Despite the similarities between the two areas, the synergy effects have so far been sparse, in particular on the theoretical level. The project aims to bridge the gap between these areas.
DeCipher - Data-driven Framework for Personalised Cancer Screening with Valeriya Naumova and Evrim Acar (both Simula) as main applicants has also received funding. 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. NORA-partner SimulaMet is the project coordinator with Cancer Registry Norway, Karolinska University and Lawrence Livermore National Lab as partners. If successful, already in the short term, the results will empower women to make better-informed health-related decisions together with healthcare professionals, according to Senior Research Scientist and project leader Valeriya Naumova.
Qu-Test: Enabling Future Dependable Ubiquitous Services and Data with Novel Testing Methods for Quantum Programs with Shaukat Ali and Tao Yue (both Simula) as main applicants is another project at Simula to be awarded funding. 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.
cureIT: Adaptive Immunity for Software: Making Systems and Services Autonomously Self-Healing with Leon Moonen (Simula) as main applicants has also been awarded funding. 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.
We congratulate these NORA-partners and others on being awarded these research funds.