AI-forskning og -innovasjon
UiB har flere tverrfaglige forskningssentre innen grunnleggende og anvendt AI samt AI innen innovasjon. Forskningsgrupper med fokus på grunnforskning og anvendelse av AI finnes på flere fakulteter.
Hovedinnhold
 The Center for Data Science, CEDAS Foto/ill.:
Center for Digital Narrative
| Center for Digital Narrative is a Norwegian Centre of Research Excellence funded by the Norwegian Research Council from 2023-2033. CDN focuses on algorithmic narrativity, new environments and materialities, and shifting cultural contexts. https://www.uib.no/en/cdn |
 The Bergen Algorithms Research Group | The Center for Data Science, CEDAS, was established to unify and coordinate research and education efforts in Data Science and Artificial Intelligence across the University of Bergen. https://www.uib.no/en/cedas |
 The research group in machine learning | The Bergen Algorithms Research Group is researching effective and efficient algorithms that can make computer programs to run as fast as possible. A special focus is put on hard decision problems, so-called NP-complete problems, and try to find practical algorithm for these. https://www.uib.no/en/rg/algo |
 Computational Biology Unit (CBU) | The research group in machine learning conducts research in fundamental principles and algorithms for machine learning, including Bayesian networks, topological data analysis, computational learning theory, and deep learning. https://www.uib.no/en/rg/ml |
 The group for Intelligent Information Systems (I2S) | Computational Biology Unit (CBU) is a leading hub of bioinformatics research spanning both the basic and applied fields. The centre offers support and assistance to the life science community, and coordinates the bioinformatics education for the next generation of computational biologists. https://www.cbu.uib.no/ |
 The Logic and Artificial Intelligence (LAI) | The Logic and Artificial Intelligence (LAI) group study the foundations of reasoning about information in systems of interacting agents, with applications in several different sub-areas of Artificial Intelligence and Multi-Agent Systems particularly including logic-based knowledge representation and reasoning. |
 Statistics and data science | The group for Intelligent Information Systems (I2S) studies information systems (IS) that employ artificial intelligence (AI) and related techniques. Examples of such techniques are: data analytics, data and process mining, image analysis, knowledge graphs, machine learning, natural-language understanding, predictive modelling, and semantic technologies. https://www.uib.no/en/rg/i2s |
 Image Processing | Statistics and data science. Statistics is a field within mathematics that deals with the principles and methods for collecting and analyzing quantitative information, based on models and concepts from probability theory. https://www.uib.no/en/math/62813/statistics-and-data-science |
 The Digital Culture Research Group | Image Processing. In our modern society, mathematical imaging, image processing and computer vision have become fundamental for gaining information on various aspects in sciences, and technology as well as in the public and private sectors. Technically, imaging and vision are concerned with the computation, visualisation and the automatic processing of (digital) data. https://www.uib.no/math/92149/bildebehandling-image-processing |
 MediaFutures: Research Centre for Responsible Media Technology & Innovation | The Digital Culture Research Group gathers researchers and post-graduate students from different humanities disciplines who share an interest in studying how technology and culture interact. Current research is on topics including intercultural uses of technology, self-representation in social media, critical digital editions, and the cultural implications of machine vision. https://www.uib.no/en/rg/digitalculture |
 SFI Smart Ocean - Technology for monitoring and management of a healthy and productive ocean | MediaFutures: Research Centre for Responsible Media Technology & Innovation. The main objective of the centre is the development of responsible media technology, in particular leveraging AI technology, for the media sector. https://mediafutures.no/ |
 Centre for Cancer Biomarkers (CCBIO) | SFI Smart Ocean - Technology for monitoring and management of a healthy and productive ocean. SFI Smart Ocean is a centre for research-based innovation, working to develop underwater wireless communication along the coast of Norway, for the benefit of science and industry. Les mer her. |
 Mohn Medical Imaging and Visualization Centre | Centre for Cancer Biomarkers (CCBIO) is a Centre of Excellence at the Faculty of Medicine, University of Bergen. The center is working on new cancer biomarkers and targeted therapy, and has particular focus on mechanisms that show how cancer cells are affected by the microenvironment in the tumors, and what significance this has for cancer proliferation and poor prognosis. https://www.uib.no/ccbio |
 The Centre for the Science of Learning & Technology (SLATE) | Mohn Medical Imaging and Visualization Centre. The aim of the Centre is to research new methods in quantitative imaging and interactive visualization to predict changes in health and disease across spatial and temporal scales. This encompassed research in tissue feature detection, feature extraction and feature prediction. https://mmiv.no/ |
 | The Centre for the Science of Learning & Technology (SLATE) is an R&D learning sciences unit, which contributes to international research and national competence development on the use data and data approaches in understanding education and lifetime learning. https://slate.uib.no/ |
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The Centre for Social Algorithms
| The Centre for Social Algorithms research how to design algorithms for the computation needs of today. Algorithms are designed for optimal use of computing time and memory. This was good enough when only trained professionals worked with computation. Today, computers are part of our society and we all interact with them. How well algorithms serve the interest and wellbeing of people also needs to be part of the algorithm design. This is what we explore at the centre. www.uib.no/en/csa |