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Limb wounds in horses are common, however healing is exceedingly slow and fraught with complications. Contrary to body wounds, limb wounds demonstrate only a small amount of wound contraction. The specialist procedure of applying split-thickness skin grafts to limb wounds stimulates wound contraction by unknown mechanisms. The objective of this project is to identify those mechanisms to develop a treatment strategy for equine limb wounds for use in general  practice. Limb wounds are severely impacting animal welfare due to an extended healing/treatment duration, and the risk of euthanasia due to a poor functional outcome. By stimulating wound contraction, healing time will be reduced, and the functional outcome improved, directly benefitting the welfare of wounded horse and reducing treatment cost for the owner. Aim: To identify dermal components stimulating wound contraction, and to develop this knowledge into future state-of-the-art treatment of equine limb wounds for use in general practice. Hypotheses: i) Application of dermal fractions to collagen gels seeded with equine fibroblasts will increase gel contraction in vitro; ii) Application of dermal fractions to experimental limb wounds in vivo, will increase wound contraction resulting in a faster healing time versus wounds treated by conventional methods. Methods: i) The contractile effect of different dermal components will be assessed in a collagen gel/ fibroblast model; ii) Identified dermal components will be tested in a standardized experimental limb wound model in vivo (n=5). Ultimately, results from this project are expected to improve wound treatment in horses, directly impacting animal welfare by reducing healing time and improving the functional outcome of wounded horses. This will also directly benefit horse owners and caretakers and making veterinarians able to offer better treatment solutions.

HESTEFORSK - Raskere og bedre sårheling hos hest med autologe hudkomponenter

Prosjektet «Wheelchair Activity Monitoring» (WHAM) sikter både på å øke fysisk aktivitet blant rullestolbrukere, og på å bidra til bredere mål om mangfold og inkludering av personer med nedsatt mobilitet, ved å fremme større tilgjengelighet og deltakelse gjennom innovativ teknologi og forskning.

Rullestolbrukere er tre til fem ganger mindre aktive enn den generelle befolkningen, noe som øker risikoen for å utvikle forebyggbare sykdommer. Selv om det finnes retningslinjer for fysisk aktivitet som er tilpasset rullestolbrukere, trenger vi fortsatt effektive måter å implementere disse på samt nøyaktig teknologi for å spore mulige endringer i fysisk aktivitet. WHAM har som mål å bidra til økt fysisk aktivitet blant rullestolbrukere ved å lage digitale verktøy for å monitorere og gi tilbakemelding på rullestolbrukerens aktivitet. WHAM består av tre faser: to år ved University of British Columbia (UBC), som inkluderer et samarbeid med eksperter innen atferdsendrings-intervensjoner for rullestolbrukere; ett år ved Norges teknisk-naturvitenskapelige universitet (NTNU) og et halvt år ved Maastricht Instruments - de to siste fasene er viet til å utvikle de digitale teknologiene. 

WHAMs mål er:
1)	Å teste effekten av et treningsprogram på fysisk aktivitetsnivå og fitness blant rullestolbrukere,
2)	Å utvikle nøyaktige algoritmer for monitorering av fysisk aktivitet blant rullestolbrukere,
3)	Å lage et system som både monitorerer og gir tilbakemelding på fysisk aktivitet blant rullestolbrukere.

Wheelchair users (WCU) are three to five times more inactive than the general population, leading to a high risk of developing preventable secondary conditions. Although physical activity (PA) guidelines have been specifically developed for WCU, we lack systematic approaches to implement them in practice, as well as valid algorithms to monitor PA change in WCU through sensor-based solutions. Accordingly, the overall scientific aim of the WHeelchair Activity Monitoring project (WHAM) is to advance PA research and practice in WCU by developing valid digital markers for monitoring of and providing feedback on PA, paving the way for implementation and intervention. I will accomplish this through combining the complementary research fields of 1) behavioral intervention studies focusing on increasing PA in WCU (core competence University of British Columbia, UBC; outgoing phase) and 2) sensor-based PA monitoring (core competence Norwegian University of Science and Technology, NTNU; returning phase – consolidated by non-academic placement at Maastricht Instruments, which develop research prototypes including PA monitors). WHAM’s scientific aim is achieved through three objectives: 1) Measure the effect of a pragmatic exercise intervention trial on self-reported physical activity levels and cardio-respiratory fitness, 2) Develop valid algorithms for tracking PA markers in WCU, and 3) Co-create
a framework that outlines how PA can be conjointly monitored and provided feedback on in WCU. This fellowship will enable me to become established as an internationally recognized researcher in the field of “physical activity and disability”, while bringing together ongoing national disjointed research activities in this field. Altogether, my overall ambition is to contribute to reducing inequalities in daily-life participation among WCU compared to the rest of the population.

Topfinancing - WHeelchair Activity Monitoring project (WHAM)

Effektene av fysisk og seksuell vold på ofre og deres familier kan være ødeleggende og vedvarende, med potensielt langvarige konsekvenser for fysisk og mental helse, utdanning, sysselsetting og bruk av velferdstjenester. Mens strafferettssystemet anses som en viktig del av offerets gjenopprettingsprosess, er det begrenset empirisk forskning på hvorvidt strafferettslige prosesser hjelper og/eller hindrer bedring langs disse ulike dimensjonene. I dette prosjektet vil vi adressere dette kunnskapshullet ved å bruke en kombinasjon av kvantitative og kvalitative forskningsmetoder. I de kvantitative analysene vil vi bruke administrative registerdata som dekker hele befolkningen sammen med kvasi-eksperimentelle metoder for å kunne trekke kausale slutninger. Vi vil også benytte maskinlæringsteknikker for prediksjon. De kvalitative analysene vil supplere de kvantitative analysene ved å gi kontekst til et komplekst felt av saker og ofre og ved å identifisere potensielle mekanismer mellom strafferettslige prosesser og utfall for ofrene. Samlet vil disse metodene gi en mer robust, representativ og nyansert forståelse av hvordan kontakt med strafferettssystemet påvirker offeret på tvers av flere viktige livsområder både på kort og lang sikt. Prosjektet ledes av Folkehelseinstituttet (FHI) med Frischsenteret og Universitetet i Oslo som partnere. Prosjektet har et rådgivende utvalg med medlemmer fra Nasjonalt kunnskapssenter om vold og traumatisk stress (NKVTS), ETH Zurich, Universitetet i Oslo, Frischsenteret, Universitetet i Bergen, og OsloMet. Det er også tilknyttet en brukergruppe bestående av personer og organisasjoner som er i kontakt med ofre for vold og overgrep.

Victims of sexual and physical violence is one of the most vulnerable groups in our society. The criminal justice system (CJS) serves a critical role in providing assistance to victims of these crimes, enabling them to seek justice, protection, compensation, and closure. Yet, knowledge about whether the CJS helps or harms these victims is extremely limited. This project aims to remedy this by providing a comprehensive understanding of the role of the CJS in supporting and providing restoration for victims of physical and sexual violence in Norway. We will utilize a combination of quantitative and qualitative research methods across disciplines to study outcomes across multiple important life domains, both in the short and long run. For the quantitative analyses we will use exceptionally rich longitudinal administrative register data with full population coverage combined with state-of-the-art quasi-experimental methods for credible causal inference and predictive machine learning techniques. The qualitative analysis will be based on narrative interviews with victims, providing context and insights into how interactions with the CJS shape life stories. The results will yield a robust and nuanced understanding of how the different stages of the CJS impacts victims. This is particularly urgent given how the current emphasis on legal responses to assaults has caused a sense of obligation and civic duty for especially women to report incidents, while the chances of legal closure remain small. In addition to advancing the methods for quasi-experimental designs and machine learning within quantitative criminology, this project will provide valuable insights for policymakers, stakeholders, and practitioners working in the field of victim support and rehabilitation and may inform current legal reform efforts aimed at addressing these issues.

Helpful or harmful: The effects of criminal justice system contact on victims of sexual and physical violence

The goal of the Bilingual Experiences, Cognitive Ageing and underlying Mechanisms (BECAME) project is to examine the functional neuroplastic mechanisms underlying mitigatory effects of bilingual experience on age-related cognitive decline. While evidence is available for structural brain changes supporting bilingualism-induced effects on cognitive aging (CA), functional mechanisms underlying such effects are not yet well understood. BECAME aims to fill this gap by investigating the trajectory of bilingualism-induced functional neuroplasticity across the adult lifespan (ages 18-85), crucially adopting an individual differences approach related to measurable degree of bilingual engagement. Importantly, although such benefits are thought to be rooted early in the lifespan, evidence for the timeframe and conditions of their early emergence is scarce. The choice of including the whole adult lifespan allows us to investigate these mechanisms and their emergence more directly from a lifespan perspective. I combine behavioral testing with brain recordings via electroencephalography (EEG). EEG is widely used in cognitive neuroscience to assess brain activity and the degree of communication between brain regions (functional connectivity) in response to stimuli and at rest. Combining behavioral and EEG modalities will allow me to test bilingualism’s effect on functional connectivity, as well as its consequences for functional efficiency, the minimum required neural activation to successfully perform a task. This will enable a detailed, evidence-based account of the protective effects observed in older-aged bilinguals, and how they are built from earlier life stages. By illuminating the relationship between multilingualism and resulting neurocognitive adaptations, BECAME will enable to capitalize on it as a health initiative, with manifold societal implications and the potential to be translated into actionable policies exploiting multilingualism to ameliorate effects of CA.

Bilingual Experiences, Cognitive Ageing and underlying Mechanisms

From the SEA to the SOLution. An integrative assessment of marine pollution in a changing Arctic

Marine chemical pollution poses known threats to human health and to biodiversity, ecosystem and societal services. The Arctic is a major sink of global mercury (Hg) pollution. Arctic sediments, sea and glacial ice constitute vast Hg reservoirs. Recent studies raise concerns about their increasing role as local Hg sources. In a rapidly warming Arctic, the consequences of potentially increased environmental Hg on marine biota remain unknown. The objective of SEASOL is to identify the pathway(s) of Hg bioaccumulation in marine food webs of the High Arctic Kongsfjorden (Svalbard). This changing glacial fjord is recognised as a ‘natural laboratory’ of climate change in the Arctic. The fellow’s earlier research has shown the sole measurement of Hg levels as insufficient to connect biotic Hg dynamics to environmental change, whereas the analysis of Hg stable isotopes proved to be a promising tool for source discrimination and biotic transfer. SEASOL will build on the novel application of stable isotope analysis to identify the sources of Hg within the fjord system and the pathways to Hg accumulation within sentinel marine species. On the short-term, the study will provide fundamental knowledge to help understand how emerging sources of Hg from rapid environmental change will impact Arctic marine predators. On the long-term, SEASOL will contribute to the development of early-warning, adaptive management strategies, including modelling, for mitigating the cumulative impact of pollutants and climate change on Arctic marine species. This multidisciplinary approach and the central position of the host institution (Norwegian Polar Institute) in the field of Polar Research will equip the Fellow with a broad set of new skills and lay the foundation for building her specific niche as a future leader in marine pollution science.

Reality-Connected Machine Simulation of Heavy Machinery

The RealSim project proposal aims to connect machine simulation to reality in the framework of heavy machinery, which is an interdisciplinary application. The results of this project are expected to optimize machine performance, accurately and reliably predict machine failure, and reduce overall development and operation costs, thus, serving the Europe’s priority of green transformation and the United Nation’s sustainable development goal 9. The RealSim project will close the gaps of: (1) Onboard estimations of force and pressure components of heavy machinery; (2) Estimating deformability, cylinder friction, leakage, and valve dynamics of heavy machinery using independent nonlinear Kalman filters; (3) Employing dependent nonlinear Kalman filters in state estimators of heavy machinery; (4) Tuning algorithms for the covariance matrix of plant noise in the state estimation of heavy machinery. 

I will consolidate and leverage my research career and position as a leading researcher in the field through integration in Assoc. Prof. Mohammad Poursina’s group at the Department of Engineering Sciences of the University of Agder (UiA), Norway. Here, I will acquire hands-on experience of working with actual mechatronic systems and develop efficient control algorithms. I will improve my knowledge of fluid power designing, control theory, instrumentation, and develop efficient coding skills. I will also develop entrepreneurial skills. The skills, knowledge, and international network that I will develop during this fellowship will put me in an excellent position to achieve my long-term goal of becoming a professor with my own independent research group at an esteemed university in EU. This fellowship will help me to prepare a strong ERC Starting Grant application in the future. It will also cater my additional goal of setting-up a research-related start-up in the future.

Information theory is a discipline at the intersection of statistics, engineering and computer science. As the study of information quantities, such as compression or communication capacities, information content or measures of statistical dependency, it is one of the theoretical underpinnings of data science.

Computational problems in information theory are highly non-linear. The goal of this project is to transfer state-of-the-art methods of computational non-linear algebra to information theory, to study the inherent algebraic complexity of information-theoretical problems and to provide tools for solving them in practice. The algebraic point of view has proven to be fruitful in seemingly unrelated areas, as witnessed by a surge of recent work in algebraic statistics, in particular on likelihood geometry. However, maximizing the likelihood function is the same as minimizing relative entropy — a specific information quantity. Hence, this project also aims at generalizing the techniques developed in likelihood geometry.

One focus is on the practical computation of information quantities using numerical and differential algebraic geometry. Such quantities are defined via non-linear optimization problems and we aim to pinpoint the algebraic complexity of these problems in instances of general interest, such as common information measures. The final objective is finding fundamental laws and limits of data science imposed by non-linear inequalities constraining the entropic region. These inequalities provide, by duality, universal bounds for many of the optimization problems studied in information theory.

Algebraic Theory of Information Quantities

Enabling the next generation in search of blood cancer cures

The CarrerasPathfinder program is new a world-wide unique doctoral program that covers the entire spectrum of research and innovation in blood cancers from understanding disease biology to the implementation of novel processes in the clinical practice. The program will fund 14 excellent Doctoral Candidates (DCs) for a period of 48 months. DCs will perform collaborative PhD projects involving associated partners from different sectors, countries, and disciplines through secondments. DCs will improve their research capacity and transferable skills through high-quality supervision arrangements and a tailored training program.

The program has been designed and will be hosted by the Josep Carreras Leukaemia Research Institute (IJC) which is the first European non-profit institute exclusively devoted to blood cancers. By answering the European needs for human resources, it is fully aligned with the 13 recommendations of the EU Cancer Board’s Draft Mission  and the Europe’s Beating Cancer Plan (2021). The CarrerasPathfinder program has a strong triple-I dimension of internationality, inter-sectorality and interdisciplinarity in training, networking, co-supervision and research. Its specific objectives are:
•	To develop an excellent doctoral program in blood cancer research conceived as a pilot for a permanent international doctoral program
•	To equip DCs with a unique skill set boosting effectiveness and innovation capacity. 
•	To promote DCs’ career development and increase their employability in different sectors.
•	To establish the IJC as a European reference for research and training in blood cancers.
•	To provide Europe with a new generation of researchers able to address unmet needs and societal challenges of blood cancers.
•	To contribute to structuring the European research area by collaborating and synergizing with other European key opinion leaders.



Tenk på universet som en enorm ballong som alltid utvider seg. Jo lenger unna et punkt er på ballongen, jo raskere beveger det seg bort fra deg. Dette ligner på hvordan universet utvider seg, jo lenger unna en galakse er, jo raskere beveger den seg bort fra oss på jorden.

I mange år trodde forskerne at universets ekspansjon ble bremset. Begrunnelsen deres var at gravitasjonskraften fra all materie i universet virket mot denne utvidelsen. Imidlertid gjorde kosmologer i 1998 en overraskende oppdagelse gjennom studiet av fjerne supernovaer: utvidelsen av universet akselererer faktisk!

Dette betyr at avstanden mellom galaksene blir større og større i stadig økende hastighet. Det er som om ballongen blåses opp raskere og raskere.

Forskere vet ikke nøyaktig hva som får universet til å akselerere. De kaller den ukjente kraften som får dette til å skje "mørk energi". Mørk energi er overalt i universet, men den mørke energien vekselvirker ikke med materie i de formene som vi kan observere direkte.

NEVO-prosjektet er et nytt forsøk på å forstå egenskapene til mørk energi. NEVO vil bruke kraftige datamaskiner for å simulere universet og studere effekten av kandidater til den mørke energien på en måte som aldri har vært gjort før. Ved å studere disse simuleringene og utnytte høypresisjons-observasjonene fra Euclid-teleskopet som nylig er skutt opp i rommet, vil kosmologene være i stand til å bedre betydelig vår forståelse av den mørke energiens gåtefulle natur.

The Universe has entered an accelerating expansion phase in the last few billion years of its evolution, a phenomenon that is caused by the mysterious entity known as dark energy. Through the NEVO proposal, I aim to provide key insights about the properties of dark energy, which includes its time evolution and spatial distribution in the Universe. This objective will be achieved by utilizing cutting-edge cosmological N-body simulations and novel techniques to study cosmic EVOlution accurately.

A comprehensive understanding of the nature of dark energy requires a thorough investigation of viable candidates and their impact on different stages of the Universe. However, the consistent and accurate modeling of dark energy candidates has been largely neglected so far. To address this gap, I propose the development of a novel, integrated framework that utilizes state-of-the-art relativistic N-body simulations along with the hi_class code, to accurately model dark energy candidates in both linear and non-linear scales.

NEVO: illuminating the dark cosmos

Global natur- og miljøforvaltning er en av vår tids mest sentralt og vanskellige mål. Mange av utfordringene skyldes motsetningene mellom vår fragmenterte politiske verden og økosystemer som ikke forholder seg til landegrenser eller politiske skillelinjer.
Ulike biologiske samfunn (biomer) som ligger i én stat, kan ikke løsrives fra et større økosystem. Derfor er flere «lokale» naturområder blitt del av den globale miljøforvaltningen.
Prosjektet RESOLVING skal se på politiske løsninger for en naturforvaltning som både er:
(i) lokal: som del av en stats territorium og hjem til ulike befolkningsgrupper
(ii) global: som kritiske deler av planetens økosystem
Hva betyr denne forvaltningen på flere nivåer for staters suverenitet?
Vi vet allerede mye om utfordringene nasjonalt oppdelt myndighet utgjør for effektiv forvaltning av jordens økosystemer. Vi vet derimot langt mindre om hvordan forsøkene på å styre jordens komplekse og grenseløse økosystemer faktisk kan endre selve systemet som forsinker den globale forvaltningen: statlig suverenitet.
RESOLVING vil prøve å forstå denne dynamikken ved å undersøke gruppene som faktisk utøver internasjonal naturforvaltning på vegne av eller parallelt med statene. Prosjektet vil her se nærmere på styringen av to områder som er viktige for hele verden: Amazonas-regnskogen og Guineabukta.
RESOLVING undersøker hvordan tiltak for å ta vare på disse områdene – laget på både internasjonalt, nasjonalt og lokalt nivå – fungerer sammen. Hvilke aktører får mer makt? Hvem blir inkludert i beslutningsprosessene og hvem blir utelatt?

The RESOLVING project asks: How does global governance of nature transform the exercise of sovereign power? Scientific evidence of the environment as a complex system of planetary dimensions has elevated several natural resources as objects of global governance. Primary forests and maritime biomes particularly capture global attention because of their systemic relevance for our planetary ecosystem. Still, international politics operates within a framework locating authority over nature indivisibly into territorially discrete and independent states. This project investigates the implications for sovereignty stemming from the construction of nature as a global governance object. We build on existing conceptualizations of sovereignty as a combination of de jure sovereign authority and bundles of de facto sovereign competence. In the case of nature, while permanent sovereignty over natural resources is an immutable property of state authority, a wider range of actors can be involved in defining the ways in which these resources are governed or even in governing them. RESOLVING will focus on two parcels of local nature especially entangled in global governance: the Amazon rainforest and the Gulf of Guinea. The project will investigate how networks of actors work across levels of governance to produce sovereign competence and exert sovereign power over nature in these regions. Sovereign power is the capacity to achieve de facto sovereign competence, here identified as the capacity to define and implement the rules of human–nature interaction. We look at multilevel governance from three angles: the global, the state, and the local. The comparative analysis of those networks across levels, regions, and regimes complexes will allow for identifying the mechanisms driving the rebundling of sovereign power with or away from the state, and a better understanding of the consequences of that process.

Rebundling sovereignty over local nature in global governance

Midlene fra PUBL-Publisering/prosjektinform fordelt på år

Midlene fra PUBL-Publisering/prosjektinform fordelt på fylker

Midlene fra PUBL-Publisering/prosjektinform fordelt på fagområde

Professor

Prosjektet innledes med en fremstilling av forutsetningene for katolisismens politiske teologi: bibelske og oldkirkelige motiver, omsatt i Augustins historieteologi og den thomistisk-aristoteliske naturrettsteori. Deretter følger en fremstilling av det liberale demokratiets ideologiske røtter i nytidens politiske filosofi hos Thomas Hobbes, John Locke, Jean-Jacques Rousseau, Immanuel Kant og teoretikere bak den store franske revolusjon. Så tas pavestolens kritikk og kamp med demokratiet under 1800-tallet opp til analyse og utsoningen frem mot og under den annen verdenskrig. Det blir lagt vekt på den filosofiske og teologiske utvikling av katolske tenkning fram mot Det annet vatikankonsil. Konsilet og dets etterhistorie blir bredt analysert. Dernest bidragene fra de fire siste paver.

The Catholic Church and the Liberal Democracy

The conference is non-profit and will be organized at UiT The Arctic University of Norway. The team has previously organised SCIA 2017, and NLDL 2018/2019/2020/2021/2022/2023, which received support for the events from NFR and were successes. The group has several projects ongoing related to ICT and this conference will benefit those projects.

The conference program will consist of presentations and poster sessions, where participants can present recent and
ongoing work. Participants that would like to present their work have submitted a two-page abstract or a full
six-page paper. Full papers are published in the NLDL proceedings (Level 1 in the Norwegian system). Additionally, there will be a panel discussion, where issues and recent developments in the field will be discussed, as well as dedicated events for "Industry in AI" and "Diversity in AI". We have invited 4 high-profile keynote speakers. This will contribute to the quality and also increase the visibility of the conference.

We will use the conference organizing company Xtenso AS, who will provide help with setting up registration.
We expect 250 participants this year. Expenses for the keynote speakers as well as lunch and dinner for the physical
participants will be covered. This results in an overall direct cost of 555 KNOK (see budget below).
To cover costs, UiT The Arctic University of Norway contributes with 55KNOK (50 hours at an hourly rate of 1100,-
NOK) of Kampffmeyer’s and Jenssen's salary. Additionally, 74 KNOK internal funding and 80 KNOK from industrial sponsors will be used to organize the conference in 2024. Budgeting for 250 participants, this means that we estimate a deficit of 100 KNOK and we hope that with help of 100 KNOK from NFR we will be able to roughly break-even.

Northern Lights Deep Learning Conference 2024

The conference is non-profit and will be organized at UiT The Arctic University of Norway. The team has previously organised SCIA 2017, and NLDL 2018/2019/2020/2021/2022, which also received support for the events via the IKTPLUSS funding and were successes. The group has several projects ongoing related to ICT and funded over IKTPLUSS, and this conference will benefit those projects. 
The conference program will consist of presentations and poster sessions, where participants can present recent and ongoing work. Participants that would like to present their work will be asked to submit a two-page abstract or a full six-page paper. Additionally, there will be a panel discussion, where issues and recent developments in the field will be discussed. We have invited 4 high-profile keynote speakers. This will contribute to the quality and also increase the visibility of the conference.
We will use the conference organizing company Xtenso AS, who will provide help with setting up registration.
We expect 250 participants this year. Expenses for the keynote speakers as well as lunch and dinner for the physical participants will be covered. This results in an overall direct cost of 480 KNOK (see budget below).
To cover costs, UiT The Arctic University of Norway contributes with 44KNOK (40 hours at an hourly rate of 1100,- NOK) of Kampffmeyer’s and Jenssens salary. Additionally, 190 KNOK internal funding will be used to organize the conference in 2023. Budgeting for 250 participants, this means that we estimate a deficit of 100 KNOK and we hope that with help of 100 KNOK from IKTPLUSS we will be able to roughly break-even.

Northern Lights Deep Learning Conference 2023

The conference is non-profit and will be organized at UiT The Arctic University of Norway. The team has previously
organised SCIA 2017, and NLDL 2018/2019/2020/2021, which also received support for the events via the IKTPLUSS funding and were successes. The group has several projects ongoing related to ICT and funded over IKTPLUSS, and this conference will benefit those projects.
This year, due to the Covid-19 situation, the conference will be following a hybrid model, where national and European participants will meet physically, while other international participants will attend digitally.
The conference program will consist of presentations and poster sessions, where participants can present recent and ongoing work. Participants that would like to present their work will be asked to submit a two-page abstract or a full
six-page paper. Additionally, there will be a panel discussion, where issues and recent developments in the field will
be discussed.
We have invited 4 high-profile keynote speakers. This will contribute to the quality and also increase the visibility of
the conference.
We will use the conference organizing company Xtenso AS, who will provide help with setting up registration. 
We expect 200 participants this year. Expenses for the keynote speakers as well as lunch and dinner for the physical participants will be covered. This results in an overall direct cost of 340 KNOK (see budget below). 
To cover costs, UiT The Arctic University of Norway contributes with 44KNOK (40 hours at an hourly rate of 1100,-
NOK) of Kampffmeyer’s and Jenssens salary. Additionally, 140 KNOK internal funding will be used to organize the
conference in 2022. Budgeting for 200 participants, this means that we estimate a deficit of 100 KNOK and we hope that with help of 100 KNOK from IKTPLUSS we will be able to roughly break-even.

Northern Lights Deep Learning Conference 2022

Kunstig intelligens ved hjelp av dyp læring har i de siste årene tatt steget inn i medisinsk bildeprosessering. Drevet av de enorme datamengdene i helsesektoren, representerer disse modellene nå forskningsfronten i blant annet identifisering av hudkreft og detektering av lesjoner. Til tross for det store potensialet disse modellene har til å redusere medisinske kostnader og forbedre behandlingskvalitet, har vi fortsatt ikke sett den utbredte adapteringen av modellene i praksis. Dette er på grunn av modellenes begrensninger: deres manglende evne til å inkludere umerkede data, den begrensede teoretiske forståelsen av deres treningsmekanismer og mangel på tolkbarhet i beslutningsprosessen. MedEx vil utvikle nye, tolkbare algoritmer som også kan lære fra umerkede data, og som kan brukes på tvers av sykehus. Videre vil prosjektet utvikle metoder for å analysere modellene og gi en bedre teoretisk forståelse av treningsmekanismene. Algoritmene vil bli evaluert på en rekke medisinske bildemodaliteter og oppgaver, med spesifikt fokus på tumordeteksjon og påvisning av diabetisk retinopati. MedEx er et ambisiøst prosjekt som muliggjøres gjennom et tverrfaglig konsortium bestående av både nasjonale og internasjonale eksperter innen kunstig intelligens og medisin. Prosjektets resultater vil nå en rekkevidde langt utover helsesektoren og vil bidra til å flytte forskningsfronten innen kunstig intelligens.

A large fraction of the data gathered in health care consists of images and as the field transitions towards data-driven health, the opportunity for clinical decision support systems and thus the need for processing medical images becomes apparent. Deep learning artificial intelligence technologies have emerged as the state-of-the-art for image processing as they achieve unprecedented predictive performance due to their ability to learn complex representations from the input data. However, in safety-critical domains, such as the medical domain, there are key-obstacles that need to be resolved before wide spread adaption in the clinic. Obstacles for Universal Healthcare are the inability of deep learning approaches to provide interpretable solutions, the lack of theoretical understanding of deep learning models, and the lack of annotated patients in the health domain. MedEx will develop interpretable data-efficient methods that are able to use unannotated data and are applicable across hospitals and not limited to a particular imaging protocol. The primary application focus is the detection of lung-cancer from PET/MR/CT images in order to improve early-detection and thereby improve patient survivability and quality of care. The secondary application is diabetic retinopathy detection from fungus images to enable efficient systematic screening. While methodological advances are generic and will impact data-driven health and science beyond, concrete results and outcomes will find application through MedEx's clinical stakeholders. Despite being a high-risk endeavor, the project is feasible due to the combination of a high-quality team, top international collaborators, and direct involvement of clinical stakeholders.

Next Generation Explainable Medical Computer Vision

The workshop is non-profit and will be organized at UiT The Arctic University of Norway. The team has previously organised SCIA 2017, and NLDL 2018/2019/2020, which also received support for the events via the IKTPLUSS funding and were successes. The group has several projects ongoing related to ICT and funded over IKTPLUSS, and this workshop will benefit those projects.
Due to the COVID-19 situation, the workshop will be organised in a hybrid format, where local participants can join physically (following the national guidelines), while other national and international participants will join digitally.
The workshop program will consist of presentations and poster sessions, where participants can present recent and ongoing work. Participants that would like to present their work will be asked to submit a two-page abstract or a full six-page paper. Additionally, there will be a panel discussion, where issues and recent developments in the field will be discussed. 
We have invited 5 high-profile keynote speakers. This will contribute to the quality and also increase the visibility of the workshop. 
We will use the conference organizing company Xtenso AS, who will provide help with setting up registration. Due to the digital nature, we expect more participants this year, estimating a maximum number of participants of 400. For physical participants, we will cover the lunch and the dinner. We will further gift physical participants and keynote-speakers with an NLDL-t-shirt. This results in an overall direct cost of 145 KNOK (see budget below).
To cover costs, UiT The Arctic University of Norway contributes with 44KNOK (40 hours at an hourly rate of 1100,- NOK) of  Kampffmeyer’s and Jenssens salary. Additionally, 75 KNOK internal funding will be used to organize the workshop in 2021. Budgeting for 400 participants, this means that we estimate a deficit of 70 KNOK and we hope that with help of 70 KNOK from IKTPLUSS we will be able to roughly break-even.

Northern Lights Deep Learning Workshop 2021

The workshop is non-profit and will be organized at UiT The Arctic University of Norway. The team has previously organized SCIA 2017, NLDL 2018 and NLDL 2019, which also received support for the events via the IKTPLUSS funding and were successes. The group has several projects ongoing related to ICT and funded over IKTPLUSS, and this workshop will benefit those projects.
The workshop program will consist of presentations and poster sessions, where participants can present recent and ongoing work. Participants that would like to present their work will be asked to submit a two-page abstract or a full six-page paper. Additionally, there will be a panel discussion, where issues and recent developments in the field will be discussed.
We have invited 5 high-profile keynote speakers. This will contribute to the quality and also increase the visibility of the workshop. However, this also leads to expenses, such as plane journeys and hotels, that need to be covered. We estimate these costs to be 40 000 NOK.
In addition to this, we will use the conference organizing company Xtenso AS, who will provide help with setting up registration (e.g. credit card payment, budgets). Overall, we estimate a total of 95 participants, which would result in an overall direct cost of 200 KNOK.
To cover these costs, UiT The Arctic University of Norway contributes with 44KNOK (40 hours at an hourly rate of 1100,- NOK) of Jenssen's and Kampffmeyer's salary. Additionally, 100 KNOK will be used to organize a workshop in 2020. Budgeting for 45 participants, this means that we estimate a deficit of 100 KNOK and we hope that with help of 100 KNOK from NFR we will be able to roughly break-even.

0 projects

IKTPLUSS-IKT og digital innovasjon

Northern Lights Deep Learning Conference 2024

Awarded: NOK 99,999

Project Period: 2024-2024

Location: Troms - Romsa - Tromssa

IKTPLUSS-IKT og digital innovasjon

Northern Lights Deep Learning Conference 2023

Awarded: NOK 99,999

Project Period: 2023-2023

Location: Troms - Romsa - Tromssa

IKTPLUSS-IKT og digital innovasjon

Northern Lights Deep Learning Conference 2022

Awarded: NOK 92,930

Project Period: 2022-2022

Location: Troms - Romsa - Tromssa

FRIPRO-Fri prosjektstøtte

Next Generation Explainable Medical Computer Vision

Awarded: NOK 12.2 mill.

Project Period: 2021-2027

Location: Troms - Romsa - Tromssa

IKTPLUSS-IKT og digital innovasjon

Northern Lights Deep Learning Workshop 2021

Awarded: NOK 45,092

Project Period: 2021-2021

Location: Troms - Romsa - Tromssa

IKTPLUSS-IKT og digital innovasjon

Northern Lights Deep Learning Workshop 2020

Awarded: NOK 99,999

Project Period: 2020-2020

Location: Troms - Romsa - Tromssa