Investments overview
1852 investments
Title Sort descending | Period | Programme | |
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ADRIMON | 2020 - 2022 | International collaborations
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ADRIMON
Period
2020 - 2022
Region
Program
Internationalt samarbejde Area
Produktion, Materialer, Digitalisering og IKT Investment
Percentage
55.5 Invested
2.3 mill. Budget
4.2 mill. Realize the potential of AI for wind turbine vibration monitoring to boost asset performance and thus accelerate the transition towards a society powered by renewable energy.
Partners
Vertical AI ApS, Enel Green Power Espana SL People
Aktiv
Read more about the project
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Advanced Accurate and Computationally Efficient Numerical Methods for Wind Turbine Rotor Blade Design | 2017 - 2020 | Industrial Researcher
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Advanced Accurate and Computationally Efficient Numerical Methods for Wind Turbine Rotor Blade Design
Period
2017 - 2020
Region
Program
Erhvervsforsker Area
Energi, Klima og Miljø Investment
Percentage
58.45 Invested
1.1 mill. Budget
1.8 mill. This project develops novel advanced computational models and methods for structural optimization based wind turbine rotor blade analysis. The models and methods are implemented into LM’s in-house cross section analysis tool LMBlades as integral part of the blade design workflow of LM Wind Power. The intended outcome of this project is to proof that the gain in accuracy and computational efficiency leads to blade designs with lower weight due to reduced material usage and increased reliability.
Partners
LM WIND POWER A/S Danmarks Tekniske Universitet People
Aktiv
Read more about the project
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Advanced characterization of large scale fermentations | 2019 - 2021 | Industrial Researcher
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Advanced characterization of large scale fermentations
Period
2019 - 2021
Region
Program
Erhvervsforsker Area
Biotek, Medico og Sundhed Investment
Percentage
46.94 Invested
828.000 Budget
1.8 mill. The lack of knowledge of the heterogeneous process condition in the large-scale reactors is a major challenge for bioindustries. This project aims to tackle this problem by establishing validated computational simulations with a novel real-time measurement technology (free-floating sensor device by Freesense) for large-scale fermentations. These simulations could be provided to the bioindustry as a valuable tool to design, evaluate, control and optimize various processes.
Partners
Freesense Aps, Danmarks Tekniske Universitet People
Aktiv
Read more about the project
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Advanced Chromatographic Methods for Analysis of Small Oxygenates from Sugar Processing | 2017 - 2020 | Industrial Researcher
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Advanced Chromatographic Methods for Analysis of Small Oxygenates from Sugar Processing
Period
2017 - 2020
Region
Program
Erhvervsforsker Area
Produktion, Materialer, Digitalisering og IKT Investment
Percentage
40.74 Invested
1.1 mill. Budget
2.6 mill. Projektet vil udvikle analytiske værktøjer som gør det muligt at identificere og kvantificere produkter som dannes ved termisk og katalytisk omdannelse af sukker. Disse værktøjer vil bestå af avancerede kromatografiske separationsteknikker som kan adskille produkterne, i kombination med høj-opløseligt massespektrometri til identifikation. De analytiske metoder vil skabe en bedre forståelse af de kemiske reaktioner som finder sted når sukkermolekyler omdannes i katalytiske processer.
Partners
Københavns Universitet, Haldor Topsøe A/S People
Aktiv
Read more about the project
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Advanced freeze valves for energy production and conversion systems using molten salts | 2020 - 2023 | Industrial Researcher
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Advanced freeze valves for energy production and conversion systems using molten salts
Period
2020 - 2023
Region
Program
Erhvervsforsker Area
Energi, Klima og Miljø Investment
Percentage
55.58 Invested
1.1 mill. Budget
1.9 mill. Dette projekt undersøger innovation indenfor såkaldte fryse-ventiler til brug i nye reaktor typer samt i CSP. Fælles for de to er brugen af smeltet salt ved høje temperaturer, samt nødvendigheden af komponenter med passiv sikkerhed, skulle salten blive for varm (f.eks. ved pumpefejl). Projektet udvikler ventiler med komponenter der automatisk smelter i sådanne tilfælde, hvormed salten kan køles. Projektet skal bruges i Seaborgs reaktordesign samt åbne for brugen af flour-salte i CSP.
Partners
Seaborg ApS Technical University of Denmark People
Aktiv
Read more about the project
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Advanced Machine Learning for Automated Omni-Channel Support | 2018 - 2020 | Grand Solutions
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Advanced Machine Learning for Automated Omni-Channel Support
Period
2018 - 2020
Region
Program
Grand Solutions Area
Produktion, Materialer, Digitalisering og IKT Investment
Percentage
46.04 Invested
5.2 mill. Budget
11.2 mill. In the description below we refer to the work packages, deliverables, and milestones described in the Work Plan section. An overall timeline of the project is illustrated in Appendix A.
The project consists of several partners: Department of Computer Science, University of Copenhagen (from hereon DIKU), who will head the research of the project. Several industry partners (listed previously), who will provide large amounts of support data including tickets, refining the business case and assist with integration and validation/testing. Finally, SupWiz will head the development part of the project and assist with the research. SupWiz will collaborate with the industry partners on data collection and preparation as well as integration and testing. This includes developing technologies for tying everything together in the different channels of support employed by the industry partners (social media, chat bots, e-mail, etc.).
The overall structure of the project (described in more detail below) is to have a specification phase, proof of concept phase, agile “mini-projects” of, and a generalization phase. In parallel with this, there will be a research track, which feeds into the mini projects.
Each mini-project lasts roughly six months and will work through all three stages of the value chain (from research to testing/validation). The mini projects will use the experience and results from the previous phases as well as the research of the project to collect relevant data, refine the features developed during previous phases, and develop new components. Each mini project ends with integrating and testing in collaboration with the industry partners. The research will feed into the project in the speed results are delivered, and one mini project will contain refinement of the technology based on both new results and experience from previous stages. In this way, partners can be engaged from the beginning and work on integration even before the final results are delivered and implemented.
In the generalization track, the goal is to continuously refine the features developed during the project and extract several generic components, which can be further developed, packeted, and marketed as a suite of independent components which can be plugged into existing support systems (such as the systems used by the project partners).
SupWiz will be the main responsible party for coordinating between the project partners. This is elaborated further in the project governance section. During the specification phase SupWiz will take special care to account for the diversity of the industry partner involved in the project. This diversity will ensure that the project results in not only customized intelligent support solutions for the involved parties, but also a generic suite of components of independent interest as described above.
The research of the project will be split into three work packages with focus on (WP1) question answering, (WP2) ticket routing / expert finding, (WP3) efficient algorithms. Here, WP3 will be focused on refining the methods developed in WP1 and WP2 from an algorithmic perspective.
We propose a way to efficiently use deep learning for domain-specific question answering (WP1), covering both factoid and more subjective questions. This is a novel combination, since deep learning requires a lot of training data and is therefore not applicable in small domains, but also there has been very little work, in general, on automatic answering of more subjective questions. We do this in three phases: Knowledge base population, question generation, and question matching. This approach should work well for FAQs, but for tickets there may be several embedded questions and background information, which we will handle using summarization based on different types of parsing.
For ticket routing (expert finding, WP2) we propose a two-phase pipeline using online learning, which has not been previously done. In phase 1 we will use advanced data mining to extract expertise indicators for each candidate entity in an organization, and in phase 2 experts will be ranked using a type of online learning called multi-armed bandits.
It is the intention to connect the project to the Danish Center for Big Data Analytics Driven Innovation (DABAI) to facilitate maximum synergy with the leading BigData research center in Denmark. The project team is in talks with the DABAI leadership about this.
SupWiz is also currently in the process of appointing an advisory board consisting of international experts from both the academic and business world, and is able, through the company’s founders’ and investors’ large networks, to get world-leading experts.
In order to accommodate the research of the project, DIKU will hire one 2-year PostDoc and one 1-year student programmer. SupWiz will also hire one full-time resource with a strong theoretical background in algorithms and ML, which assist the remaining SupWiz staff.
Partners
SupWiz ApS, University of Copenhagen, Edulab, Københavns Kommune, Lix Technologies, MaCom, NNIT A/S People
Aktiv
Read more about the project
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Advanced methods for blade MOnitoring UNder full-scale Testing (AMOUNT) | 2018 - 2022 | Industrial Researcher
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Advanced methods for blade MOnitoring UNder full-scale Testing (AMOUNT)
Period
2018 - 2022
Region
Program
Erhvervsforsker Area
Produktion, Materialer, Digitalisering og IKT Investment
Percentage
45.4 Invested
1.1 mill. Budget
2.4 mill. Formålet med projektet er at udvikle metoder til at analysere det globale respons samt vækst af skader i vindmøllevinger udsat for forskellige udmattelsestest. Projektet sigter mod at udvikle eksperimentelle metoder til at måle og overvåge vindmøllevinger i under fremtidens fuldskala test, som forventes at blive mere komplicerede for bedre at repræsentere de virkelige laster.Målet er også at udvikle numeriske metoder, som kan bruges til at simulere, hvordan de eksperimentelle målemetoder virker.
Partners
Danmarks Tekniske Universitet, KRÜGER A/S People
Aktiv
Read more about the project
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Advanced model development and validation of Wind Turbine Active Flap system | 2020 - 2023 | Industrial Researcher
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Advanced model development and validation of Wind Turbine Active Flap system
Period
2020 - 2023
Region
Program
Erhvervsforsker Area
Energi, Klima og Miljø Investment
Percentage
31.44 Invested
1.1 mill. Budget
3.4 mill. Projektets formål er numerisk demonstration og empirisk validering af modeller og strategier for lastreduktion ved hjælp af active flap til anvendelse på store møllevinger og andre hovedkomponenter. Projektet fokuserer på designdrivende lasttilfælde, som har stor industriel relevans specifikt til offshore vindmøller. Last reduktionen har en umiddelbare konsekvens: reduktion af LCOE
Partners
Siemens Gamesa Renewable Energy A/S, Danmarks Tekniske Universitet People
Aktiv
Read more about the project
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Advanced modelling for prediction and control of related substances in an antibiotic fermentation processes | 2019 - 2022 | Industrial Researcher
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Advanced modelling for prediction and control of related substances in an antibiotic fermentation processes
Period
2019 - 2022
Region
Program
Erhvervsforsker Area
Biotek, Medico og Sundhed Investment
Percentage
47.73 Invested
1.1 mill. Budget
2.2 mill. For at kunne hjælpe så mange patienter som muligt, er det nødvendigt at nedbringe omkostningerne ved lægemiddelproduktion. Det er dyrt og risikabelt at foretage ændringer i de farmaceutiske produktionsprocesser. En af de bedste måder at mindske risici er udviklingen af effektive forudsigelige procesmodeller. I dette projekt vil vi udvikle nye og innovative modeller ved hjælp af store datasæt med det formål at minimere produktionen af uønskede stoffer ved proces skalaer over 25 kubikmeter.
Partners
LEO PHARMA A/S, Danmarks Tekniske Universitet People
Aktiv
Read more about the project
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Advanced Pirate Fence | 2018 - 2019 | Innobooster
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Advanced Pirate Fence
Period
2018 - 2019
Region
Program
Innobooster Area
Infrastruktur, Transport og Byggeri Investment
Percentage
32.92 Invested
1.8 mill. Budget
5.3 mill. Hvor nuværende anti-pirat sikring af tankere og containerskibe ligner befæstninger fra 2. verdenskrig, vil Nordreps Advanced Pirate Fence tilbyde en simpel løsning med avanceret teknologi, der vil gøre det både let og effektivt at sikre skibe mod kapring. Løsningen reducerer omkostningerne til installation af værnemidler med en faktor 10, samtidig med at risikoen for skader på mandskab og materiel under installation reduceres til en minimum.
Partners
Nordrep A/S People
Aktiv
Read more about the project
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Advanced process models for analysis and process control of continuous casting of iron | 2019 - 2022 | Industrial Researcher
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Advanced process models for analysis and process control of continuous casting of iron
Period
2019 - 2022
Region
Program
Erhvervsforsker Area
Produktion, Materialer, Digitalisering og IKT Investment
Percentage
61.08 Invested
1.1 mill. Budget
1.8 mill. It is the project´s aim to create a fast, reliable closed-loop control system for Tasso´s continuous casting unit that will increase the company´s product quality and production rate. Such systems do not exist today and will have to be developed from a thorough experimental analysis combined with application of numerical
modelling of the casting process. The project should lead to a first version of a closed-loop control system.
Partners
A/S TASSO ODENSE, Danmarks Tekniske Universitet People
Aktiv
Read more about the project
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Advanced wound care adhesives with new functional properties. | 2017 - 2020 | Industrial Researcher
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Advanced wound care adhesives with new functional properties.
Period
2017 - 2020
Region
Program
Erhvervsforsker Area
Biotek, Medico og Sundhed Investment
Percentage
50.23 Invested
1.1 mill. Budget
2.1 mill. Projektet søger at løse de væsentligste bivirkninger ved brug af Silikone hudklæbere til Sårbandager, som er begrænset fugthåndtering samt dannelse af Biofilm, med inkludering af Glyceroldråber i Silikone klæberen.
Dernæst skal inkludering af antimikrobielle stoffer i Glyceroldråberne undersøges for deres indflydelse på Biofilm.
Projektet skal i videst mulig omfang også undersøge opskalering af processen, som demonstrerer at klæberne kan produceres i en industriel virkelighed.
Partners
Coloplast A/S Technical University of Denmark People
Aktiv
Read more about the project
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Advancing biological solutions for biofouling | 2019 - 2022 | Industrial Researcher
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Advancing biological solutions for biofouling
Period
2019 - 2022
Region
Program
Erhvervsforsker Area
Biotek, Medico og Sundhed Investment
Percentage
56.02 Invested
1.1 mill. Budget
1.9 mill. Bakterier i biofilm er indkapslet i en beskyttende matrix, og de tåler derfor biocider og antibiotika. Formålet med dette projekt er at udvikle en high-throughput screenings-platform til identifikation af enzymkombinationer som nedbryder biofilm. Samtidig opnås viden om hvilke makromolekyler der beskytter bakterierne mod biocider. Projektet vil give både ny viden om biofilms sammensætning, og tage det første skridt mod udvikling af biocid-frie enzymbaserede løsninger til biofilm kontrol.
Partners
Novozymes A/S Aarhus University People
Aktiv
Read more about the project
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Advancing KP405 - A Novel, First-in-Class, Disease Modifying Treatment for Parkinson's Disease | 2019 - 2020 | Innobooster
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Advancing KP405 - A Novel, First-in-Class, Disease Modifying Treatment for Parkinson's Disease
Period
2019 - 2020
Region
Program
Innobooster Area
Biotek, Medico og Sundhed Investment
Percentage
33 Invested
4.0 mill. Budget
12.0 mill. Efficacy of KP405 has been extensively characterized in multiple animal models of neurodegeneration. This proposal has been submitted with the purpose to advance the development of KP405 to human trials. Specifically, this proposal entails completion of the manufacturing and toxicity studies of KP405 in animals, required for regulatory submission of an investigational new drug (IND)/clinical trial application (CTA) and subsequent evaluation of safety, tolerability, and efficacy in humans.
Partners
Kariya Pharmaceuticals IVS People
Aktiv
Read more about the project
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Affaldssortering - fra uoverskueligt besvær til ubemærket rutine | 2019 - 2022 | Industrial Researcher
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Affaldssortering - fra uoverskueligt besvær til ubemærket rutine
Period
2019 - 2022
Region
Program
Erhvervsforsker Area
Handel, Service og Samfund Investment
Percentage
53.76 Invested
1.1 mill. Budget
2.0 mill. Med afsæt i en praksisteoretisk tilgang kombineret med perspektiver fra forbrugs- og hverdagslivsstudier skal projektet skabe forståelse af den hjemlige sammenhæng, affaldssortering finder sted i. Ved at belyse hvilke træk ved disse omgivelser der understøtter eller blokerer sorteringspraksis vil projektet kvalificere danske affaldsselskabers fremtidige indsats for at få borgerne til at sortere mere og bedre. Den praksis- og kontekstorienterede tilgang til studiet af affaldssortering er ny.
Partners
Dansk Affaldsforening, Aalborg Universitet People
Aktiv
Read more about the project
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