Alisa Lincke
Universitetslektor
Institutionen för datavetenskap och medieteknik
Fakulteten för teknik
- Ph.D. in Computer and Information Science, Linnaeus University, Sweden, 2020
- MSc in Computer and Information Science, Linnaeus University, Sweden, 2013
- MSc in Computer Science, Odesa National Polytechnical University, Ukraine 2012
Alisa Lincke is a researcher in the field of Data Science and Recommender Systems. Her main work is to provide data-driven solutions for effective decision-making or recommendations. It includes understanding the problem domain, data collection, data processing, using machine learning tools, statistical techniques, contextualization tools to provide the solutions to a given problem, and reporting results.
Forskning
- decision-support systems;
- data-driven applications;
- contextualized data-driven applications;
- recommender systems
Mina forskargrupper
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Center for Learning and Knowledge Technologies (CeLeKT) Forskningen inom ämnet medieteknik på Linnéuniversitetet har fokus på mobilitet, sociala medier och lärande, och genomförs främst inom…
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Computational Thinking and Coding Skills in Schools (CoCoS) Forskargruppen Computational Thinking and Coding Skills in Schools arbetar med forskning, undervisning och kurser för kompetensutveckling…
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E-health – Improved Data to and from Patients Forskningen inom e-hälsoområdet vid Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) kommer att resultera i nya metoder för…
Mina pågående forskningsprojekt
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Projekt: Extending design thinking with emerging digital technologies (Exten.D.T.2) Kärnan i detta projekt är antagandet att designtänkande i kombination med framväxande teknologier som artificiell…
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Projekt: Prediktion av läkemedelsrelaterade problem och risker Läkemedelsrelaterade problem är ett stort problem för samhället, särskilt med en åldrande befolkning och ökad användning av läkemedel.…
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Såddprojekt: Användning av naturliga språkmodeller för att extrahera läkemedelsrelaterade problem (NLMED) Det övergripande målet med forskningen i detta såddprojekt inom Linnaeus University Center for…
Mina avslutade forskningsprojekt
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Projekt: Design, utveckling och implementering av en databaserad interaktiv krishanteringsövning med drönarteknik för krishanteringssystemet Projektets syfte är att utveckla en datorbaserad interaktiv…
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Projekt: Digitala simuleringsövningar för samverkande räddningsaktörer Digitala simuleringsövningar baserade på avancerad inspelning med bland annat 360-graderskamera och drönarteknik med fokus på…
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Projekt: Smart cities – projekt Ready Ready-projektet är ett internationellt forskningsprojekt på fem år (2014-2019), finansierat av Europeiska kommissionen, med fokus på att implementera avancerade…
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Såddprojekt: Att använda artificiell intelligens för att upptäcka Acanthamoeba Keratit i ögat - AIDAK-studien Det övergripande målet med forskningen i detta såddprojekt inom Linnaeus University Centre…
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Såddprojekt: Design av en intelligent wearable – DIWAH-studien Det övergripande målet med forskningen i detta såddprojekt inom Linnaeus University Centre for Data Intensive Sciences and Applications…
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Såddprojekt: Läkemedel som ökar risken för biverkningar Det övergripande syftet med detta såddprojekt inom Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) är att…
Publikationer
Artikel i tidskrift (Refereegranskat)
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Lincke, A., Fagerström, C., Ekstedt, M., Löwe, W., Backåberg, S. (2023). A comparative study of the 2D- and 3D-based skeleton avatar technology for assessing physical activity and functioning among healthy older adults. Health Informatics Journal. 29 (4).
Status: Publicerad -
Lincke, A., Roth, J., Macedo, A.F., Bergman, P., Löwe, W., et al. (2023). AI-Based Decision-Support System for Diagnosing Acanthamoeba Keratitis Using In Vivo Confocal Microscopy Images. Translational Vision Science & Technology. 12 (11).
Status: Publicerad -
Lincke, A., Jansen, M., Milrad, M., Berge, E. (2021). The performance of some machine learning approaches and a rich context model in student answer prediction. Research and Practice of Technology Enhanced Learning. 16.
Status: Publicerad -
Lincke, A., Fagerström, C., Ekstedt, M., Löwe, W., Backåberg, S. (2021). Skeleton avatar technology as a way to measure physical activity in healthy older adults. Informatics in Medicine Unlocked. 24.
Status: Publicerad -
Fellman, D., Lincke, A., Berge, E., Jonsson, B. (2020). Predicting Visuospatial and Verbal Working Memory by Individual Differences in E-Learning Activities. Frontiers in Education. 5.
Status: Publicerad -
Fellman, D., Lincke, A., Jonsson, B. (2020). Do Individual Differences in Cognition and Personality Predict Retrieval Practice Activities on MOOCs?. Frontiers in Psychology. 11. 1-10.
Status: Publicerad -
Backåberg, S., Hellström, A., Fagerström, C., Halling, A., Lincke, A., et al. (2020). Evaluation of the Skeleton Avatar Technique for Assessment of Mobility and Balance Among Older Adults. Frontiers of Computer Science. 2.
Status: Publicerad -
Herault, R.C., Lincke, A., Milrad, M., Forsgärde, E., Elmqvist, C. (2018). Using 360-degrees interactive videos inpatient trauma treatment education : design, development and evaluationaspects. Smart Learning Environments. 5.
Status: Publicerad
Konferensbidrag (Refereegranskat)
- Milrad, M., Herodotou, C., Grizioti, M., Lincke, A., Girvan, C., et al. (2023). Combining Design Thinking with Emerging Technologies in K-12 Education. Methodologies and Intelligent Systems for Technology Enhanced Learning, 13th International Conference. MIS4TEL 2023. 15-27.
- Hagelbäck, J., Lincke, A., Löwe, W., Rall, E. (2019). On the Agreement of Commodity 3D Cameras. Proceedings of the 2019 International Conference on Image Processing, Computer Vision, & Pattern Recognition. 36-42.
- Hagelbäck, J., Liapota, P., Lincke, A., Löwe, W. (2019). Variants of Dynamic Time Warping and their Performance in Human Movement Assessment. 21st International Conference on Artificial Intelligence (ICAI'19: July 29 - August 1, 2019, Las Vegas, USA). 9-15.
- Lincke, A., Fellman, D., Jansen, M., Milrad, M., Berge, E., et al. (2019). Correlating Working Memory Capacity with Learners´ Study Behavior in a Web-Based Learning Platform. Proceedings of the 27th International Conference on Computers in Education Conference Proceedings. 90-92.
- Lincke, A., Jansen, M., Milrad, M., Berge, E. (2019). Using Data Mining Techniques to Assess Students’ Answer Predictions. ICCE 2019 - 27th International Conference on Computers in Education, Proceedings : Volume 1. 42-50.
- Lincke, A., Lozano Prieto, D., Herault, R.C., Forsgärde, E., Milrad, M. (2019). Visualizing learners’ navigation behaviour using 360 degrees interactive videos. Proceedings of the 15th International Conference on Web Information Systems and Technologies. 358-364.
- Hagelbäck, J., Liapota, P., Lincke, A., Löwe, W. (2019). The performance of some machine learning approaches in human movement assessment. 13th Multi Conference on Computer Science and Information Systems (MCCSIS). 35-42.
- Lincke, A., Lundberg, J., Thunander, M., Milrad, M., Lundberg, J., et al. (2018). Diabetes Information in Social Media. Proceedings of the 11th International Symposium on Visual Information Communication and Interaction (VINCI '18). 104-105.
- Herault, R.C., Lincke, A., Milrad, M., Forsgärde, E., Elmqvist, C., et al. (2018). Design and Evaluation of a 360 Degrees Interactive Video System to Support Collaborative Training for Nursing Students in Patient Trauma Treatment. 26TH INTERNATIONAL CONFERENCE ON COMPUTERS IN EDUCATION (ICCE 2018). 298-303.
- Sotsenko, A., Jansen, M., Milrad, M., Rana, J. (2016). Using a Rich Context Model for Real-Time Big Data Analytics in Twitter. 2016 IEEE 4TH INTERNATIONAL CONFERENCE ON FUTURE INTERNET OF THINGS AND CLOUD WORKSHOPS (FICLOUDW). 228-233.
- Sotsenko, A., Jansen, M., Milrad, M. (2015). Using a Rich Context Model for People-to-People Recommendation. 2015 3rd International Conference on Future Internet of Things and Cloud (FiCloud), 24-26 Aug. 2015, Rome. 703-708.
- Sotsenko, A. (2015). Exploring Different Use Cases for a Rich Context Model for Mobile Applications. Proceedings of Doctoral Symposium of the 9th International and Interdisciplinary Conference on Modeling and Using Context (CONTEXT 2015). 23-31.
- Sotsenko, A., Jansen, M., Milrad, M. (2014). Implementing and Validating a Mobile Learning Scenario Using Contextualized Learning Objects. Proceedings of the 22nd International Conference on Computers in Education ICCE 2014 : November 30, 2014 - December 4, 2014, Nara, Japan. 522-527.
- Sotsenko, A., Jansen, M., Milrad, M. (2014). Using a Rich Context Model for a News Recommender System for Mobile Users. UMAP 2014 Extended Proceedings : Posters, Demos, Late-breaking Results and Workshop Proceedings of the 22nd Conference on User Modeling, Adaptation, and Personalization co-located with the 22nd Conference on User Modeling, Adaptation, and Personalization (UMAP2014) Aalborg, Denmark, July 7-11, 2014.. 13-16.
- Sotsenko, A., Jansen, M., Milrad, M. (2013). Supporting Content Contextualization in Web Based Applications on Mobile Devices. Proceedings of the 9th International Conference on Web Information Systems and Technologies : Aachen, Germany, 8-10 May, 2013. 501-504.
- Sotsenko, A., Jansen, M., Milrad, M. (2013). About the Contextualization of Learning Objects in Mobile Learning Settings. QScience Proceedings : Vol. 2013, 12th World Conference on Mobile and Contextual Learning (mLearn 2013). 67-70.
Kapitel i bok, del av antologi (Refereegranskat)
- Sotsenko, A., Zbick, J., Jansen, M., Milrad, M. (2016). Flexible and Contextualized Cloud Applications for Mobile Learning Scenarios. Mobile, Ubiquitous, and Pervasive Learning : Fundaments, Applications, and Trends. Springer. 167-192.
- Sotsenko, A., Zbick, J., Jansen, M., Milrad, M. (2015). Contextualization of Mobile Learners. Mobile Learning : Trends, Attitudes and Effectiveness. Nova Science Publishers, Inc.. 39-54.
Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
- Lincke, A. (2020). A Computational Approach for Modelling Context across Different Application Domains. Doctoral Thesis. Växjö, Linnaeus University Press. 106.
Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
- Sotsenko, A. (2017). A Rich Context Model : Design and Implementation. Licentiate Thesis. Växjö, Faculty of Technology, Linnaeus University. 103.