Member of the Skövde Artificial Intelligence Lab (SAIL). Research interests: visual analytics, data mining, machine learning, data science and HCI.
Main supervisor of doctoral students Elio Ventocilla (visual analytics and interactive machine learning) and Nikolas Huhnstock (adaptive neural networks). Primary supervisor of industrial PhD-student Ulrika Ohlander (HCI, Saab Aero, Linköping). Co-supervisor of Erik Lagerstedt (HRI, iLab), Patrick Gabrielsson (deep learning, University of Borås), Navoda Senavirathne (VR, data privacy) and Zhen Rong (visiting PhD-student from Shanghai Maritime University, maritime anomaly detection).
SPS2022: Proceedings of the 10th Swedish production symposium
2022. Conference paper.
https://doi.org/10.3233/ATDE220124
IEEE Computer Graphics and Applications
2021. Article. https://doi.org/10.1109/MCG.2021.3107875
PLANs forsknings- och tillämpningskonferens 2021, Högskolan i Borås, 20-21 oktober 2021
2021. Conference paper, oral presentation with abstract.
ICMI '21: Proceedings of the 2021 International Conference on Multimodal Interaction
2021. Conference paper. https://doi.org/10.1145/3462244.3479879
Journal of Biotechnology
2021. Article.
https://doi.org/10.1016/j.jbiotec.2020.12.002
Big Data Research
2021. Article.
https://doi.org/10.1016/j.bdr.2021.100254
Developments of Artificial Intelligence Technologies in Computation and Robotics: Proceedings of the 14th International FLINS Conference (FLINS 2020)
2020. Conference paper. https://doi.org/10.1142/9789811223334_0074
ACM Computing Surveys
2020. Article.
https://doi.org/10.1145/3340960
Machine Learning Methods in Visualisation for Big Data
2020. Conference paper.
https://doi.org/10.2312/mlvis.20201099
Information Visualization
2020. Article.
https://doi.org/10.1177/1473871620922166
Virtual factories with knowledge-driven optimization (VF-KDO) is an eight-year research profile that is being coordinated by the University of Skövde. Research within this profile aims to help strengthen the competitiveness of Swedish industry.
October 2018 - September 2025 Virtual EngineeringThe aim of this project is to contribute with improved methods for analysis, integration, and visualization of biomedical big data. Recent years it has been a massive digitalization of all types of data and information in the society and the majority of all information in the world is nowadays anticipated to be digitalized. This encompasses enormous possibilities for generation of new knowledge but also puts demands on competence and tools for analysis and interpretation of big and complex data, e.g. to identify and extract patterns and information from different data sources. To meet these increasing demands of large-scale data analysis more competence, better and faster algorithms, and powerful computers are needed for execution these algorithms.
October 2015 - September 2019 Systems BiologyBig data has gained much interesting in recent years due to the rapid expansion of the massive amount of data that is available for solving different types of tasks within many different application domains. However, today's big data is still on a fairly low level of abstraction when it comes to complex decision support tasks, subject to e.g. high dimensionality and significant portions of uncertainty regarding which patterns to look for in the data.
October 2015 - September 2019 InformaticsFusarium attacks on Swedish cereals in recent years have attracted increasing attention. While these attacks can lead to reduced harvests, the most serious effect is that this fungus can produce toxins. EU legislation has defined limit values for the content of Fusarium toxins because they are harmful to both humans and animals. Our project aims to develop a farm-based decision support system that will assess the risk of Fusarium attacks and elevated levels of deoxynivalenol (DON) in cereals. It can be used by both advisers/consultancies and farmers.
January 2018 - June 2020 InformaticsThe project will study design elements of future air systems that offer cognitive support for increased team effectiveness. The project will investigate how the design of complex systems can benefit from taking the teamwork perspective.
November 2019 - February 2022 InformaticsAn unprecedented growth of data, fed by novel technologies, user behaviour and business models, is one of the most dramatic and important developments in both ICT and society at large. Most of this is Big Data, characterised by vast volume, high velocity, large variety and unknown veracity. These properties pose significant challenges when collecting, managing and processing data.
January 2015 - January 2020 Informatics