Maria Riveiro

Member of the Skövde Artificial Intelligence Lab (SAIL). Research interests: visual analytics, data mining, machine learning, data science and HCI.
Current research projects:
- BIDAF (A Big Data Analytics Framework for a Smart Society).
- BISON (Big Data Fusion - Bioinformatics subproject, with AstraZeneca
and TakaraBio). - HMI for Distributed Decision-Making with Saab Aeronautics.
- Infofusion Fusarium.
- IDS. Golf Data Analysis (GOATS).
Some earlier projects:
- NOVA (New Opportunities through Visual Analytics for Big Data with Combitech and Takara Europe).
- CARSII (Energimyndigheten, eco-driving).
- UMIF (Uncertainty Management in Information Fusion, with Saab AB, Volvo Technology, Volvo CC, Agroväst, etc.).
- InfoFusion Research Program.
Current teaching:
- Data Analysis Course, post-graduate level (IT929F).
Research students:
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).
Brief CV:
- Associate Professor of Informatics (2017)
- Docent (2015)
- Senior Lecturer in Computing Science (2012)
- PhD in Computer Science (2011)
- Software Engineer (2004-2005)
- M.Sc. in Telecommunication Engineering, Higher Technical School of Telecommunication Engineering, Vigo, Spain (mostv. Civilingenjör i Elektroteknik enligt Högskoleverket) (2004)
Research
2021
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
2020
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
Computer Vision, Imaging and Computer Graphics Theory and Applications: 14th International Joint Conference, VISIGRAPP 2019, Prague, Czech Republic, February 25–27, 2019, Revised Selected Papers
2020. Chapter in book. https://doi.org/10.1007/978-3-030-41590-7_9
2019
Data science in Practice
2019. Chapter in book. https://doi.org/10.1007/978-3-319-97556-6_8
Modeling Decisions for Artificial Intelligence: 16th International Conference, MDAI 2019, Milan, Italy, September 4–6, 2019, Proceedings
2019. Conference paper. https://doi.org/10.1007/978-3-030-26773-5_27
Ergonomics
2019. Article.
https://doi.org/10.1080/00140139.2019.1596319