Maria Riveiro
PhD
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Research
Maria Riveiro’s research interests are at the intersection of human-computer interaction (HCI), machine learning (ML) and artificial intelligence (AI). The unifying theme of her research is to investigate the potential of integrating ML/AI techniques with interactive visual analysis methods to support decision-making tasks. Currently, Prof. Riveiro research work focuses on Explainable AI (XAI) and Human-Centered AI (HCAI).
Check out our new Human-Centered Technology Group!
Current research projects:
- XPECT - How to Tailor Explanations from AI Systems to Users' Expectations, funded by the Swedish Research Council (Vetenskapsrådet). Consolidator Grant.
- XAAI - Explainable and Adaptable Artificial Intelligence, funded by The Knowledge Foundation (2025-2028).
- AI4QAM - (End-to-End) AI for Quality Assurance in Manufacturing. Project funded by VINNOVA 2024-2027. We create user-friendly End-to-End AI for automated quality control of manufactured components that can adapt to different environmental conditions and product designs, with RISE, Husqvarna, Thule, Scania, Enodo Robotics and PVI Hydroforming.
- MAIN - Managing AI integration,funded by The Knowledge Foundation (Jan 2025- Dec 2027).
- SIP-DP Supporting Individual Prosthetic Design Preferences. Development and evaluation of an AI-based patient decision aid, funded by The Knowledge Foundation (2025-2028).
- Research school Smart Industry Sweden with ITAB AB, Tobias Pettersson and Siemens Energy, Nils-Erik Ohlson. https://smartindustrysweden.se/
Previous:
- EXPLAIN - Evaluation of Explainable AI. EXplAIn tackles the challenge of evaluating users interacting with ML systems, aiming at developing a generic and integrative framework for evaluating human ML-system collaboration. Funded by The Swedish Research Council (Etableringsbidrag, Vetenskapsrådet, to 2023).
- XAI-Pro - Explainable AI for product and service development; project under AFAIR (a multidisciplinary research project with a focus on applied AI; funded by The Knowledge Foundation). With Husqvarna and SAAB Training and Simulation. (2022-2024)
- OptiPro – Optimization of prosthesis design according to Kansei Engineering and Machine Learning. This project brings together prosthetics, industrial product development and machine learning experts to improve the quality of prosthetic services and products for people who have undergone a lower-limb amputation. Funded by The Knowledge Foundation. (2021-2024)
- SMARTER 2.0 Competence development within AI for professionals, 2019-2023, led by Örebro University. Funded by The Knowledge Foundation.
Biography
Maria Riveiro is a Professor of Computer Science at the School of Engineering, Jönköping University (JU), Sweden. Prior to joining JU, Prof. Riveiro worked for several years at the University of Skövde, Sweden, being named Docent in 2015 and Assoc. Prof. of Informatics in 2017. She holds a Ph.D. degree in Computer Science from Örebro University (2011) and a Master of Science in Telecommunication Engineering from the University of Vigo, Spain (2004). She has held several positions in the industry as a consultant and software engineer in Finland and Spain.
Maria Riveiro has experience teaching at undergraduate, graduate, and post-graduate levels in several areas of Computer Science and Electrical Engineering; she has pedagogical education; in 2014, Maria Riveiro received the merited title of “Accomplished Teaching Lecturer” from the University of Skövde. Prof. Riveiro is currently supervising several doctoral students in the areas of visual analytics, interpretable and interactive ML, neural networks, human-robot interaction, etc.
Article
Smedberg, H., Bandaru, S., Riveiro, M., Ng, A.
(2024).
Mimer: A Web-Based Tool for Knowledge Discovery in Multi-Criteria Decision Support [Application Notes] IEEE Computational Intelligence Magazine, 19(3), 73-87.
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Ramstrand, N., Riveiro, M., Eriksson, L., Ceder, M.
(2024).
Designing feelings into lower-limb prostheses: A kansei engineering approach to understand lower-limb prosthetic cosmeses Rehabilitation and Assistive Technologies Engineering, 11.
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Pettersson, T., Riveiro, M., Löfström, T.
(2024).
Multimodal fine-grained grocery product recognition using image and OCR text Machine Vision and Applications, 35(4).
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Riveiro, M.
(2023).
Expectations, trust, and evaluation Dagstuhl Reports, 12(8), 109.
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Riveiro, M.
(2023).
A design theory for uncertainty visualization? Dagstuhl Reports, 12(8), 12-13.
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Ohlander, U., Alfredson, J., Riveiro, M., Helldin, T., Falkman, G.
(2023).
The Effects of Varying Degrees of Information on Teamwork a Study on Fighter Pilots Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 67(1), 1965-1970.
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Gleicher, M., Riveiro, M., Von Landesberger, T., Deussen, O., Chang, R., Gillman, C.
(2023).
A Problem Space for Designing Visualizations IEEE Computer Graphics and Applications, 43(4), 111-120.
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Beauxis-Aussalet, E.
Behrisch, M.
Borgo, R.
Chau, D.
Collins, C.
Ebert, D.
, ... Rhyne T.
(2021).
The Role of Interactive Visualization in Fostering Trust in AI IEEE Computer Graphics and Applications, 41(6), 7-12.
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Arvidsson, S., Gullstrand, M., Sirmacek, B., Riveiro, M.
(2021).
Sensor fusion and convolutional neural networks for indoor occupancy prediction using multiple low-cost low-resolution heat sensor data Sensors, 21(4), 1-21.
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Ulfenborg, B., Karlsson, A., Riveiro, M., Andersson, C., Sartipy, P., Synnergren, J.
(2021).
Multi-assignment clustering: Machine learning from a biological perspective Journal of Biotechnology, 326, 1-10.
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Ventocilla, E., Martins, R., Paulovich, F., Riveiro, M.
(2021).
Scaling the Growing Neural Gas for Visual Cluster Analysis Big Data Research.
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Riveiro, M., Thill, S.
(2021).
“That's (not) the output I expected!” On the role of end user expectations in creating explanations of AI systems Artificial Intelligence, 298.
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Ventocilla, E., Riveiro, M.
(2020).
A comparative user study of visualization techniques for cluster analysis of multidimensional data sets Information Visualization, 19(4), 318-338.
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Riveiro, M.
(2020).
Explainable AI for maritime anomaly detection and autonomous driving Dagstuhl Reports, 9(11), 29-30.
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Sirmacek, B., Riveiro, M.
(2020).
Occupancy prediction using low-cost and low-resolution heat sensors for smart offices Sensors, 20(19).
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Bae, J., Helldin, T., Riveiro, M., Nowaczyk, S., Bouguelia, M., Falkman, G.
(2020).
Interactive Clustering: A Comprehensive Review.
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Ohlander, U., Alfredson, J., Riveiro, M., Falkman, G.
(2019).
Fighter pilots’ teamwork: a descriptive study Ergonomics, 62(7), 880-890.
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Thill, S., Riveiro, M., Lagerstedt, E., Lebram, M., Hemeren, P., Habibovic, A., Klingegård, M.
(2018).
Driver adherence to recommendations from support systems improves if the systems explain why they are given: A simulator study Transportation Research Part F: Traffic Psychology and Behaviour, 56, 420-435.
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Riveiro, M., Pallotta, G., Vespe, M.
(2018).
Maritime anomaly detection: A review.
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Kinkeldey, C., MacEachren, A., Riveiro, M., Schiewe, J.
(2017).
Evaluating the effect of visually represented geodata uncertainty on decision-making: Systematic review, lessons learned, and recommendations.
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Riveiro, M., Lebram, M., Elmer, M.
(2017).
Anomaly Detection for Road Traffic: A Visual Analytics Framework IEEE transactions on intelligent transportation systems (Print), 18(8), 2260-2270.
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Bae, J., Helldin, T., Riveiro, M.
(2017).
Understanding Indirect Causal Relationships in Node-Link Graphs Computer graphics forum (Print), 36(3), 411-421.
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Zhen, R., Riveiro, M., Jin, Y.
(2017).
A novel analytic framework of real-time multi-vessel collision risk assessment for maritime traffic surveillance Ocean Engineering, 145, 492-501.
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Ulfenborg, B.
Karlsson, A.
Riveiro, M.
Améen, C.
Åkesson, K.
Andersson, C.
, ... Synnergren J.
(2017).
A data analysis framework for biomedical big data: Application on mesoderm differentiation of human pluripotent stem cells PLOS ONE, 12(6).
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Riveiro, M.
(2016).
Visually supported reasoning under uncertain conditions: Effects of domain expertise on air traffic risk assessment Spatial Cognition and Computation, 16(2), 133-153.
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Riveiro, M., Helldin, T., Falkman, G., Lebram, M.
(2014).
Effects of visualizing uncertainty on decision-making in a target identification scenario Computers & graphics, 41(1), 84-98.
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Riveiro, M.
(2014).
Evaluation of Normal Model Visualization for Anomaly Detection in Maritime Traffic ACM Transactions on Interactive Intelligent Systems, 4(1), 1-24 New York: Association for Computing Machinery (ACM) .
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Riveiro, M., Falkman, G.
(2014).
Detecting anomalous behavior in sea traffic: A study of analytical strategies and their implications for surveillance systems International Journal of Information Technology & Decision Making, 13(2), 317-360.
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Doctoral thesis
Riveiro, M.
(2011).
Visual Analytics for Maritime Anomaly Detection
(Doctoral thesis, Örebro:
Örebro University).
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Book chapter
Bae, J., Falkman, G., Helldin, T., Riveiro, M.
(2019).
Visual Data Analysis.
In:
A. Said, & V. Torra
(Ed.),
Data science in Practice
(pp. 133 -155).
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Dahlbom, A., Riveiro, M., König, R., Johansson, U., Brattberg, P.
(2014).
Supporting Golf Coaching with 3D Modeling of Swings.
In:
Sportinformatik X: Jahrestagung der dvs-Sektion Sportinformatik
(pp. 142 -148).
Hamburg: Feldhaus Verlag
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Riveiro, M.
(2013).
The importance of visualization and interaction in the anomaly detection process.
In:
Mao Lin Huang & Weidong Huang
(Ed.),
Innovative approaches of data visualization and visual analytics
(pp. 133 -150).
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Conference paper
Pettersson, M., Westphal, F., Riveiro, M.
(2024).
Exploring demonstration pre-training with improved Deep Q-learning.
Linköping:
Linköping University Electronic Press, 14th Scandinavian Conference on Artificial Intelligence, SCAI 2024: June 10-11, 2024, Jönköping, Sweden.
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Holmberg, L., Riveiro, M., Thill, S.
(2024).
Leveraging large language models for tailored and interactive explanations in AI systems.
Skövde:
Swedish Cognitive Science Society, 19th SweCog Conference, Stockholm, Sweden, 10-11 October, 2024.
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Pettersson, T., Riveiro, M., Löfström, T.
(2024).
Real-time automatic checkout via prompt-based product extraction and cross-domain learning.
Miami, FL, USA:
IEEE, 2024 International Conference on Machine Learning and Applications (ICMLA), 18-20 December 2024.
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Pettersson, T., Riveiro, M., Löfström, T.
(2023).
Explainable local and global models for fine-grained multimodal product recognition.
Multimodal KDD 2023, International Workshop on Multimodal Learning, in conjunction with 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023), August 6–10, 2023, Long Beach, CA, USA.
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Ohlson, N., Riveiro, M., Bäckstrand, J.
(2022).
Identification of tasks to be supported by machine learning to reduce Sales & Operations Planning challenges in an engineer-to-order context.
Amsterdam:
IOS Press, 10th Swedish Production Symposium (SPS2022), School of Engineering Science, University of Skövde, Sweden, April 26–29 2022.
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Riveiro, M., Thill, S.
(2022).
The challenges of providing explanations of AI systems when they do not behave like users expect.
New York:
Association for Computing Machinery (ACM), UMAP '22: 30th ACM Conference on User Modeling, Adaptation and Personalization, Barcelona, Spain, July 4-7, 2022.
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Schuller, B., Virtanen, T., Riveiro, M., Rizos, G., Han, J., Mesaros, A., Drossos, K.
(2021).
Towards Sonification in Multimodal and User-Friendly Explainable Artificial Intelligence.
ICMI ’21, International Conference on Multimodal Interaction, 18–22 October, 2021, Montréal, QC, Canada.
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Ohlson, N., Bäckstrand, J., Riveiro, M.
(2021).
Artificial Intelligence-enhanced Sales & Operations Planning in an Engineer-to-order context.
PLANs forsknings- och tillämpningskonferens 2021, Högskolan i Borås, 20-21 oktober 2021.
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Ventocilla, E., Riveiro, M.
(2020).
A model for the progressive visualization of multidimensional data structure.
Cham:
Springer, 14th International Joint Conference, VISIGRAPP 2019 Prague, Czech Republic, February 25–27, 2019.
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Annavarjula, V., Mbiydzenyu, G., Riveiro, M., Lavesson, N.
(2020).
Implicit user data in fashion recommendation systems.
14th International FLINS Conference (FLINS 2020), Cologne, Germany, 18–21 August 2020.
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Ventocilla, E., Martins, R., Paulovich, F., Riveiro, M.
(2020).
Progressive multidimensional projections: A process model based on vector quantization.
International Workshop on Machine Learning in Visualisation for Big Data, Norrköping, Sweden, May 25-29, 2020 (Virtual).
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Ventocilla, E., Riveiro, M.
(2019).
Visual Growing Neural Gas for Exploratory Data Analysis.
14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 25 - 27 February, 2019, Prague, Czech Republic.
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Huhnstock, N., Karlsson, A., Riveiro, M., Steinhauer, H.
(2019).
An Infinite Replicated Softmax Model for Topic Modeling.
16th International Conference, MDAI 2019, Milan, Italy, September 4–6, 2019.
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Thill, S., Riveiro, M.
(2019).
Memento hominibus: on the fundamental role of end users in real-world interactions with neuromorphic systems.
Robust Artificial Intelligence for Neurorobotics, 26 – 28 August 2019, Edinburgh, Scotland.
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Huhnstock, N., Karlsson, A., Riveiro, M., Steinhauer, H.
(2018).
On the behavior of the infinite restricted boltzmann machine for clustering.
New York, NY, USA:
Association for Computing Machinery (ACM), SAC 18 The 33rd Annual ACM Symposium on Applied Computing, Pau, France, April 9-13, 2018.
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Bae, J., Ventocilla, E., Riveiro, M., Torra, V.
(2018).
On the Visualization of Discrete Non-additive Measures.
9th International Summer School on Aggregation Functions (AGOP), Skövde, Sweden, June 19-22, 2017.
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Bae, J., Ventocilla, E., Riveiro, M., Helldin, T., Falkman, G.
(2017).
Evaluating Multi-Attributes on Cause and Effect Relationship Visualization.
8th International Conference on Information Visualization Theory and Applications (IVAPP), part of the 12th International Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017), February 27-March 1, 2017, in Porto, Portugal.
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Ventocilla, E., Bae, J., Riveiro, M., Said, A.
(2017).
A Billiard Metaphor for Exploring Complex Graphs.
Second Workshop on Supporting Complex Search Tasks co-located with the ACM SIGIR Conference on Human Information Interaction & Retrieval (CHIIR 2017), Oslo, Norway, March 11, 2017.
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Bae, J., Helldin, T., Riveiro, M.
(2017).
Identifying Root Cause and Derived Effects in Causal Relationships.
Thematic track on Human Interface and the Management of Information, held as part of the 19th International Conference on Human–Computer Interaction, HCI International 2017, Vancouver, Canada, 9 July 2017 through 14 July 2017.
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Ventocilla, E., Riveiro, M.
(2017).
Visual Analytics Solutions as 'off-the-shelf' Libraries.
2017 21st International Conference Information Visualisation (IV), London, United Kingdom, July 11-14, 2017.
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Ohlander, U., Alfredson, J., Riveiro, M., Falkman, G.
(2017).
User Participation in the Design of Cockpit Interfaces.
AHFE 2016 International Conference on Ergonomics Modeling, Usability & Special Populations, July 27-31, 2016, Walt Disney World®, Florida, USA.
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König, R., Johansson, U., Riveiro, M., Brattberg, P.
(2017).
Modeling golf player skill using machine learning.
1st IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference on Machine Learning and Knowledge Extraction, CD-MAKE 2017; Reggio; Italy; 29 August 2017 through 1 September 2017.
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Lagerstedt, E., Riveiro, M., Thill, S.
(2017).
Agent Autonomy and Locus of Responsibility for Team Situation Awareness.
New York:
Association for Computing Machinery (ACM), 5th International Conference on Human Agent Interaction, Bielefeld, October 17-20, 2017.
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Ohlander, U., Alfredson, J., Riveiro, M., Falkman, G.
(2016).
A Teamwork Model for Fighter Pilots.
13th International Conference, EPCE 2016, Held as Part of HCI International 2016, Toronto, ON, Canada, July 17-22, 2016.
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Riveiro, M., Gustavsson, P., Lebram, M., Bengstsson, M., Blomqvist, P., Wallinius, M.
(2016).
Enhanced Training through Interactive Visualization of Training Objectives and Models.
2016 NATO Modelling & Simulation Group (NMSG) Symposium, Bucharest, Romania, October 20-21, 2016.
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Ohlander, U., Alfredson, J., Riveiro, M., Falkman, G.
(2016).
Elements of team effectiveness: A qualitative study with pilots.
IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA), San Diego, CA, 21-25 March 2016.
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Riveiro, M., Lebram, M., Andersson, C., Sartipy, P., Synnergren, J.
(2016).
Interactive visualization of large-scale gene expression data.
20th International Conference Information Visualisation, 19-22 July 2016, Lisbon, Portugal.
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Johansson, U., Konig, R., Brattberg, P., Dahlbom, A., Riveiro, M.
(2016).
Mining trackman golf data.
International Conference on Computational Science and Computational Intelligence, CSCI 2015, 7 December 2015 through 9 December 2015.
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Synnergren, J., Ameén, C., Åkesson, K., Karlsson, A., Riveiro, M., Andersson, C., Sartipy, P.
(2016).
Transcriptional profiling of human embryonic stem cells during mesodermal- and cardiac differentiation.
International Society for Stem Cell Research (ISSCR) Annual meeting, San Fransisco 22–25 June 2016.
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Helldin, T., Riveiro, M., Pashami, S., Falkman, G., Byttner, S., Nowaczyk, S.
(2016).
Supporting analytical reasoning: A study from the automotive industry.
18th International Conference on Human Interface and the Management of Information (HCI International 2016), Toronto, Canada, July 17-22, 2016..
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Bergström, E., Carlén, U., Riveiro, M.
(2016).
How to Include Female Students in Technical Computer Science Study Programs.
NU2016, Malmö, 15-17 juni, 2016.
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Riveiro, M., Dahlbom, A., König, R., Johansson, U., Brattberg, P.
(2015).
Supporting Golf Coaching and Swing Instruction with Computer-Based Training Systems.
Learning and Collaboration Technologies.
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Lagerstedt, E., Riveiro, M., Thill, S.
(2015).
Interacting with Artificial Agents.
13th Scandinavian Conference on Artificial Intelligence, SCAI 2015, Halmstad, Sweden, 4 November 2015 through 5 November 2015.
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Ohlander, U., Alfredson, J., Riveiro, M., Falkman, G.
(2015).
Understanding Team Effectiveness in a Tactical Air Unit.
12th International Conference on Engineering Psychology and Cognitive Ergonomics (EPCE 2015), Held as Part of HCI International 2015, Los Angeles, CA, USA, August 2-7, 2015.
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Thill, S., Riveiro, M.
(2015).
Situation awareness in eco-driving.
5th IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA), March 9-12, Orlando, USA.
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Thill, S., Riveiro, M., Nilsson, M.
(2015).
Perceived intelligence as a factor in (semi-) autonomous vehicle UX.
"Experiencing Autonomous Vehicles: Crossing the Boundaries between a Drive and a Ride" workshop in conjunction with CHI2015.
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Riveiro, M., Helldin, T., Falkman, G.
(2014).
Influence of Meta-Information on Decision-Making: Lessons Learned from Four Case Studies.
2014 IEEE International Inter-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA), March 3-6, San Antonio, USA.
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Riveiro, M., Lebram, M., Warston, H.
(2014).
On visualizing threat evaluation configuration processes: A design proposal.
17th International Conference on Information Fusion, FUSION 2014, Salamanca, Spain 7 July 2014 through 10 July 2014.
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Dahlbom, A., Riveiro, M.
(2014).
Situation Modeling and Visual Analytics for Decision Support in Sports.
16th International Conference on Enterprise Information Systems, Lisbon, Portugal, April 27-30, 2014.
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Helldin, T., Ohlander, U., Falkman, G., Riveiro, M.
(2014).
Transparency of Automated Combat Classification.
11th International Conference on Engineering Psychology and Cognitive Ergonomics, EPCE 2014, Held as Part of 16th International Conference on Human-Computer Interaction, HCI International 2014, Heraklion, Crete, Greece, 22 June 2014 through 27 June 2014.
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Andreasson, R., Riveiro, M.
(2014).
Effects of Visualizing Missing Data: An Empirical Evaluation.
2014 18th International Conference on Information Visualisation: Visualisation, BioMedical Visualization, Visualisation on Built and Rural Environments and Geometric Modelling and Imaging, IV 2014, Paris, France, 16 July 2014 through 18 July 2014.
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Helldin, T., Falkman, G., Riveiro, M., Dahlbom, A., Lebram, M.
(2013).
Transparency of military threat evaluation through visualizing uncertainty and system rationale.
10th International Conference on Engineering Psychology and Cognitive Ergonomics: Applications and Services, EPCE 2013, Held as Part of 15th International Conference on Human-Computer Interaction, HCI 2013, 21 July 2013 through 26 July 2013, Las Vegas, NV.
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Helldin, T., Falkman, G., Riveiro, M., Davidsson, S.
(2013).
Presenting system uncertainty in automotive UIs for supporting trust calibration in autonomous driving.
New York:
Association for Computing Machinery (ACM), 5th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI’13), 28-30 October, 2013, Eindhoven, The Netherlands.
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Riveiro, M., Helldin, T., Lebram, M., Falkman, G.
(2013).
Towards future threat evaluation systems: user study, proposal and precepts for design.
16th International Conference on Information Fusion (FUSION), 2013, 9-12 July 2013, Istanbul, Turkey.
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Riveiro, M., Bergström, E., Carlén, U.
(2012).
Inför en ökad jämställdhet i datavetenskapliga utbildningsprogram.
NU 2012, 17-19 oktober 2012, Göteborg.
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Riveiro, M., Falkman, G.
(2011).
The role of visualization and interaction in maritime anomaly detection.
Visualization and Data Analysis 2011; San Francisco, CA; 24 January 2011 through 25 January 2011.
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Riveiro, M., Falkman, G.
(2011).
Empirical evaluation of visualizations of normal behavioral models for supporting maritime anomaly detection.
GeoViz: Linking Geovisualization with Spatial Analysis and Modeling, March 10–11, 2011, Hamburg, Germany.
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Riveiro, M., Falkman, G.
(2010).
Evaluating the usability of visualizations of normal behavioral models for analytical reasoning.
7th International Conference on Computer Graphics, Imaging and Visualization, CGIV 2010; Sydney, NSW; 7 August 2010 through 10 August 2010.
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Riveiro, M., Falkman, G.
(2010).
Supporting the analytical reasoning process in maritime anomaly detection: evaluation and experimental design.
14th International Conference Information Visualisation, IV 2010; London; 26 July 2010 through 29 July 2010.
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Riveiro, M., Falkman, G., Ziemke, T., Kronhamn, T.
(2009).
Reasoning about anomalies: a study of the analytical process of detecting and identifying anomalous behavior in maritime traffic data.
Visual analytics for homeland defense and security : 14 April 2009, Orlando, Florida, United States.
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Riveiro, M., Falkman, G.
(2009).
Interactive Visualization of Normal Behavioral Models and Expert Rules for Maritime Anomaly Detection.
Sixth International Conference on Computer Graphics, Imaging and Visualization: 11-14 August 2009, Tianjin, China.
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Helldin, T., Riveiro, M.
(2009).
Explanation Methods for Bayesian Networks: review and application to a maritime scenario.
Proceedings of the 3rd Skövde Workshop on Information Fusion Topics (SWIFT 2009), 12-13 Oct 2009, Skövde, Sweden.
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Riveiro, M., Falkman, G., Ziemke, T., Warston, H.
(2009).
VISAD: an interactive and visual analytical tool for the detection of behavioural anomalieis in maritime traffic data.
Visual analytics for homeland defense and security : 14 April 2009, Orlando, Florida, United States.
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Niklasson, L.
Riveiro, M.
Johansson, F.
Dahlbom, A.
Falkman, G.
Ziemke, T.
, ... Gustavsson P.
(2008).
Extending the scope of Situation Analysis.
11th International Conference on Information Fusion (FUSION 2008), Cologne, Germany, June 30–July 3, 2008.
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Riveiro, M., Falkman, G., Ziemke, T.
(2008).
Improving maritime anomaly detection and situation awareness through interactive visualization.
11th International Conference on Information Fusion, FUSION 2008; Cologne; Germany; 30 June 2008 through 3 July 2008.
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Riveiro, M., Johansson, F., Falkman, G., Ziemke, T.
(2008).
Supporting Maritime Situation Awareness Using Self Organizing Maps and Gaussian Mixture Models.
Amsterdam:
IOS Press, 10th Scandinavian Conference on Artificial Intelligence, SCAI 2008; Stockholm; 26 May 2008 through 28 May 2008.
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Riveiro, M., Falkman, G., Ziemke, T.
(2008).
Visual Analytics for the Detection of Anomalous Maritime Behavior.
12th International Conference Information Visualisation, IV08; London; United Kingdom; 9 July 2008 through 11 July 2008.
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Niklasson, L.
Riveiro, M.
Johansson, F.
Dahlbom, A.
Falkman, G.
Ziemke, T.
, ... Gustavsson P.
(2007).
A Unified Situation Analysis Model for Human and Machine Situation Awareness.
Bonn:
Gesellschaft für Informatik, INFORMATIK 2007, Informatik trifft Logistik, 37. Jahrestagung der Gesellschaft für Informatik e.V. (GI) 24. - 27. September 2007 in Bremen.
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Riveiro, M.
(2007).
Cognitive Evaluation of Uncertainty Visualization Methods for Decision Making.
Proceedings of the 4th symposium on Applied perception in graphics and visualization, Tubingen, Germany — July 25 - 27, 2007.
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Riveiro, M.
(2007).
Evaluation of Uncertainty Visualization Techniques for Information Fusion.
10th International Conference on Information Fusion, 2007.
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Conference proceedings (editor)
Westphal, F., Peretz-Andersson, E., Riveiro, M., Bach, K., Heintz, F. (Eds.).
(2024).
14th Scandinavian Conference on Artificial Intelligence, SCAI 2024: June 10-11, 2024, Jönköping, Sweden.
, Linköping:
Linköping University Electronic Press
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Report
Riveiro, M., Johansson, R., Karlsson, A.
(2011).
Modeling and analysis of energy data: state-of-the-art and practical results from an application scenario.
Skövde:
University of Skövde
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Nilsson, M., Riveiro, M., Ziemke, T.
(2008).
Investigating human-computer interaction issues in information-fusion-based decision support.
Skövde:
Institutionen för kommunikation och information
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Riveiro, M.
(2007).
Research proposal: Information Visualization for Information Fusion.
Skövde:
Institutionen för kommunikation och information
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