Amilcar Soares Junior

Associate professor

Department of Computer Science and Media Technology Faculty of Technology

amilcar.soares@lnu.se

+46 470-70 81 90

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My research groups

E-health – Improved Data to and from Patients The research in the e-health area within Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) will result in novel ways for…
Information and Software Visualization (ISOVIS) The research group Information and Software Visualization mainly focuses on the explorative analysis and visualization of large and complex information…
Linnaeus University Centre for Data Intensive Sciences and Applications The DISA research centre at Linnaeus University focuses its efforts on open questions in collection, analysis and utilization of…

My ongoing research projects

Publications

Article in journal (Refereed)

Holm, I., Martins, R.M., Linhares, C.D.G., Soares, A. (2026). VILOD : Combining Visual Interactive Labeling With Active Learning for Object Detection. IEEE Computer Graphics and Applications.
Status: Epub ahead of print
Djebbar, F., Soares, A. (2025). An Overview and a Reflection of the Process and Product of Ph.D. Programs. Journal of Teaching and Learning in Higher Education. 6 (1).
Status: Published
Tavakoli, Y., Pena-Castillo, L., Soares, A. (2025). A novel multilevel taxonomical approach for describing high-dimensional unlabeled movement data. INTERNATIONAL JOURNAL OF DATA SCIENCE AND ANALYTICS. 21 (1).
Status: Published
Noel, J.T., Fonseca, V.P.D., Soares, A. (2024). The Use of Momentum-Inspired Features in Pre-Game Prediction Models for the Sport of Ice Hockey. International Journal of Computer Science in Sport. 23 (1). 1-21.
Status: Published
Das, S., Prado Da Fonseca, V., Soares, A. (2024). Active learning strategies for robotic tactile texture recognition tasks. Frontiers in Robotics and AI. 11.
Status: Published
Song, R., Spadon, G., Pelot, R., Matwin, S., Soares, A. (2024). Enhancing global maritime traffic network forecasting with gravity-inspired deep learning models. Scientific Reports. 14 (1).
Status: Published
Noel, J.T.P., Prado Da Fonseca, V., Soares, A. (2024). A Comprehensive Data Pipeline for Comparing the Effects of Momentum on Sports Leagues. Data. 9 (2).
Status: Published
Spadon, G., Kumar, J., Eden, D., Van Berkel, J., Foster, T., et al. (2024). Multi-path long-term vessel trajectories forecasting with probabilistic feature fusion for problem shifting. Ocean Engineering. 312 (Part 1).
Status: Published

Conference paper (Refereed)

Carlini, E., Di Gangi, D., Monteiro De Lira, V., Kavalionak, H., Soares, A., et al. (2025). ImPORTance - Machine Learning-Driven Analysis of Global Port Significance and Network Dynamics for Improved Operational Efficiency. SSTD '25: Proceedings of the 19th International Symposium on Spatial and Temporal Data.
Larkina, K., Holomsha, O., Lemos, L., Soares, A., Martins, R.M., et al. (2025). Visualizing Communities in Dynamic Multivariate Networks. 2025 38th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI): September 30th - October 3rd, 2025, Salvador, Brazil : Proceedings.
Giussani, S., Martins, R.M., Soares, A., Caporuscio, M., Perez-Palacin, D. (2025). Visualizing Feature Importance of Time Series Data in Discrete-Event Simulations using Shapley Additive Explanations. Proceedings of the 39th ACM SIGSIM Conference on Principles of Advanced Discrete Simulation. 65-69.
Othman, R., Powley, B., Martins, R.M., Soares, A., Kerren, A., et al. (2025). Fairness-Aware Urban Planning in Sweden: An Interactive Visualization Tool for Equitable Cities. .
Zare, N., Sayareh, A., Sadraii, A., Firouzkouhi, A., Soares, A. (2025). Cross Language Soccer Framework : An Open Source Framework for the RoboCup 2D Soccer Simulation. RoboCup 2024 : Robot World Cup XXVII. 152-163.
Sayareh, A., Simha, V., Swamidas, J., Alves De Oliveira, T.E., Soares, A., et al. (2025). Toward Automated Anomaly Detection and Categorization in Polymer Fiber Production. 2025 IEEE 34th International Symposium on Industrial Electronics (ISIE).
Alam, M.M., Soares, A., F. Rodrigues-Jr, J., Spadon, G. (2025). Physics-Informed Neural Networks for Vessel Trajectory Prediction : Learning Time-Discretized Kinematic Dynamics via Finite Differences. SSTD '25: Proceedings of the 19th International Symposium on Spatial and Temporal Data.
Das, S., Simha, V., Swamidas, J., Soares, A., Prado Da Fonseca, V. (2024). Unbalanced Fault Classification Using Active Learning in Synthetic Fiber Manufacturing Process. 2024 IEEE International Systems Conference (SysCon).
Haranwala, Y.J., Spadon, G., Renso, C., Soares, A. (2023). A Data Augmentation Algorithm for Trajectory Data. EMODE '23: Proceedings of the 1st ACM SIGSPATIAL International Workshop on Methods for Enriched Mobility Data: Emerging issues and Ethical perspectives 2023, November. 25-29.