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

Project: InfraVis – National Research Infrastructure for Visualisation of Data InfraVis will create a common gateway to Swedish visualization resources and enhance the competence of researchers in…

Publications

Article in journal (Refereed)

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
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
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
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)

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.
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.
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. .
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).
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.
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.