Amilcar Soares Junior
Docent
Institutionen för datavetenskap och medieteknik
Fakulteten för teknik
Mina forskargrupper
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E-health – Improved Data to and from Patients Forskningen inom e-hälsoområdet vid Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) kommer att resultera i nya metoder för…
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Information and Software Visualization (ISOVIS) Forskargruppen Information and Software Visualization fokuserar huvudsakligen på att genom analys och visualisering utforska stora och komplexa…
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Linnaeus University Centre for Data Intensive Sciences and Applications DISA är Linnéuniversitetets spetsforskningsmiljö som arbetar med insamling, analys och nyttogörande av stora datamängder.…
Mina pågående forskningsprojekt
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Projekt: Ansvarsfull användning av AI för protein–ligandenergier (RED-ALE) Projektet syftar till att ta fram riktlinjer för ansvarsfull användning av AI vid beräkning av bindningsenergi mellan…
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Projekt: InfraVis – nationell forskningsinfrastruktur för visualisering av data InfraVis kommer att skapa en gemensam ingång till de svenska resurserna i visualisering och utbilda forskare inom olika…
Publikationer
Artikel i tidskrift (Refereegranskat)
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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. 1-14.
Status: Publicerad -
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: Publicerad -
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: Publicerad -
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: Publicerad -
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: Publicerad -
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: Publicerad -
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: Publicerad -
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: Publicerad
Konferensbidrag (Refereegranskat)
- 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.