Pina, R., De Silva, V. and Illeperuma M. (2025). Representing Clinical Conditions on Vital Signs from Healthy Individuals using Latent Modeling. In 25th IEEE International Conference on Digital Signal Processing (DSP).

Illeperuma M., De Silva, V. and Pina, R. (2025). EEG-Based Signal Processing Framework for Self-Organized Criticality Detection. In 25th IEEE International Conference on Digital Signal Processing (DSP).

Pina, R. and De Silva, V. (2025). Exploring Communication in Multi-Agent Reinforcement Learning Under Agent Malfunction. In Proceedings of the 14th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-730-6; ISSN 2184-4313, SciTePress, pages 445-452.

Sikdar, A., Liu, Y., Kedarisetty, S., Zhao, Y., Ahmed, A. and Behera, A., 2024. Interweaving Insights: High-Order Feature Interaction for Fine-Grained Visual Recognition. International Journal of Computer Vision, pp.1-25.

Humnabadkar, A., Sikdar, A., Cave, B., Zhang, H., Bakaki, P. and Behera, A., 2024. High-Order Evolving Graphs for Enhanced Representation of Traffic Dynamics. European Conference on Computer Vision (ECCV) - 2nd Workshop on Vision-Centric Autonomous Driving (VCAD).

Humnabadkar, A., Sikdar, A., Zhang, H., Hussain, T. and Behera, A., 2024, October. Driving Through Graphs: a Bipartite Graph for Traffic Scene Analysis. In 2024 IEEE International Conference on Image Processing (ICIP) (pp. 908-914). IEEE.

Sun, Y., Lu, B., Liu, Y., Yang, Z., Behera, A., Song, R., Yuan, H. and Jiang, H., 2024. Exploiting Label Uncertainty for Enhanced 3D Object Detection From Point Clouds. IEEE Transactions on Intelligent Transportation Systems.

Farooq, M., De Silva, V., & Shi, X. (2024, July). An Attention-based Ensemble Model for Emotion Recognition in Conversation. In 14th International Conference on Pattern Recognition Systems (ICPRS) (pp. 1-7).

De Silva, V., & Artaud, C. (2024, July). Adversarial Contrastive Representation Learning for Passive WiFi Fingerprinting of Individuals. In 14th International Conference on Pattern Recognition Systems (ICPRS) (pp. 1-7).

Artaud, C., De-Silva, V., Pina, R., and Shi, X. (2024). Generating neural architectures from parameter spaces for multi-agent reinforcement learning.Pattern Recognition Letters, 185, 272-278.

Illeperuma, M., Pina, R., De Silva, V., & Liu, X. (2024). Novel Directions for Neuromorphic Machine Intelligence Guided by Functional Connectivity: A Review. Machines, 12(8), 574.

Pina, R., De Silva, V. and Artaud, C., 2024. Towards Self-Adaptive Resilient Swarms Using Multi-Agent Reinforcement Learning. In ICPRAM (pp. 410-417).

Pina, R., Artaud, C., Liu, X., and De Silva, V. (2023, May). Staged Reinforcement Learning for Complex Tasks Through Decomposed Environments. In International Conference on Intelligent Systems and Pattern Recognition (pp. 141-154). Cham: Springer Nature Switzerland.

Artaud, C., Pina, R., Shi, X. and De-Silva, V., 2023, May. Policy Generation from Latent Embeddings for Reinforcement Learning. In International Conference on Intelligent Systems and Pattern Recognition (pp. 155-168). Cham: Springer Nature Switzerland.