Tiago Almeida
Tiago Almeida Position: Doctoral Student School/office: School of Science and TechnologyEmail: dGlhZ28uYWxtZWlkYTtvcnUuc2U=
Phone: +46 19 303725
Room: T2226
Research subject
Research environments
About Tiago Almeida
Tiago Rodrigues de Almeida holds an MSc in Mechanical Engineering from the University of Aveiro, Portugal. In October 2020, he started his Ph.D. in Computer Science at Örebro University and enrolled in the Wallenberg AI, Autonomous Systems program (WASP).
His main research focus is motion prediction and its possible connections with semantics about the target agent.
Publications
Articles in journals |
Conference papers |
Doctoral theses, monographs |
Articles in journals
- Schreiter, T. , Almeida, T. R. d. , Zhu, Y. , Gutiérrez Maestro, E. , Morillo-Mendez, L. , Rudenko, A. , Palmieri, L. , Kucner, T. P. & et al. (2024). THÖR-MAGNI: A large-scale indoor motion capture recording of human movement and robot interaction. The international journal of robotics research. [BibTeX]
- Almeida, T. R. d. , Zhu, Y. , Rudenko, A. , Kucner, T. P. , Stork, J. A. , Magnusson, M. & Lilienthal, A. J. (2024). Trajectory Prediction for Heterogeneous Agents: A Performance Analysis on Small and Imbalanced Datasets. IEEE Robotics and Automation Letters, 9 (7), 6576-6583. [BibTeX]
Conference papers
- Rudenko, A. , Zhu, Y. , Almeida, T. R. d. , Schreiter, T. , Castri, L. , Belotto, N. , Linder, T. , Vaskevicius, N. & et al. (2025). Hierarchical System to Predict Human Motion and Intentions for Efficient and Safe Human-Robot Interaction in Industrial Environments. In: 1st German Robotics Conference. Paper presented at 1st German Robotics Conference, Nuremberg, Germany, March 13-15, 2025. [BibTeX]
- Almeida, T. , Schreiter, T. , Rudenko, A. , Palmieri, L. , Stork, J. A. & Lilienthal, A. J. (2025). THÖR-MAGNI Act: Actions for Human Motion Modeling in Robot-Shared Industrial Spaces. In: 20th edition of the ACM/IEEE International Conference on Human-Robot Interaction. Paper presented at 20th ACM/IEEE International Conference on Human-Robot Interaction (HRI 2025), Melbourne, Australia, March 4-6, 2025. [BibTeX]
- Rodrigues de Almeida, T. & Martinez Mozos, O. (2023). Likely, Light, and Accurate Context-Free Clusters-based Trajectory Prediction. In: 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), 24-28 Sept. 2023 Proceedings. Paper presented at 26th IEEE International Conference on Intelligent Transportation Systems (IEEE ITSC 2023), Bilbao, Bizkaia, Spain, September 24-28, 2023. (pp. 1269-1276). IEEE. [BibTeX]
- Almeida, T. , Rudenko, A. , Schreiter, T. , Zhu, Y. , Gutiérrez Maestro, E. , Morillo-Mendez, L. , Kucner, T. P. , Martinez Mozos, O. & et al. (2023). THÖR-Magni: Comparative Analysis of Deep Learning Models for Role-Conditioned Human Motion Prediction. In: 2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW). Paper presented at IEEE/CVF International Conference on Computer Vision (ICCV) Workshops, Paris, France, October 2-6, 2023. (pp. 2192-2201). IEEE. [BibTeX]
- Almeida, T. R. d. , Gutiérrez Maestro, E. & Martinez Mozos, O. (2022). Context-free Self-Conditioned GAN for Trajectory Forecasting. In: Wani, MA; Kantardzic, M; Palade, V; Neagu, D; Yang, L; Chan, KY, 21st IEEE International Conference on Machine Learning and Applications. ICMLA 2022 Proceedings. Paper presented at 21st IEEE International Conference on Machine Learning and Applications (IEEE ICMLA), Nassau, Bahamas, December 12-14, 2022. (pp. 1218-1223). IEEE. [BibTeX]
- Schreiter, T. , Almeida, T. R. d. , Zhu, Y. , Gutiérrez Maestro, E. , Morillo-Mendez, L. , Rudenko, A. , Kucner, T. P. , Martinez Mozos, O. & et al. (2022). The Magni Human Motion Dataset: Accurate, Complex, Multi-Modal, Natural, Semantically-Rich and Contextualized. Paper presented at 31st IEEE International Conference on Robot & Human Interactive Communication, Naples, Italy, August 29 - September 2, 2022. [BibTeX]
Doctoral theses, monographs
- Almeida, T. (2025). Learning to Understand and Predict Heterogeneous Trajectory Data. (Doctoral dissertation). Örebro: Örebro University. [BibTeX]