Eduardo Gutiérrez Maestro

PhD Student

AASS Research Center
School of Science and Technology
Örebro University
70182 Örebro, Sweden
Room: T2214
Phone: No Phone Number Available
Email: No Email Address Available

Google Scholar

Eduardo is a Ph.D student at the Center for Applied Autonomous Sensor Systems (AASS) Cognitive Robotic System Lab. He is employee at the University of Örebro by to the Wallenberg AI, Autonomous Systems and Software Program (WASP).

He received BSc in Telematics Engineering (2016) and MSc in Telecommunications Engineering (2019) from the University of Alcalá, Spain. In 2017 he studied half of his Masters studies at the Technische Universität Darmstadt, Germany.

As a researcher, Eduardo is focused to make use of AI (mainly Machine Learning and Deep Learning) to develop solutions which improve people’s mental health and life quality.


Publications

[1] T. Schreiter, T. R. d. Almeida, Y. Zhu, E. Gutiérrez Maestro, L. Morillo-Mendez, A. Rudenko, L. Palmieri, T. P. Kucner, M. Magnusson and A. J. Lilienthal. THÖR-MAGNI : A large-scale indoor motion capture recording of human movement and robot interaction. The international journal of robotics research 2024 [ BibTeX | DiVA ]
[2] E. Gutiérrez Maestro, H. Banaee and A. Loutfi. Towards Addressing Label Ambiguity in Sequential Emotional Responses Through Distribution Learning. In 12th International Conference on Affective Computing and Intelligent Interactions, Glasgow, United Kingdom, September 15-18, 2024 2024 [ BibTeX | DiVA ]
[3] E. Gutiérrez Maestro, H. Banaee and A. Loutfi. Stress Lingers : Recognizing the Impact of Task Order on Design of Stress and Emotion Detection Systems. In 2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, pages 175-176, 2023 [ BibTeX | DiVA | PDF ]
[4] T. Almeida, A. Rudenko, T. Schreiter, Y. Zhu, E. Gutiérrez Maestro, L. Morillo-Mendez, T. P. Kucner, O. Martinez Mozos, M. Magnusson, L. Palmieri, K. O. Arras and A. Lilienthal. 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), pages 2192-2201, 2023 [ BibTeX | DiVA ]
[5] E. Gutiérrez Maestro, T. R. d. Almeida, E. Schaffernicht and O. Martinez Mozos. Wearable-Based Intelligent Emotion Monitoring in Older Adults during Daily Life Activities. Applied Sciences, 13(9), 2023 [ BibTeX | DiVA ]
[6] T. R. d. Almeida, E. Gutiérrez Maestro and O. Martinez Mozos. Context-free Self-Conditioned GAN for Trajectory Forecasting. In 21st IEEE International Conference on Machine Learning and Applications. ICMLA 2022 : Proceedings, pages 1218-1223, 2022 [ BibTeX | DiVA ]
[7] T. Schreiter, T. R. d. Almeida, Y. Zhu, E. Gutiérrez Maestro, L. Morillo-Mendez, A. Rudenko, T. P. Kucner, O. Martinez Mozos, M. Magnusson, L. Palmieri, K. O. Arras and A. Lilienthal. The Magni Human Motion Dataset : Accurate, Complex, Multi-Modal, Natural, Semantically-Rich and Contextualized. 2022 [ BibTeX | DiVA | PDF ]
[8] F. M. Calatrava-Nicolás, E. Gutiérrez-Maestro, D. Bautista-Salinas, F. J. Ortiz, J. R. González, J. A. Vera-Repullo, M. Jiménez-Buendía, I. Méndez, C. Ruiz-Esteban and O. Martinez Mozos. Robotic-Based Well-Being Monitoring and Coaching System for the Elderly in Their Daily Activities. Sensors, 21(20), 2021 [ BibTeX | DiVA ]