I am a Research Scientist at the Samsung AI R&D Center in Cambridge. From September 2016 to March, 2019, I was with the Computer Vision Lab, at the University of Nottingham. I obtained my PhD degree in Computer Science from the University of Nottingham in 2017, with a thesis on Continuous Regression for Face Tracking. In my previous life, I obtained my MSc in Signal Theory and Communications and my MEng in Telecommunications Engineering from the University of Vigo (Spain), in 2011 and 2009, respectively (GPA 8.0/10.0). I visited the Human Sensing Lab @ CMU for 6 months in 2011. My PhD was partially funded by the Vice-Chancellor’s Scholarship for Research Excellence, as well as by the School of Computer Science scholarship. Prior to this, I received a scholarship from the Fundación Pedro Barrié, to do a research stay @ the CVLab in Nottingham, in 2013.

My research interests are on the use of Deep Learning techniques for Facial Expression Recognition, as well as the fundamental theory behind the recent developments in generative methods using Deep Learning (VAEs and GANs).



Affective Processes: Stochastic modelling of temporal context for emotion and facial expression recognition
E. Sanchez, M. K. Tellamekala, M. Valstar, G. Tzimiropoulos
IEEE Int’l Conf. on Computer Vision and Pattern Recognition (CVPR)

A transfer learning approach to heatmap regression for action unit intensity estimation
I. Ntinou, E. Sanchez, A. Bulat, M. Valstar, G. Tzimiropoulos
IEEE Transactions on Affective Computing (TAFFC)

Self-supervised learning of person-specific facial dynamics for automatic personality recognition
S. Song, S. Jaiswal, E. Sanchez, G. Tzimiropoulos, L. Shen, M. Valstar
IEEE Transactions on Affective Computing (TAFFC)

Improving memory banks for unsupervised learning with large mini-batch,consistency and hard negative mining
A. Bulat, E. Sanchez-Lozano, G. Tzimiropoulos
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)


Unsupervised learning of object landmarks via self-training correspondence
D. Mallis, E. Sanchez, M. Bell, G. Tzimiropoulos
Advances in Neural Information Processing Systems (NeurIPS).

Semi-supervised facial action unit intensity estimation with contrastive learning
E. Sanchez, A. Bulat, A. Zaganidis, G. Tzimiropoulos.
Asian Conf. on Computer Vision (ACCV).

Unsupervised face manipulation via hallucination
K. Kusumam, E. Sanchez, G. Tzimiropoulos
Int’l Conf. on Pattern Recognition (ICPR)

Self-supervised learning of dynamic representations for static images
S Song, E. Sanchez, L. Shen, M. Valstar.
Int’l Conf. on Pattern Recognition (ICPR)

A recurrent cycle consistency loss for progressive face-to-face synthesis
E. Sanchez, M. Valstar
IEEE Int’l Conf. on Automatic Face Gesture Recognition (FG, Oral)


Object landmark discovery through unsupervised adaptation
E. Sanchez, G. Tzimiropoulos
Advances in Neural Information Processing Systems (NeurIPS).

Dynamic Facial Models for Video-based Dimensional Affect Estimation
S. Song, E. Sanchez-Lozano, M. K. Tellamekala, L. Shen, A. Johnston, M. Valstar
Int’l Workshop on Computer Vision for Physiological Measurement (ICCV’W - CVPM)


Joint Action Unit localisation and intensity estimation through heatmap regression
E. Sanchez, G. Tzimiropoulos, M. Valstar
British Machine Vision Conf. (BMVC).

A functional regression approach to facial landmark tracking
E. Sanchez-Lozano, G. Tzimiropoulos, B. Martinez, F. De la Torre, M. Valstar
IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(9), 2037–2050. (TPAMI)


Fera 2017 - addressing head pose in the third facial expression recognition and analysis challenge
M. Valstar, E. Sanchez-Lozano, J. Cohn, L. Jeni, J. Girard, Z. Zhang, L. Yin, M. Pantic
IEEE Int’l Conf. on Automatic Face Gesture Recognition (FG).

Continuous Regression: A functional regression approach to real-time facial landmark tracking
E. Sanchez-Lozano
PhD Thesis (PhD)


Cascaded continuous regression for real-time incremental face tracking
E. Sanchez-Lozano, B. Martinez, G. Tzimiropoulos, M. Valstar
European Conf. on Computer Vision (ECCV).

Cascaded regression with sparsified feature covariance matrix for facial landmark detection.
E. Sanchez-Lozano, B. Martinez, M. Valstar
Pattern Recognition Letters, 73, 19–25. (PRL)


Blockwise linear regression for face alignment
E. Sanchez-Lozano, E. Argones-Rua, J. Alba-Castro, J.
British Machine Vision Conf. (BMVC 2013).

Audiovisual three-level fusion for continuous estimation of Russell’s emotion circumplex
Enrique Sánchez-Lozano, Paula Lopez-Otero, Laura Docio-Fernandez, Enrique Argones-Rúa and José Luis Alba-Castro
Int’l Workshop on Audio/visual Emotion Challenge (AVEC)

Continuous regression for non-rigid image alignment
E. Sanchez-Lozano, F. De la Torre, D. Gonzalez-Jimenez
European Conf. on Computer Vision (ECCV 2012).