Sergio Escalera is Full Professor at the Department of Mathematics and Informatics, Universitat de Barcelona, where he is the head of the Informatics degree. He is ICREA Academia. He leads the Human Pose Recovery and Behavior Analysis Group. He is Distinguished Professor at Aalborg University. He is also a member of the Computer Vision Center at UAB. He is vice-president of ChaLearn Challenges in Machine Learning, leading ChaLearn Looking at People events. He is also Fellow of the ELLIS European Laboratory for Learning and Intelligent Systems working within the Human-centric Machine Learning program, member of the AAAC Association for the Advancement of Affective Computing, ACIA Catalan Association of Artificial Intelligence, AEPIA Artificial Intelligence Spanish Association, and vice-Chair of IAPR TC-12: Multimedia and visual information systems. He received an Amazon Research Award, a CVPR best paper award nominee and a CVPR outstanding reviewer award.

Research interests

Affective computing, computer vision, and machine learning, with special interest in characterizing people: personality and psychological profile computing. The main objective of his research is to reproduce from a computational perspective the human visual system so that intelligent systems can, ethically, provide with automatic interpretations of human behaviour from visual data coming from non-invasive environments/setups. This research is grounded on multi-disciplinarity, combining knowledge from computing, mathematics, artificial intelligence (computer vision and machine learning) and psychology to translate psychological theories into computational models. As a result he created pioneer models, mainly based on deep learning, that allow to detect and analyse people in visual data: from human posture estimation, facial expression analysis, action/gesture/interaction recognition, to the automatic detection of feelings and personality profiles.

Keywords

Computer Vision, Machine Learning, Human Posture Analysis, Human behavior Analysis, Action and Gesture Recognition, Convolutional Neural Networks, Emotion Recognition, Affective Computing, Personality Computing