Back 19-03-2024 Ágata Lapedriza. Emotion perception: challenges and use cases.

19-03-2024 Ágata Lapedriza. Emotion perception: challenges and use cases.

06.03.2024

 

Tuesday March 19th 2024, 12:30h - 13:30h. Room 52.S29 (Roc Boronat 138, Barcelona)

Emotion perception: challenges and use cases.

Ágata Lapedriza, Northeastern University (Institute for Experiential AI) and a Tenured Professor at Universitat Oberta de Catalunya

One of the challenges Human-Centered AI systems face is understanding human behavior and emotions considering the context in which they take place. For example, current computer vision approaches for recognizing human emotions usually focus on facial movements and often ignore the context in which the facial movements take place. In this presentation, I will talk about our work on emotion perception and will discuss the challenges we face when we attempt to create automatic models to perceive emotions. In the talk, I will also discuss possible use cases of emotion perception technologies.

Speaker

Agata Lapedriza is a Principal Research Scientist at Northeastern University (Institute for Experiential AI) and a Tenured Professor at Universitat Oberta de Catalunya. She is also an Affiliate Professor at the Bouvé College of Health Sciences at Northeastern University and a Research Affiliate at Massachusetts Institute of Technology (MIT) Medialab. Her research interests are related to Computer Vision, Natural Language Processing, Affective Computing, Explainable Artificial Intelligence (AI), Social Robotics, AI for Health and Wellness, and Fairness in AI. From 2012 to 2015 she was a Visiting Professor at MIT CSAIL, where she worked on Object Detection, Scene Recognition, and Explainabile AI. From 2017 to 2020 she was a Research Affiliate at MIT Medialab, where she worked on Emotion Perception, Emotionally-aware Dialog Systems, and Social Robotics. In 2020 she spent one year as a Visiting Faculty at Google (Cambridge, USA) and, more recently (2022-2023), she worked as a part-time contractor at Apple Machine Learning Research.

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