Agata Lapedriza

Principal Research Scientist

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Agata Lapedriza
Principal Research Scientist

Agata Lapedriza is a Principal Research Scientist at the Institute for Experiential AI, where she leads research on AI for Health and Responsible AI. She is also Affiliated Professor at the Bouvé College of Health Sciences at Northeastern University. Her research interests are related to Computer Vision, Natural Language Processing, Affective Computing, AI for Health and Wellness, Social Robotics, and Responsible AI. More concretely, her current research focuses on Human-Centric AI, which refers to creating AI that meets human needs, enhances human capacities, and aligns with human values. Her research program includes fundamental research on explainable, contextualized, and multi-modal systems for emotion and social signal perception, and their use cases for Health and Human Wellness.

She is also a Professor at Universitat Oberta de Catalunya and a Research Affiliate at Massachusetts Institute of Technology (MIT) Medialab. From 2012 to 2015 she was a Visiting Professor at MIT CSAIL, where she worked on Object Detection, Scene Category and Attribute Recognition, and Explainable AI. From 2017 to 2020 she was a visiting professor at MIT Medialab Affective Computing group, where she worked on Emotion Perception, Emotionally-Aware Dialog Systems, and Human-Social Robot Interaction, focusing on the application of improving Emotional Well-being. During 2020-2021 she was a Visiting Faculty at Google (USA). Currently, she is a contractor at Apple Machine Learning Research.

She has served co-organizer in the “IEEE Conference on Affective Computing and Intelligent Interactions” 2023 (Program Chair); the “1st. International Workshop on Affective Understanding in Video”, at CVPR 2021; the “15th IEEE Conference on Face and Gesture Recognition”, 2020 (Workshops and Tutorials Chair), among many others. She regularly serves and as an Area Chair (e.g. NeurIPS 2023; ICLR2023; WACV2021; BMVC2021) and as a Program Committee member in Machine Learning / Affective Computing / Computer Vision Conferences and Journals.