A new multimodal dataset and architecture combining egocentric vision and physiological signals for in-the-wild emotion and personality recognition, presented at NeurIPS 2025 …
Systematic study of multimodal emotion recognition in natural human-chatbot interactions, evaluating text, acoustic, and behavioral signal fusion strategies. ICMI 2024.
Multimodal affective state prediction from smartphone touch and sensor data in naturalistic conditions, using deep learning fusion. CHI 2022.
Semi-supervised learning for affective state prediction from smartphone touch data, leveraging abundant unlabeled naturalistic data. CHI 2020.
Multimodal deep learning systems for affective state prediction from smartphone sensors, biometric data, egocentric vision, and physiological signals — enabling real-world …