Data Chair

Data

A full day workshop in conjunction with ACM Multimedia 2022

Participation

Alice Baird

Hume AI, USA, alice [at] hume.ai

Alice Baird is an audio researcher with interdisciplinary expertise in machine learning, computational paralinguistics, stress, and emotional well-being. She earned her Ph.D. at the University of Augsburg, where she was supervised by Dr. Björn Schuller. Her work on emotion understanding from auditory, physiological, and multimodal data has been published extensively in the leading journals and conferences in her field, including Interspeech, ICASSP, IEEE Intelligent Systems, and the IEEE Journal of Biomedical and Health Informatics.


Alexander Kathan

University of Augsburg, GER, alexander.kathan [at] informatik.uni-augsburg.de

Alexander Kathan received his M.Sc. degree in Business Analytics from the University of Ulm, Germany, in 2021. Currently, he is pursuing his Ph.D. degree with the Chair of Embedded Intelligence for Health Care and Wellbeing at the University of Augsburg, Germany. His research interests include deep learning and machine learning methods for audio and multimodal signal processing in healthcare applications, as well as personalised machine learning approaches.

Panagiotis Tziraks

Hume AI, USA, panagiotis [at] hume.ai

Dr. Panagiotis Tzirakis is a computer scientist and AI expert with expertise in machine learning, deep learning, and emotion recognition. He earned his Ph.D. with the Intelligent Behaviour Understanding Group (iBUG) at Imperial College London, where he focused on multimodal emotion recognition efforts. He has published in top outlets including Information Fusion, International Journal of Computer Vision, and several IEEE conference proceedings on topics including 3D facial motion synthesis, multi-channel speech enhancement, the detection of Gibbon calls, and emotion recognition from audio and video.