Bio: Sofia Yfantidou is an early-stage researcher at the Aristotle University of Thessaloniki, and a Marie Skłodowska-Curie fellow at the Innovative Training Network "Real-time Analytics for the Internet of Sports" (RAIS). She works at the intersection of ubiquitous computing and machine learning fairness. Her current research focuses on defining, quantifying, and mitigating biases in data and models for health and well-being. She is a Heidelberg Laureate Forum alumna, a Grace Hopper scholar, and a European Joint Master Degree graduate in "Big Data Management and Analytics" from Université Libre de Bruxelles (ULB), Universitat Politècnica de Catalunya (UPC) and Technische Universität Berlin (TUB).

Bio: Dimitris Spathis is a senior research scientist at Nokia Bell Labs, Cambridge (UK) and a visiting researcher at the University of Cambridge. His work enables AI to make the most out of real-world multimodal data through label-efficient and robust ML. He previously worked at Microsoft Research, Telefonica Research, Ocado, and Qustodio. His recent work includes publications in top venues such as NeurIPS, KDD, and Nature Digital Medicine. Last, he serves on the program committees of leading academic conferences (AAAI, IJCAI, and KDD), and his research projects have been featured in international media (BBC, CNN, Guardian, Washington Post, Forbes, and Financial Times).

Bio: Marios Constantinides is a Senior Research Scientist at Nokia Bell Labs, Cambridge (UK) and a visiting researcher at the University of Cambridge. He works in the areas of human-computer interaction, UbiComp, and responsible AI. His current research focuses on building AI-based technologies that augment people's interactions and communication, with a particular focus on the workplace. He has been a member of the organizing committee of the SensiBlend workshop at UbiComp 2021, and co-organized two Special Interests Groups (SIG) at CHI 2023 on future of work and responsible AI.

Bio: Tong Xia is a third-year PhD candidate at the Department of Computer Science and Yechnology of the University of Cambridge. Her research interests lie in data mining, ML, and UbiComp for public health and human well-being. Particularly, she is keen to develop data-efficient, high-performance, uncertainty-aware and privacy-preserving mobile health systems. Her studies have validated the great promise of leveraging sounds from mobile devices for reliable respiratory pathology screening at the population scale. She previously worked at Tencent and she has been a committee member of the UK-Tsinghua association. She also served as the Posters & Demos session chair in UbiComp, 2022.

Bio: Niels van Berkel is an Associate Professor at Aalborg University. His work focuses on the design and evaluation of intelligent computing systems, particularly in real-world contexts, publishing in HCI, Social Computing, and Ubiquitous Computing. He has previously served as organiser of workshops at UbiComp ("UbiTtention" 2020, "Mobile Human Contributions" 2018, "Sensors & Behaviour" 2018) and CHI ("2VT" 2021, "Emergent Interaction" 2021), and served on the editorial board for IJHCS (2019-present) and ACM TiiS Special Issue on Human-Centered Explainable AI.