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Pervasive computing has revolutionized how we collect data and interact with information. Research interest in pervasive computing has been growing exponentially over the years, demonstrating enormous potential in biomedical applications ranging from a research-fertile field to clinical translation and healthcare delivery [1]. The sophisticated capabilities of smartphones integrating diverse sensors along with wearable and non-wearable sensors provide the opportunity to collect longitudinal, multimodal data streams and facilitate near real-time monitoring, over and above standardized self-reports [1], [2], [3], [4]. Overall, digital technologies (e.g., smartphones and smartwatches) are becoming increasingly affordable and have already been embraced by many people including elders [2], [3], facilitating large scale investigations and clinical trials. Furthermore, ubiquitous devices such as standard telephones, for example, have been used to collect speech signals for healthcare assessments, enabling large studies (∼10000 people) within months, across multiple countries, with minimal cost [5]. Nation-wide studies reaching 100000+ people who contribute their data have become possible, such as the U.K. BioBank (https://www.ukbiobank.ac.uk/), which has enabled novel data explorations into incident cardiovascular disease at scale [6]. Many innovative solutions capitalizing on (large) data streams from different sources have been proposed, coupled with emerging advances in data science and machine learning which enable fast and advanced processing of the collected datasets [7].