Advances in large language models (LLMs) have empowered a variety of applications.
However, there is still a significant gap in research when it comes to understanding and …

Advances in wearable sensing and mobile computing have enabled the collection of health
and well-being data outside of traditional laboratory and hospital settings, paving the way for …

Despite the plethora of telehealth applications to assist home-based older adults and
healthcare providers, basic messaging and phone calls are still the most common …

Recent efforts to predict stress in the wild using mobile technology have increased; however,
the field lacks a common pipeline for assessing the impact of factors such as label encoding …

Despite a rich history of investigating smartphone overuse intervention techniques, AI-based
just-in-time adaptive intervention (JITAI) methods for overuse reduction are lacking. We …

Understanding the dynamics of mental health among undergraduate students across the
college years is of critical importance, particularly during a global pandemic. In our study, we …

Today's AI systems for medical decision support often succeed on benchmark datasets in
research papers but fail in real-world deployment. This work focuses on the decision making …

The recent technology boost of large language models (LLMs) has empowered a variety of
applications. However, there is very little research on understanding and improving LLMs' …

Problematic smartphone use negatively affects physical and mental health. Despite the wide
range of prior research, existing persuasive techniques are not flexible enough to provide …

Studies of dataset development in machine learning call for greater attention to the data
practices that make model development possible and shape its outcomes. Many argue that …