We present Trivana, an on-device mental health mobile application that enables holistic, proactive, and privacy-preserving support. The system integrates multimodal user inputs, a forecasting model for anticipating mental health risks, and a local …
Mental health challenges among college students continue to rise, motivating scalable and proactive support. Passive smartphone sensing provides an unobtrusive way to capture behavioral signals related to mental well-being, enabling machine learning …
Many users want to reduce their screen time and time spent on social media. Yet, most existing interventions rely on static rules that may not fully account for variations in user context and receptivity. In this paper, we propose the design of …
Contemplative traditions have long guided ethical behavior and prosocial interaction, and recent work suggests that contemplative principles (e.g., mindfulness, compassion, non-dual reasoning) may offer a promising paradigm for aligning large …
The field of affective computing focuses on recognizing, interpreting, and responding to human emotions, and has broad applications across education, child development, and human health and wellness. However, developing affective computing pipelines …
The COVID-19 pandemic has intensified the urgency for effective and accessible mental health interventions in people's daily lives. Mobile Health (mHealth) solutions, such as AI Chatbots and Mindfulness Apps, have gained traction as they expand …
Creating UI tests for mobile applications is a difficult and time-consuming task. As such, there has been a considerable amount of work carried out to automate the generation of mobile tests—largely focused upon the goals of maximizing code coverage …
Writing and maintaining UI tests for mobile apps is a time-consuming and tedious task. While decades of research have produced automated approaches for UI test generation, these approaches typically focus on testing for crashes or maximizing code …
Prefetching web pages is a well-studied solution to reduce network latency by predicting users' future actions based on their past behaviors. However, such techniques are largely unexplored on mobile platforms. Today's privacy regulations make it …