Northeastern University
My research focuses on providing user-inspired interventions, such as daily summaries, for multiple stakeholders based on the daily activities of older adults. The first part of my research involves conducting sense-making of multimodal sensing data collected from older adults. We developed and implemented a multi-modal sensing system that includes wearable devices, smartphones, and smart home devices. Using the data we collected, we are developing a context-aware framework to synthesize insights using Language Model (LLM), specifically related to older adults' daily activities. Our ultimate goal is to create a visualization and annotation system where AI can assist researchers in understanding the status of older adults. The second part of my research focuses on behavior simulation and modeling for older adults based on expert knowledge and the sensing dataset. We aim to create AI agents that can simulate the behaviors of older adults, which will allow us to learn more about this population on a larger scale. Our next goal is to generate user-inspired customized daily summaries for multiple stakeholders based on the information synthesized from the previous steps. Our main focus is to conduct user studies with different stakeholders to understand their varying needs and address the gap in providing such information using existing systems.