[{"_1":2,"_186":-5,"_187":-5},"loaderData",{"_3":4,"_185":-5},"routes/news_.$slug",{"_5":6},"news",{"_7":8,"_9":10,"_11":-5,"_12":13,"_14":15,"_16":17,"_18":19,"_20":21,"_22":23,"_24":25,"_26":27,"_65":66,"_148":149},"id","9ce8effb-cb91-4749-bb86-6fe1c1182210","status","published","sort","user_updated","ff755970-69e2-4bda-ae11-3f4bf42322b9","date_updated",["D",1774892988147],"image","88de9358-fbdd-47d0-adf9-16472740875e","title","Liz presents at the SYNERGY series","date",["D",1770854400000],"description","

On Thursday February 12, 2026 @ 12:00-1:00pm, Liz will present our work to develop AI tools for person-centered dementia care.

More info about the talk is here: https://synergy.dartmouth.edu/mc-events/synergy-translational-and-learning-health-system-science-collaborative-series-2026-2/

And more info about the project is here: https://empowerlab.dartmouth.edu/projects/ai-dementia

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Liz specializes in human-computer interaction, information science, and social computing, focusing on applications in healthcare, STEM education, and environmental sustainability. Her primary expertise is in the domain of digital health, working to develop health monitoring and behavioral intervention technologies that emphasize inclusive design, patient empowerment, and health equity.

Before joining the Dartmouth faculty, Liz was a postdoctoral scholar in Computer Science at Stanford University and received her PhD in Information Science from Cornell University. After completing her undergraduate degree in Mathematics and Computer Science at MIT, she also spent 4 years as the lead engineer and head of experimental features of a CSAIL startup that built interactive visualization tools to help software developers make sense of complex codebases. Liz’s work continues to promote translational approaches that seek opportunities to meaningfully engage with and positively shape industry practices, local communities, and policy-making.

Fun facts! Liz grew up on the beach 🏖, loves to play volleyball 🏐, and her favorite music is industrial metal 😈.

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Dylan is a PhD student at Thayer School of Engineering, with a coursework focus on Computer Science. His research focuses on expanding understanding of Human-Centered Design and Human-AI interaction. Specifically, he is interested in exploring novel use cases of narrative-based communication with AI technology. His projects address problems of equity and accessibility at scale within the domains of digital health and education. Dylan is a Dartmouth Innovation Fellow and received a Masters of Engineering Management (MEM) at Dartmouth. Prior to Dartmouth, he worked as a software engineer at YouTube and Lark Health and has a Masters and Bachelors in Computer Science from Stanford University.

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Sonny is currently pursuing a Ph.D. in Computer Science at Dartmouth College, specializing in Human-Computer Interaction and Digital Health. His research centers on harnessing AI-generated music to enhance individuals' well-being, particularly in the realms of physical therapy and autism care.

",[113],"songyun-tao",{"_7":134,"_69":8,"_70":135,"_72":136},114,"fc089e69-cf1a-43a6-9638-c27d7aa10ade",{"_7":135,"_9":10,"_11":137,"_12":75,"_14":138,"_77":139,"_79":140,"_16":141,"_82":83,"_84":142,"_85":143,"_87":-5,"_88":89,"_90":144,"_92":145,"_95":96,"_24":146,"_98":147,"_100":-5},7,["D",1771304787858],"Emma","Ricci-De Lucca","126ce241-e9bd-4600-9edd-aeefc7cbdd3e","mental health, women's health, wearables, AI/ML","emma.g.ricci-de.lucca.th@dartmouth.edu","

Emma is a Biomedical Engineering PhD student working to bridge the gender health gap by creating technologies to improve women's health. Her current research focuses on the pressing needs and challenges within maternal health and how to leverage human-centered design to improve patient clinical outcomes.
Check out her portfolio here: link

",[113],"emma-ricci-de-lucca","https://scholar.google.com/citations?hl=en&user=1q4eYmQAAAAJ","news_projects",[150],{"_7":137,"_69":8,"_151":152,"_153":154},"projects_id","1014a742-8712-499c-9025-e10b89112790","projects",{"_7":152,"_9":10,"_11":-5,"_12":40,"_14":155,"_18":156,"_22":157,"_158":96,"_159":160,"_161":162,"_163":164,"_165":166,"_175":160,"_176":-5,"_177":-5,"_178":179,"_180":-5,"_24":181,"_182":-5,"_183":184},["D",1771873739457],"AI Infrastructure for Person-Centered Dementia Care","

Person-centered dementia care depends on caregivers’ ability to interpret subtle behavioral changes and share relational knowledge across shifts, roles, and families. However, high staff turnover, fragmented documentation, and inconsistent family engagement often erode continuity of care in long-term, resource-constrained care facilities.

This project introduces an AI-enabled narrative infrastructure designed to overcome these issues and support the full caregiving sensemaking loop:

Capturing meaningful moments during care interactions
Enriching them with clinical and contextual information
Synthesizing patterns over time
Delivering actionable, role-specific insight at the point of care

Developed through a multi-year collaboration with seven long-term care facilities in the Northeastern U.S. and Canada, the platform integrates directly into existing workflows, including memory-therapy sessions and electronic documentation systems. Rather than introducing a separate dashboard, it captures bounded care interactions, enriches them with contextual signals, and generates narrative summaries aligned with caregiver reasoning.

In real-world deployments, caregivers reported faster access to resident context, reduced repeated mismatched interventions, improved situational awareness across shifts, and greater confidence in care decisions while families reported increased transparency, improved trust, and more productive care conferences.

Overall, this work advances a model of narrative AI infrastructure: systems designed not only to document care but to preserve and circulate relational knowledge in complex, high-turnover environments.

","is_active","is_collaboration",false,"collaborators","

Memory care specialists at Memcara: Christina Tadin, Dio Tadin, Brian Morgan

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