Projects

An open family of models, code, and evaluation tools that makes time series a native modality for language-model reasoning.

On-device time-series language-model inference, bringing multimodal methods closer to the phones people already use.

A reproducible pipeline connecting wearable time series with language through deterministic, signal-grounded captions.

A wearable-health dataset available to qualified researchers, with reproducible foundation-model baselines for prediction, imputation, and forecasting.

A Python library and command-line interface for registering, fetching, and exploring heterogeneous time-series datasets through one shared format.

An experimental app that helps patients ask questions about their own health records and prepare for clearer conversations with their care team.

Stanford’s supervisory system in the ARPA-H ADVOCATE program will screen actions proposed by cardiovascular care agents and give reviewers a rationale for flagged claims.

Extracting and clustering patient needs from portal conversations, then studying how they change across cardiovascular, kidney, and metabolic health.

A clinical collaboration studying whether explanations grounded in health records can support reproductive health literacy and patient-provider communication.

A research prototype exploring record-grounded explanations and evidence-based preparation for a spine-care consultation.

A mobile-friendly, printable patient education resource for heart failure basics, goals, treatment conversations, and clinical visits.

An open-source coding agent for biomedical research, connecting analysis work with reviewable actions, persistent sessions, and documented evidence.

Infrastructure for agent-assisted research and writing, keeping manuscript claims connected to references, analysis inputs, and reproducible figures.

A Stanford collaboration connecting secure research environments, multimodal models, and agent-assisted workflows for biomedical discovery.

A longitudinal digital cardiovascular study connecting wearable sensing, patient-reported data, active tasks, health records, and personalized activity coaching.

Now enrolling participants to study how brief pauses before social-media use relate to sleep, physical activity, and wellbeing, with a focus on adolescents.

A family of connected-care research applications combining home measurements, patient-reported outcomes, education, and structured communication in heart failure.

Earlier exploration of spatial interfaces for low-vision accessibility, with related interests in clinical education and surgical contexts.