Lace M. Padilla

schoolNortheastern Universitybar_chart#2157 Global Rank

Total Papers

HCI Rank

#2157

Research Areas

Years Active

Recent Publications

MIND: Empowering Mental Health Clinicians with Multimodal Data Insights through a Narrative Dashboard

Advances in data collection enable the capture of rich patient-generated data: from passive sensing (e.g., wearables and smartphones) to active self-reports (e.g., cross-sectional surveys and ecological momentary assessments). Although prior research has demonstrated the utility of patient-generated data in mental hea…

CHI '265th+ AuthorTelemedicine & Remote Patient Monitoring +1

Exploring Collaboration Breakdowns Between Provider Teams and Patients in Post-Surgery Care

Post-surgery care involves ongoing collaboration between provider teams and patients, which starts from post-surgery hospitalization through home recovery after discharge. While prior HCI research has primarily examined patients’ challenges at home, less is known about how provider teams coordinate discharge preparati…

CHI '261st AuthorHonorable MentionInteractive Data Visualization +2

Examining Interpretation Strategies for Multiple Forecast Visualizations with Two and Four Forecasts

Multiple forecast visualizations (MFVs) present curated sets of forecasts to support decision-making under uncertainty. However, the research community knows little about how people interpret and integrate competing forecasts. In this study, we investigate the strategies individuals use when predicting hypothetical fu…

CHI '252nd AuthorMultilingual & Cross-Cultural Voice Interaction +3

Lost in Translation: How Does Bilingualism Shape Reader Preferences for Annotated Charts?

Visualizations are powerful tools for conveying information but often rely on accompanying text for essential context and guidance. This study investigates the impact of annotation patterns on reader preferences and comprehension accuracy among multilingual populations, addressing a gap in visualization research. We c…

CHI '245th+ AuthorExplainable AI (XAI) +2

Rethinking Human-AI Collaboration in Complex Medical Decision Making: A Case Study in Sepsis Diagnosis

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 of sepsis, an acute life-threatening systematic infection that requires an early diagnosis with high uncertainty from the clinician. Our aim…

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