Publications

CDEAtlas: Interactive Visualization and Exploration of Common Data Elements at Scale

A co-first-author paper at the AMIA 2026 Annual Symposium presenting CDEAtlas, an interactive visualization system for exploring NIH Common Data Elements at scale.

Echo: Visual Steering for AI-Assisted Cohort Definition and Comparison in Electronic Health Records

A co-first-author poster at IEEE VIS 2026 presenting Echo, a visual analytics workspace for inspecting, refining, and comparing AI-assisted EHR cohort definitions.

CDEAtlas: Interactive Visualization and Exploration of Common Data Elements at Scale

A first-author poster at the AMIA 2026 Amplify: Informatics Summit presenting CDEAtlas, an interactive visualization system for large-scale exploration of NIH Common Data Elements.

Designing a Visual Analytics Dashboard to Streamline Collaborative Common Data Element Mapping

A first-author poster presented at AMIA 2025, showcasing a clinical NLP dashboard that streamlines concept mapping and improves interpretability for researchers and clinicians.

CDEMapper 2.0: Expediting Collaborative Review and Facilitating Consensus Building During Common Data Elements Mapping

An AMIA 2025 poster presenting CDEMapper 2.0, an extension of CDEMapper that introduces a Delphi-style collaborative review framework with multi-role workflows for conflict resolution and expert consensus formation during NIH Common Data Element mapping.

My contributionI designed the user workflow framework illustration that visualizes the collaborative review process, and contributed to the interface design for the system.

CDEMapper: enhancing National Institutes of Health common data element use with large language models

A JAMIA-published study introducing CDEMapper, an LLM-powered tool that combines semantic search, GPT-based recommendations, and human-in-the-loop review to map local data elements to NIH Common Data Elements.

My contributionI contributed to evaluation workflows, system usability assessment, and visualization design for the CDE mapping pipeline.

Information Extraction from Clinical Notes: Are We Ready to Switch to Large Language Models?

A JAMIA study evaluating whether LLMs (LLaMA 3, GPT-4o) can replace BERT-based systems for clinical information extraction. Across two institutions, LLMs achieved up to 7% higher F1 on NER and 4% on relation extraction, with improved cross-institutional generalization.

My contributionI designed the user-facing interface for Kiwi, the clinical NLP system associated with this study. My work turns the LLM-based information extraction outputs into an inspectable, usable product for biomedical researchers.