Lung Integrative AI and Omics Lab
What We Do
Multi-omics for Sarcoidosis and Interstitial Lung Disease Progression
Deciphering sarcoidosis and interstitial lung disease progression and fibrotic subphenotypes through integrative multi-omics, with a focus on metabolomic and proteomic biomarkers to enable prediction and precision phenotyping.
Population Genomics of Chronic Respiratory Diseases
Leveraging large-scale biobanks—including All of Us Research Program, UK Biobank, and UCLA ATLAS Precision Health Biobank—to identify genetic determinants of chronic respiratory diseases such as chronic obstructive pulmonary disease (COPD), asthma, sarcoidosis, and interstitial lung disease (ILD).
AI for Multimodal Diseases Prediction
Developing artificial intelligence methods that integrate multi-omics, chest imaging, and clinical data to predict disease progression and enable precision management of chronic respiratory diseases.
Publications
Our lab members publish in high-impact journals spanning respiratory medicine, genomics, and translational science, including journals such as the American Journal of Respiratory and Critical Care Medicine (AJRCCM), CHEST, and other leading venues.
Areas of Focus
Multi-omics Biomarker Discovery
We integrate metabolomics, proteomics, transcriptomics, and genetics to identify blood-based biomarkers that improve diagnosis and predict disease progression in sarcoidosis and ILD.
Disease Endotyping and Mechanisms
We define molecular subphenotypes of sarcoidosis by uncovering pathways that drive inflammation and fibrosis, enabling a deeper understanding of disease heterogeneity.
Predictive Modeling and Precision Medicine
We apply advanced computational and AI approaches to combine multi-omics with clinical data, imaging, and lung function to predict disease trajectories and guide personalized treatment strategies.