Biomedical Data Science Research

We envision a decentralized & democratized future for medical care—merging robotics, multi-modal AI, and integrative science to redefine resilience. Our lab develops machine learning methods (causal inference, domain adaptation), robotic/automation frameworks and tools that decode whole-person health: from molecular genetics and multi-omics to psychosocial and environmental drivers of host resilience in acute injury, cystic fibrosis, trauma, and multi-organ failure.

By synthesizing physiological waveforms, wearable sensors, and social determinants with adaptive AI, we aim to untether hospital-level care from traditional settings, ensuring equitable, precision interventions. 

Our work bridges granular biology and societal context, empowering clinicians with transparent, real-time systems that honor the complexity of human illness. Join us to transform medical care—where decentralized innovation nurtures resilience, from cells to communities.