The lab is jointly supported by the Department of Surgery and Department of Anesthesiology in the School of Medicine.
Research Experience
The lab's research areas include synthesizing physiological waveforms, wearable sensors, and social determinants with adaptive AI, aiming to untether hospital-level care from traditional settings, ensuring equitable, precision interventions. The work also involves bridging granular biology and societal context, empowering clinicians with transparent, real-time systems that honor the complexity of human illness. The goal is to transform medical care where decentralized innovation nurtures resilience, from cells to communities.
Background
Research interests include merging robotics, multi-modal AI, and integrative science to redefine medical care. The 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.
Miscellany
The lab envisions a decentralized and democratized future for medical care, focusing on transforming medical care through decentralized innovation.