This research develops a physics-based method for measuring lung elasticity from medical imaging to predict which emphysema patients will benefit from lung valve treatment. By creating detailed elasticity maps, the work aims to improve treatment selection, enhance patient outcomes, and provide new quantitative tools for assessing lung health.

This research develops a robotic system capable of reproducing real-world knee motions and ACL injury mechanisms in human cadaver knees. The platform enables realistic testing of injury-prevention technologies, improves understanding of ACL rupture biomechanics, and may help reduce injury risk, particularly among women who experience higher ACL injury rates.

This research applies fluid mechanics, numerical simulations, and machine learning to model the brain’s waste-clearance system during sleep. By investigating how fluid moves through brain tissue and how aging or injury affect this process, the work aims to identify strategies for preventing or slowing neurodegenerative diseases such as Alzheimer's.

This research develops soft, tissue-like implantable sensors capable of monitoring molecular signals inside the body in real time. By combining high-performance electronics with flexible, biocompatible materials, these devices could detect inflammation, stress, or organ damage before symptoms arise, enabling earlier diagnosis and more personalized healthcare.

This research develops nanobubble-enhanced ultrasound imaging as an accessible alternative to MRI for cancer diagnosis. Tiny gas-filled nanoparticles amplify ultrasound signals and improve image quality, particularly in prostate cancer. The technology could reduce diagnostic delays, lower costs, and provide high-quality medical imaging to more patients worldwide.

This research develops antibacterial nanostructured surfaces inspired by natural materials such as cicada wings. The engineered surfaces physically rupture bacteria using nanoscale needle-like structures, avoiding traditional antibiotics and reducing the likelihood of antibiotic resistance. The technology could improve infection control in medical devices, implants, and hospital environments.

This research develops advanced brain-machine interface systems to improve life for spinal cord injury patients. Using neural networks such as FinNet and dynamic recurrent neural decoders, the work aims to better extract and translate brain activity into movement while creating low-power hardware capable of supporting long-term practical neuroprosthetic applications.

This research develops a noninvasive method for continuously measuring blood pressure using arterial resonance. Inspired by the physics of vibrating guitar strings, the device gently stimulates arteries and measures their resonance frequencies with ultrasound. The resulting continuous blood pressure waveforms could improve diagnosis of cardiovascular disease without invasive catheterization procedures.

This research combines focused ultrasound and engineered genetic circuits to activate cancer immunotherapy directly within solid tumors. By locally triggering immune-stimulating cytokines such as IL-12, the approach aims to convert “cold” tumors into “hot” tumors while minimizing systemic toxicity, potentially expanding curative immunotherapy treatments to more cancer patients.

This research develops engineered ultrasonic reporters that allow ultrasound imaging to detect molecular activity rather than only anatomical structure. By targeting biological signals associated with cancer progression and cellular communication, the work aims to distinguish aggressive disease earlier and improve precision medicine through real-time, noninvasive monitoring of underlying cellular behavior.