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 “nanozymes,” nanoparticle-based catalysts that activate cancer drugs directly at tumor sites. Instead of carrying large amounts of chemotherapy drugs, nanozymes locally trigger inactive drugs into their active form only within cancer tissue. Early mouse studies show effective tumor destruction with significantly reduced side effects compared to conventional chemotherapy.

This research uses artificial intelligence to predict the progression of Alzheimer’s disease and cancer using medical imaging data. By analyzing brain scans, tumor scans, and treatment responses, AI models can forecast disease development and treatment outcomes, enabling earlier intervention, more personalized care, and improved quality of life for aging populations.

This research develops nanoscale “smart package” delivery systems for PROTAC cancer drugs. Antibody nanogel conjugates selectively target cancer cells, enter them, and release therapeutic molecules while minimizing exposure to healthy tissue. The approach improves delivery efficiency and aims to reduce the severe side effects that often limit cancer treatment.

This research improves photoacoustic imaging, a technique that uses light-generated sound waves to visualize tissue oxygenation deep inside the body. By calibrating measurements using highly oxygenated arterial blood, the method overcomes longstanding accuracy limitations and avoids skin-tone bias, potentially improving early tumor detection and non-invasive monitoring of tissue health.

This research introduces iCares, a smart wound-monitoring bandage designed to detect infection and inflammation before visible symptoms appear. Using biosensors, fluid sampling, and machine learning, the system provides real-time wound analysis, enabling earlier intervention, personalized treatment, reduced complications, and improved healing outcomes for patients with chronic wounds.

This research models blood flow in narrowed arteries and during catheterization using the Herschel–Bulkley fluid model. By simulating flow and drug dispersion, it identifies factors affecting unpredictability. These insights enable optimized treatments, improved medical device design, and better visualization for clinicians, ultimately enhancing safety and outcomes in cardiovascular care.