Nate receives 2024 NSF Graduate Research Fellowship!

🎉 Exciting news! I am thrilled to announce that Nate has been granted the prestigious National Science Foundation (NSF) Graduate Research Fellowship! Collaborating with MD Anderson Cancer Center, his research will revolutionize the way we provide care to oropharyngeal cancer survivors. It’s a great honor to serve as his mentor, and I couldn’t be prouder of his remarkable achievements!

New NIH grant will answer whether wearables can improve health in LGBTQ + individuals

Did you know that 🏳️‍🌈 sexual and gender minorities (sometimes denoted LGBTQ+) have disproportionately high rates of depression, suicidal ideation, substance use, and physical health problems? Our new NIH grant will answer whether wearables can improve health disparities in LGBTQ + individuals during real-time social safety experiences in public settings by reducing their chronic threat-vigilance stress!

New grant from the American Cancer Society

Non-melanoma skin cancers are the most common cancers in the U.S. and their incidence is increasing. Electrical impedance dermography (EID) is a newer non-invasive, quantitative and objective tool sensitive to detect alterations in the electrical properties of skin cancers. The overarching hypothesis of this proposal is that EID can be used to distinguish cancer subtypes that cannot be appreciated clinically.

New R21 grant

Radiation-associated dysphagia (RAD) is a leading driver of quality of lige and a potentially life-threatening survivorship issue, afflicting more than half of patients treated with curative radiotherapy for head and neck cancers. In collaboration with MD Anderson Cancer Center in Houston, we will examine feasibility and criterion validity of surface electromyography as a rapid, non-invasive quantitative surveillance method for lingual denervation.

New NSF grant

I am thrilled to lead an #NSF grant focused on #wearable #bioimpedance #devices for #cuffless #bloodpressure. A novel aspect of our approach is the integration of #physiological, #computational, and #machinelearning models to establish the biological sources relating #fluiddynamics and #electricity.