This research explores whether altering bodily sensations can change emotional experiences. By manipulating perceived heartbeat, blinking, and muscle tension through wearable devices and virtual reality, it demonstrates that emotions can be reshaped without changing physiology, opening new possibilities for treating trauma, anxiety, eating disorders, and other mental health conditions

This research develops a machine learning system that automatically assesses the quality of wearable sensor data before it is used for clinical decision-making. By filtering unreliable signals and distinguishing noise from genuine health events, the approach aims to improve diagnostic accuracy, reduce false alarms, and enable trustworthy medical use of wearable technologies.

My research uses AI and wearable technology to track brain and body signals such as brain waves (EEG), heart rate, and movement. The goal?  Spotting early signs of Alzheimer's and Parkinson's before symptoms show up. Catching these subtle changes could mean helping people sooner, letting them enjoy the everyday moments that matter most