Passion to Learn and Explore

As an undergraduate research assistant, I had the opportunity to work on a project that used machine learning algorithms to predict the efficacy of bupropion in patients with major depressive disorder based solely on EEG data. The use of EEG data in this project was particularly exciting for me because it provides a quantitative way to determine whether or not a medication will work before the patient takes it, which saves time and money and reduces patient suffering. I worked closely with my supervisor, Dr. Maryam Ravan, to develop a model that was > 86% accurate in predicting the medication's efficacy. This was a great accomplishment for both of us and it was extremely satisfying to know that our work could have a real impact on people's lives. I am grateful for the experience and the skills I gained during this project and am excited to continue exploring the possibilities of machine learning in the future.