Sean completed his bachelor’s at Emory University with a major in neuroscience and a minor in math. At Emory, he studied the social network structure of rhesus macaques using social network analysis. He then completed a master’s in medical neurosciences at the Charité – Universitätsmedizin Berlin. His master’s thesis focused on using machine learning algorithms to predict Alzheimer’s and dementia up to 10 years before clinical diagnosis.
At Trinity, he is a PhD candidate using passively collected smartphone data to predict when substantial changes in depressive symptoms occur. He is funded by a Provost’s PhD award from Trinity.
Email: sekelley [at] tcd.ie
Sean’s Google Scholar.
Kelley, S. W., Mhaonaigh, C. N., Burke, L., Whelan, R., & Gillan, C. M. (2022). Machine learning of language use on Twitter reveals weak and non-specific predictions. NPJ Digital Medicine, 5(1), 1-13. [pdf]
Kelley, S. W., & Gillan, C. M. (2022). Using language in social media posts to study the network dynamics of depression longitudinally. Nature Communications, 13(1). [pdf]