Debdeep Pati

Debdeep Pati is an Adjunct Professor in the Department of Statistics at Texas A&M University. His research focuses on developing Bayesian methodologies for complex data structures, including high-dimensional sparse vectors, matrices, non-Euclidean objects, and large graphs. He has explored Bayesian model selection consistency in complex settings and collaborated on applications such as tumor tracking in targeted radiation therapy. Recently, his work extends to modeling connectomics data to predict cognition and discovering patterns in large networks.