Thomas Vandal is a PhD student in the SDS Lab pursuing a degree in Interdisciplinary Engineering under the supervision of Auroop Ganguly. Thomas has a BS in Mathematics from the University of Maryland. Prior to joining the SDS lab, he worked as a Data Scientist at Affectiva Inc. where he developed techniques and tools to analyze large scale time series data of facial expressions. As part of his work, he used deep learning to classify facial expressions with a mixture of labeled and unlabeled data.

Thomas is interested in applying machine learning methods to large and complex datasets. In the SDS lab, he works on data mining of spatiotemporal data to identify and predict climate extremes.