Associate Professor, Mathematics and Computer Science
Adam Smith has scholarly interests in machine learning and its applications in computational biology, that is, the development of algorithms to solve important problems in biological domains. His work often involves bioinformatics, artificial intelligence, and time series analysis. Specifically Smith has been focused on analyzing and classifying time series within biological systems, including gene expressions and mouse ultrasonic vocalization. Smith’s doctoral work involved developing algorithms for the EDGE project, which aims to make the analysis of industrial chemicals faster, cheaper, and more accurate. His team developed machine learning methods to discriminate toxins based on gene expression levels. His postdoc research involved performing mathematical analyses of mouse ultrasonic vocalizations, with the aim of better understanding the state of a mouse through its vocalizations, so as to create a baseline when mice are used as models of mental disease, such as autism, schizophrenia, or traumatic brain injury. Smith has published work in journals including Math Horizons, PLoS Computational biology, and BMC bioinformatics. He teaches courses in areas including artificial intelligence, algorithms, and programming for the natural sciences.