Chris Wiggins is an applied mathematician with a PhD in theoretical physics who develops machine learning applications for the study biological problems. His areas of focus include analysis of microarray data, comparative genomics and population genetics, design of computer vision applications for microscopy and microscopic time-lapse data, statistical inference in single-molecule biophysics, and biological network inference and analysis. Additional research interests in systems biology include the stochastic modeling of transcriptional regulatory networks and the identification of relationships between the topology of biological networks and their realizable information-processing functions. Wiggins has been a faculty member in the Department of Applied Physics and Applied Mathematics since 2001 and is also a member of the Center for Computational Biology and Bioinformatics.