Sara Mathieson

Sara Mathieson is an Assistant Professor of Biology at the University of Pennsylvania, affiliated with the Department of Biology. Her research interests include computational biology, evolutionary biology, genetics, epigenetics, and genomics. She develops computational and machine learning algorithms for evolutionary biology, focusing on inference tasks related to natural selection, demographic inference, and generative models for genomic data from various species. Her work also addresses interpretability of machine learning approaches, genetic data representation and privacy, and pedigree-based methods for understudied populations. She holds a B.S. from the Massachusetts Institute of Technology and a Ph.D. from the University of California, Berkeley.

Sara Mathieson is a researcher at the University of Pennsylvania specializing in machine learning and computational biology. Her work focuses on applying machine learning techniques to population genetic inference, demographic modeling, and the analysis of genomic data. She has developed methods for estimating effective population sizes, inferring natural selection, and reconstructing ancestral haplotypes. Her research includes the use of deep learning, generative adversarial networks, and convolutional neural networks to analyze genetic data from diverse populations. She has also contributed to scalable algorithms for population genomic inference and the interpretation of coalescent hidden Markov models. Her work has applications in understanding human adaptation, social stratification, and evolutionary processes in species such as malaria vectors.