Sara Mathieson

Sara Mathieson is an Assistant Professor in the Department of Biology at the University of Pennsylvania, affiliated with the School of Arts & Sciences. Her research integrates computational methods, machine learning, and evolutionary biology to address complex questions in genomics.

Research Interests:

• Development of machine learning algorithms for evolutionary inference
• Demographic modeling and detection of natural selection
• Generative modeling of genomic data (including GANs and transformers)
• Interpretability of deep learning in population genetics
• Genetic data privacy and representation
• Analysis of understudied populations using pedigree-based methods

Her lab currently focuses on applying these methods to human and mosquito (Anopheles gambiae) genomes, particularly to understand migration patterns and insecticide resistance evolution in African mosquito populations. Projects involve transformer-based architectures, hybrid models for introgression detection, and long-range dependency modeling in DNA sequences.

While no specific publications or awards are listed in the provided text, her work bridges computer science and biology, emphasizing both algorithmic innovation and biological interpretability.

Education:

• B.S., Massachusetts Institute of Technology, 2010
• Ph.D., University of California, Berkeley, 2015

Dr. Mathieson advises students through her lab and is actively involved in computational genomics research. She does not appear to have any listed scientific awards in the provided material, and there is no mention of grant funding, though her research scope suggests active grant-supported work. She leads the Mathieson Lab, a computational research group focused on next-generation genomic analysis tools.