Allison Lewis
Research area: My research is focused in the field of uncertainty quantification (UQ), a subfield of mathematical modeling that explores how uncertainties in model inputs propagate through the model to impact our trust and certainty in various quantities of interest. Since arriving at Lafayette, I have been working primarily in the field of mathematical oncology, exploring how UQ techniques can be utilized to connect complex models describing cancer growth to typically sparse clinical data in such a way as to optimize the information gain from such models.
My Lafayette journey: I began my teaching journey at Lafayette in 2018, after graduating from North Carolina State University in 2016 with my Ph.D. in applied mathematics and spending two subsequent years working at Johns Hopkins University Applied Physics Laboratory and St. Mary’s College of Maryland. While at Lafayette, I have taught numerous courses in mathematical modeling, differential equations, and statistics.
What I will be teaching in the fall: This fall, I will be teaching MATH 287: Introduction to Data Modeling and MATH 301: Case Studies in Math Modeling.
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