Ashlynn Crisp
- Program Year: 3
- Academic Institution: Portland State University
- Field of Study: Mathematical Sciences
- Academic Advisor: Daniel Taylor-Rodriguez
- Practicum(s):
Lawrence Berkeley National Laboratory (2024) - Degree(s):
B.S. Mathematics, Portland State University, 2021
Summary of Research
My research focuses on developing methods to model massive data. Scientific problems such as drug discovery and climate modeling require working with a massive amount of multivariate data, typically varying across time and space. Modern methods able to tackle scientific problems like these have become more accessible and commonplace in many fields. However, past a certain data size, even these methods may become infeasible due to their computational complexity. My work focuses on adapting algorithms to scale with the size and complexity of the data while reducing the tuning effort required. The aim of my research is to develop tools that enable scientists to make sense of datasets that were previously impossible to analyze.Publications
"Posterior Predictive Critique of a Psychometric Bayesian Model for Assessing Aphasia" (2021). Mathematics and Statistics Dissertations, Theses, and Final Project Papers. 2.https://pdxscholar.library.pdx.edu/mth_grad/2
"A Nonparametric Three-Sample Test", Poster, CSGF Annual Review, 2023
"Neural Network Informed Markov Chain Monte Carlo Methods" (2023). LLNL Technical Report.
Awards
Eugene Enneking Doctoral Fellowship, 2021Dean's Oregon Sports Lottery Graduate Scholarship, 2021
Best Data Visualization (Tie), ASA DataFest (Willamette University), 2021
UCLA B.I.G. Summer Research Excellence Award, 2020
H. Margaret Kolouch Scholarship, 2018, 2020
Dean's List, Portland State University, 2020
President's List, Portland State University, 2019
President's List, Portland Community College, 2016, 2017, 2018