Publications and Presentations
Publications
Monte Carlo Efficacy of IRT Software Estimation – Co-Author 
Title: "A Monte Carlo Comparison of the Efficacy of Mplus, flexMIRT, PROC IRT, ltm, and mirt in IRT Models Estimation."
Status: In preparation
Role: Led data collection, simulation design, and comparative analysis under supervision of Yi Zheng and Mark Reiser
Description: This study assesses the relative estimation accuracy of leading IRT software packages using simulation studies to inform psychometric modeling best practices. I designed simulations, developed preprocessing tools, and visualized RMSE and bias across all subjects.
18th ICCBM – First Author
Title: "Data Analysis Tools for the Compact X-ray Light Source and Compact X-ray Free Electron Laser Facilities at ASU"
Authors: Kurth, A., Botha, S., Everett, E., Ketwala, G., Verlarde, A., Grant T. G., Kirian, R.
Conference: 18th International Conference for the Crystallization of Biological Macromolecules (ICCBM)
Date: October 2024
Description: Presented novel tools for femtosecond crystallography data analysis at CXLS and CXFEL. Our framework enhances structure determination efficiency through algorithmic innovation.
Presentations
NASA HRP Investigator's Workshop – First Author, Poster
Title: "Developing Natural Language Processing and Supervised Machine Learning Techniques to Classify Mars Tasks"
Date: January 2025
Authors: Kurth, A., Rehm, H., Matar, M.
Affiliation: NASA Glenn Research Center, CHP-PRA
Abstract: Presented an NLP framework to address imbalanced multilabel classification for Mars mission data. Our approach improves human systems task categorization for future spaceflight planning.
NASA HRP Investigator's Workshop – Third Author
Title: "Large Language Models and Generative AI Tools to Depict Human Systems’ Contribution to Spaceflight Tasks"
Date: January 2025
Authors: Matar, M., Rehm, H., Kurth, A.
Affiliation: NASA Glenn Research Center
NASA CHP-PRA Research Discussion – Presenter
Title: "Using Natural Language Processing AI Tools to Analyze Mars Tasks"
Date: August 2024
Authors: Kurth, A., Rehm, H., Matar, M.
Description: Led the presentation on applying LLMs to mission task documentation using both supervised and unsupervised learning models.
BioXFEL Spring Symposium – Poster
Title: "Peak Intensity Analysis for Serial Femtosecond Crystallography Experiments at the Compact X-ray Light Source"
Authors: Kurth, A., Botha, S.
Affiliation: CXFEL Labs, ASU Biodesign
Abstract: Developed new Bragg peak integration techniques and noise-differentiation methods tailored to compact XFEL setups. This approach enables improved data accuracy in low-flux crystallography settings.
CXLS Deep Learning Report – Poster
Title: "Enhancing X-ray Peakfinding Through Deep Learning at the Compact X-ray Light Source (CXLS)"
Authors: Kurth, A., Everett, E., Botha, S.
Affiliation: Biodesign Beus CXFEL Lab, ASU
Abstract: Designed and benchmarked CNN architectures for Bragg peak prediction using simulated data from the CXLS beamline. Explored classification robustness under dynamic scattering conditions and low-flux regimes.