I'm pursuing a computing PhD at the Scientific Computing and Imaging Institute (SCI) at the University of Utah under Dr. Shireen Elhabian's advisement. I joined SCI after working in machine learning and speech science for telephone transcription at CaptionCall. Before that, I earned my BS in Mathematics from Westminster College where I also minored in Physics and Computer Science and earned an honors certificate.
My research involves quantifying uncertainty in deep learning models for medical image analysis. I am interested in Bayesian and statistical methods for shape modeling from volumetric images. I focus on medical applications such as pathology detection and diagnosis in orthopedic, neuroscience, and cardiac research.
I recently completed an internship with the Machine Learning and Instrument Autonomy group at the NASA Jet Propulsion Lab. In this project I applied Bayesian deep learning techniques for an application in cosmology, Cosmic Microwave Background (CMB) recovery.
In my free time, I tend to my garden with my husband and dog. We also enjoy art, skiing, backpacking, and river rafting.Recent News:
- My journal article "Learning Spatiotemporal Statistical Shape Models for Nonlinear Dynamic Anatomies" was accepted for publication in the Frontiers in Bioengineering and Biotechnology Biomechanics.
- Accepted to participate in the AAAI 2023 Doctoral Consortium.
- My paper "Cosmic Microwave Background Recovery: A Graph-Based Bayesian Convolutional Network Approach" was accepted to the Conference on Innovative Applications of Artificial Intelligence (IAAI), part of AAAI 2023.
- I won the "Best Oral Presentation" award for my paper "Spatiotemporal Cardiac Statistical Shape Modeling: A Data-Driven Approach" at the MICCAI Statistical Atlases and Computational Modeling of the Heart (STACOM) workshop, 2022.
- My paper "From Images to Probabilistic Anatomical Shapes: A Deep Variational Bottleneck Approach" was early accepted at the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2022.