Resume

• 2014

  Master’s Degree

  Focus on data science & machine learning\n\nThesis : Informing the Use of Hyper-Parameter Optimization Through Metalearning -- Created process and predictive models that determine whether hyper-parameter optimization will yield improved results within a given time frame.

  Computer Science

  Brigham Young University

  3.9/4.0

  Advanced Neural Networks

  Bayesian Methods in Computer Science

  Advanced Topics in Data Mining

  Machine Learning & Data Mining

• 2013

  Brigham Young University

  Argonne National Laboratory

  Lucid

  MerchantWords

  MerchantWords

  Brigham Young University

  Provo

  UT

  Taught Introduction to Computer Programming to a class of ~80 novice programming students. Developed in-class programming experiences for students providing hands-on exposure to challenging concepts. Wrote multiple-choice and programming midterms that were administered to ~300 students.

  Instructor

  Provo

  UT

  Part of a ~10-person team directed by Professor Christophe Giraud-Carrier focused on applying data mining in major research projects in computational health science

  metalearning and social capital.\n\nProjects:\n\nInforming the use of Hyperparameter Optimization Through Metalearning\n-- Created process and predictive models that determine whether hyper-parameter optimization will yield improved results within a given time frame.\n-- Implemented custom hyper-parameter optimization software package (GenOpt) to meet project requirements.\n-- Utilized distributed computing capabilities of BYU’s supercomputer to perform ~20

  000 experiments that ran for 24 hours each by automating the job submission process through bash scripts.\n-- Collected and analyzed extensive hyper-parameter data

  validating hypothesis that hyper-parameters have meaningful impact on learning algorithm performance.\n\nValidation of Quantitative Regional Atrophy Dementia Classification in a Large Clinical MRI Sample\n-- Led the machine learning effort to test the reliability of classification of dementia patients using brain volume obtained from different brain regions and assessed whether these measurements were sufficiently reliable for diagnosis.

  Research Assistant

  Brigham Young University

  Argonne

  IL

  Assisted in developing a hydration map to model the flow of fertilizer waste from the Ohio River basin to the Gulf of Mexico.

  Intern

  Argonne National Laboratory

  Lucid

  English

  Research Grant

  Annual grant awarded to fund mentored research experiences

  BYU Office of Research and Creative Activities

• 2008

  Bachelor’s Degree

  Minor - Computer Science

  Mathematics

  Minor -- Computer Science

  BYU Women in Math Club

  Brigham Young University

  3.9/4.0

• Organized gatherings for female math majors to explore math careers and network with peers.

  BYU Women in Math Club

  Data Miner

  Assisted analyzing call data from the Utah County Crisis Line to help improve their service to the community and assess the group's effectiveness; created data visualizations using Tableau.

  Utah Valley University - Utah Data Dive

  Google Cloud Platform (GCP)

  Python

  SQL

  Machine Learning

  Data Science

  Apache Airflow

  PySpark

  Validation of Quantitative Regional Atrophy Dementia Classification in a Large Clinical MRI Sample

  Jared Nielsen

  Christophe Giraud-Carrier

  Jeffrey Anderson

  Predicting the type of dementia using machine learning from functional magnetic resonance imaging (fMRI) scans

  Validation of Quantitative Regional Atrophy Dementia Classification in a Large Clinical MRI Sample

  Samantha