Below is a selection of theses from the Master of Science in Computational and Data Sciences program in Schmid College that have been included in Chapman University Digital Commons. Additional theses from years prior to 2019 are available through the Leatherby Libraries' print collection or in Proquest's Dissertations and Theses database.
Theses from 2024
Identifying a Target Protein and Ligands for Autoimmune Disorders, Sarah Caruthers
A Novel Correction for the Multivariate Ljung-Box Test, Minhao Huang
Predicting 30-Day Unplanned ICU Readmissions Using Deep Learning and Natural Language Processing Techniques: A MIMIC IV Data Analysis, David Licerio
Theses from 2023
Analyzing the Overturning of Roe vs Wade on Twitter using Natural Language Processing Techniques, Gabriela Pinto
Novel Implementation of Additive Manufacturing to Visualize the Human Brain Connectome, Greg Tyler
Theses from 2022
CausalModels: An R Library for Estimating Causal Effects, Joshua Wolff Anderson
Perturbation Modeling for Molecular Design of Protein Tyrosine Kinase Inhibitors using Unsupervised Machine Learning, Keerthi Krishnan
Modeling Similarities Among Autism Spectrum Patients Using Word Embeddings on Clinical Notes, Raha Pirzadeh
Theses from 2021
Identifying Functional Profiles of Challenging Behaviors in Autism Spectrum Disorder with Unsupervised Machine Learning, Emily Daskas
An Information-Theoretic Analysis of Adherence to Physical Exercise Routines, Lily Foster
Enhancing Microbiome Host Disease Prediction with Variational Autoencoders, Celeste Manughian-Peter
Automated Parsing of Flexible Molecular Systems using Principal Component Analysis and K-Means Clustering Techniques, Matthew J. Nwerem
Drug Repurposing for COVID-19 Using Molecular Docking Tools, Deniz Yasar Oztas
Theses from 2020
Computational Molecular Docking Models and Design of Diarylpentanoids for the Androgen Receptor, Jarett Guillow
Theses from 2019
Classifying Challenging Behaviors in Autism Spectrum Disorder with Neural Document Embeddings, Abigail Atchison
A Machine Learning Approach to Predicting Alcohol Consumption in Adolescents From Historical Text Messaging Data, Adrienne Bergh
Exploring the Impact of Challenging Behaviors on Treatment Efficacy in Autism Spectrum Disorder, Juliana Hoag
Exploring Age-Related Metamemory Differences Using Modified Brier Scores and Hierarchical Clustering, Chelsea Parlett
Development and Validation of Wearable Systems for Human Postural Sway Analysis, Michael Pollind
De novo Sequencing and Analysis of Salvia hispanica Transcriptome and Identification of Genes Involved in the Biosynthesis of Secondary Metabolites, James Wimberley
Theses from 2016
Assisting Children Action Association Through Visual Queues and Wearable Technology, Anthony Young
Theses from 2015
An Application of the Autism Management Platform to Tracking Student Progress in the Special Education Environment, Ryan Thomas Burns