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.

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Theses from 2024

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Identifying a Target Protein and Ligands for Autoimmune Disorders, Sarah Caruthers

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A Novel Correction for the Multivariate Ljung-Box Test, Minhao Huang

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Predicting 30-Day Unplanned ICU Readmissions Using Deep Learning and Natural Language Processing Techniques: A MIMIC IV Data Analysis, David Licerio

Theses from 2023

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Computational Molecular Docking Studies of Small Molecule Inhibitors With the SARS-CoV-2 Spike Protein Variants: In-Silico Drug Discovery Using Virtual Screening and Drug Repurposing Approaches, Grace Gupta

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Analyzing the Overturning of Roe vs Wade on Twitter using Natural Language Processing Techniques, Gabriela Pinto

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Novel Implementation of Additive Manufacturing to Visualize the Human Brain Connectome, Greg Tyler

Theses from 2022

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CausalModels: An R Library for Estimating Causal Effects, Joshua Wolff Anderson

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Development of Machine Learning Models for Generation and Activity Prediction of the Protein Tyrosine Kinase Inhibitors, Ryan Kassab

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Perturbation Modeling for Molecular Design of Protein Tyrosine Kinase Inhibitors using Unsupervised Machine Learning, Keerthi Krishnan

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Modeling Similarities Among Autism Spectrum Patients Using Word Embeddings on Clinical Notes, Raha Pirzadeh

Theses from 2021

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Identifying Functional Profiles of Challenging Behaviors in Autism Spectrum Disorder with Unsupervised Machine Learning, Emily Daskas

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An Information-Theoretic Analysis of Adherence to Physical Exercise Routines, Lily Foster

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Enhancing Microbiome Host Disease Prediction with Variational Autoencoders, Celeste Manughian-Peter

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Automated Parsing of Flexible Molecular Systems using Principal Component Analysis and K-Means Clustering Techniques, Matthew J. Nwerem

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Drug Repurposing for COVID-19 Using Molecular Docking Tools, Deniz Yasar Oztas

Theses from 2020

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Computational Molecular Docking Models and Design of Diarylpentanoids for the Androgen Receptor, Jarett Guillow

Theses from 2019

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Classifying Challenging Behaviors in Autism Spectrum Disorder with Neural Document Embeddings, Abigail Atchison

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A Machine Learning Approach to Predicting Alcohol Consumption in Adolescents From Historical Text Messaging Data, Adrienne Bergh

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Exploring the Impact of Challenging Behaviors on Treatment Efficacy in Autism Spectrum Disorder, Juliana Hoag

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Exploring Age-Related Metamemory Differences Using Modified Brier Scores and Hierarchical Clustering, Chelsea Parlett

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Development and Validation of Wearable Systems for Human Postural Sway Analysis, Michael Pollind

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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

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Assisting Children Action Association Through Visual Queues and Wearable Technology, Anthony Young

Theses from 2015

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An Application of the Autism Management Platform to Tracking Student Progress in the Special Education Environment, Ryan Thomas Burns