The heart of CWU's interdisciplinary computational science master's program is computer-related, but the applications will be studied in the context of a number of scientific domains, including: biological sciences, environmental sciences, chemistry, computer science, geology, mathematics, and physics.

This collection features Master's theses from students in the Computational Sciences Program at Central Washington University.

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Theses from 2022

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Interpretable Machine Learning for Self-service High-risk Decision Making, Charles Recaido

Theses from 2021

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Water Surfaces Detection from Sentinel-1 SAR Images using Deep Learning, Chao Huang Lin

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Visualization for Solving Non-image Problems and Saliency Mapping, Divya Chandrika Kalla

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Full Interpretable Machine Learning Method with In-line Coordinates, Hoang Phan

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Bias and Fairness of Evasion Attacks in Image Perturbation, SiChong Qin

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Interactive Visual Self-service Data Classification Approach to Democratize Machine Learning, Sridevi Narayana Wagle

Theses from 2020

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Image Forgery Detection with Machine Learning, Lubna Alzamil

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Optimizing Pollution Routing Problem, Shivika Dewan

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Image Features for Tuberculosis Classification in Digital Chest Radiographs, Brian Hooper

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Toward Efficient Automation of Interpretable Machine Learning Boosting, Nathan Neuhaus

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Automatic Chest X-rays Analysis using Statistical Machine Learning Strategies, Hermann Yepdjio Nkouanga

Theses from 2019

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Classification of Stars from Redshifted Stellar Spectra utilizing Machine Learning, Michael J. Brice

Theses from 2018

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Spike-Based Classification of UCI Datasets with Multi-Layer Resume-Like Tempotron, Sami Abdul-Wahid

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Data Visualization and Classification of Artificially Created Images, Dmytro Dovhalets

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Decreasing Occlusion and Increasing Explanation in Interactive Visual Knowledge Discovery, Abdulrahman Ahmed Gharawi

Theses from 2017

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Visualizing Multidimensional Data with General Line Coordinates and Pareto Optimization, Jacob Brown

Theses from 2016

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Applications of Computational Geometry and Computer Vision, Joseph Lemley

Theses from 2015

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Using Time Series Models for Defect Prediction in Software Release Planning, James W. Tunnell