"I believe in intuition and inspiration. Imagination is more important than knowledge. For knowledge is limited, whereas imagination embraces the entire world, stimulating progress, giving birth to evolution. It is, strictly speaking, a real factor in scientific research.”
― Albert Einstein 1929, quoted by Dr. Boris Kovalerchuk in Visual Knowledge Discovery and Machine Learning 2018.

Double Bachelor's of Science senior student majoring in Computer Science and Applied Mathematics. Active research assistant at the Visual Knowledge Discovery and Imaging Lab of Central Washington University. Former system administrator, full-stack software developer, and web-developer. Next, graduate studies in Computational Science focusing on visual machine learning. With a goal of building trusted expert artificial intelligence systems.

Solving problems at the intersection of machine learning and data visualization by blending machine computation with human cognition. Computing with data visualizations directly, instead of just making visuals. While integrating visual approaches with conventional machine learning methods.

Oxford Dictionary, "Intelligence", noun, 1. the ability to acquire and apply knowledge and skills. Current research goals: Aquire knowledge by visual knowledge discovery with multidimensional lossless visualizations, then apply aquired knowledge to build skills that solve difficult tasks more interpretably and accurately.

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2. "Boosting of Classification Models with Human-in-the-Loop Computational Visual Knowledge Discovery"

• Authors: Alice Williams & Dr. Boris Kovalerchuk.
• Status: Preprint under review by ArXiv. Presenting at HCII2025.
• Contributions: Introduces the Computational and Interactive Visual Learning (CIVL) framework, integrating human-in-the-loop visualization and computational techniques to improve classification model boosting, particularly in class-overlapping areas, by separating simple and complex cases, leveraging interpretable decision rules, and enhancing classifier accuracy and explainability through lossless multidimensional visualizations like Parallel Coordinates and General Line Coordinates (GLCs). This improves classification model boosting, particularly in class-overlapping areas, by separating simple and complex cases, leveraging interpretable decision rules, and enhancing classifier accuracy and explainability through lossless multidimensional visualizations achieving 100% accuracy on the Fisher Iris data with significantly fewer parameters than AdaBoost, which won the 2003 Gödel Prize, reducing the risk of overfitting by maintaining a high case-to-parameter ratio while offering enhanced interpretability.
• Topics: Visual Knowledge Discovery, Classification Model Boosting, Interpretable Machine Learning, Human-in-the-Loop, Lossless Visualization
• Developed software: Java_Tabular_Vis_Toolkit, HyperblockParser, InLineCoordinatesCoefficientSolver

1. "Synthetic Data Generation and Automated Multidimensional Data Labeling for AI/ML in General and Circular Coordinates"

• Authors: Alice Williams & Dr. Boris Kovalerchuk.
• Status: Published in IEEE proceedings and presented at IV2024 in track of Artificial Intelligence and Visual Knowledge Discovery, earned the 'Best Paper Award'.
• Contributions: Proposed an algorithm and implemented interactive software for labeled synthetic data generation using former General Line Coordinate methods and newly developed Circular Coordinates both Static and Dynamic with multi-class visualization and parameterized class discrimination. Addressed data balancing, demonstrated deficiencies of popular SMOTE (Synthetic Minority Oversampling Technique), and showed improvements to classifier performance across 14 standard machine learning classifiers.
• Topics: Synthetic Data Generation, Automated Data Labeling, General Line Coordinates, Circular Coordinates, Parallel Coordinates, Shifted Paired Coordinates, Tabular AI/ML Data, Multidimensional Data Visualization, Visual Knowledge Discovery.
• Developed software: Dynamic_Coordinates_Vis_System

Chronologically ordered from current at top to first at bottom.

In no preferential order.

I'm always open to discussing new projects or opportunities. Feel free to reach out or connect with me!