Jonathan Beagley

About Jonathan Beagley

Associate Professor of Mathematics and Statistics with a background in teaching, research, and interdisciplinary applications. I bring years of experience in higher education, currently focusing on data science and business analytics at both undergraduate and master\'s levels. My teaching portfolio spans mathematics, statistics, and data science, including courses like Computational Linear Algebra, Scientific Visualization, Data Mining, and Machine Learning. My research journey began in extremal combinatorics, using graphs to study lattices, then moved to enumerative, exploring topics such as inversions in Young Tableau, covering arrays, and convex sets. It has since evolved to include machine learning and data science applications. Recent projects include using LLMs to create summaries of course lectures and combining Semantic Knowledge Graphs and previous work on lattice theory and posets to model concepts into a hierarchy to ground LLM responses to create course materials. In addition to teaching and research, I am proficient in Python and SQL, leveraging these tools to analyze data, develop models, and visualize insights. My work is driven by a passion for fostering learning, solving complex problems, and bridging theory with real-world applications. I earned my Ph.D. in Mathematics from George Mason University, and I continue to integrate my expertise in mathematics with the rapidly advancing fields of data science, analytics, and AI.

Experience

1. Associate Professor

   Valparaiso University

   Aug 2013 — Present · Valparaiso, IN, US

   Academic and Professional Experience:Experienced educator and researcher with a strong background in mathematics and a current focus on data science and business analytics.Teaching Experience:Extensive teaching portfolio spanning undergraduate and graduate courses, including:Mathematics: Finite Mathematics, Calculus Linear Algebra, Linear Systems and Matrices, Discrete Mathematics, Combinatorics I and II, Abstract Algebra I and II.Data Science and Business Analytics: Computational Linear Algebra, Scientific Visualization, Introduction to Data Science, Analytical Modeling, Data Mining, and Machine Learning.Research Expertise:Mathematics: Combinatorics research on inversions in Young Tableau, covering arrays, and convex sets.Pedagogy: Studied the impact of cumulative assessments on student performance.Data Science: Current research focuses on machine learning applications, including:Analyzing outliers in graph data.Investigating closing costs in Bitcoin\'s Lightning Network channels.Bitcoin transaction fee estimationSkilled at blending theoretical foundations with practical applications, enabling students and professionals to excel in interdisciplinary fields like data science, analytics, and applied mathematics.

Education

• George Mason University

  Ph.D., Mathematics

  2008 — 2013

• Illinois Institute of Technology

  B.S., Applied Mathematics

  2004 — 2008

• George Mason University

  MS, Mathematics

  2008 — 2011

Skills

• Systems Engineering
• Cuda
• Affirmative Recruitment
• Programming
• Dod
• Algorithms
• Teaching
• Integration
• Microsoft Excel
• Mathematics
• Program Management
• Microsoft Office
• Simulations
• C++
• Technical Writing
• Latex
• University Teaching
• Java
• Higher Education
• Research