Faculty Profile
Zach Kessler
Assistant Professor of Data Analytics (2024)
Contact Information
Althouse Hall
717-254-8082
Bio
My research interests broadly fall at the intersection of economics, data science, and computer science. In particular, I use computational methods to build large-scale simulations of social systems such labor markets, housing markets, and institutional processes. In addition, I study the impact of AI on various occupations and industries. My current work examines how workers with a variety of skills sort themselves across different kinds of businesses and whether these emergent patterns are socially optimal. I also work with coauthors to determine the value of specific skills in shaping worker mobility and replacement risk from AI. Lastly, I use reinforcement learning methods to evaluate if alternative institutional frameworks provide improved governance and policy outcomes relative to those currently in use.
Education
- B.S., Florida Southern College, 2018
- M.A., George Mason University, 2020
- Ph.D., 2022
2025-2026 Academic Year
Fall 2025
COMP 200 Data Syst for Data Analytics
Cross-listed with DATA 200-01.
COMP 200 Data Syst for Data Analytics
Cross-listed with DATA 200-02.
DATA 200 Data Syst for Data Analytics
Cross-listed with COMP 200-01.
DATA 200 Data Syst for Data Analytics
Cross-listed with COMP 200-02.
DATA 201 Agent-Based Simulation
Cross-listed with COMP 203-01 and ECON 314-03. In this course, you will expand your data science skills to explore Agent-Based Modeling using languages like Python and NetLogo. Through the semester we will explore a variety of applications in economics, sociology, ecology, and more, emphasizing data-driven simulations of complex systems. This robust method will enable you to create highly detailed models covering critical areas like supply chains and trade networks, the impact of commercial fishing on aquatic environments, the rapid disappearance of historic civilizations, the emergence of wealth inequality in economies, and the spread of misinformation in social networks. In addition to this toolkit, you will learn various programming principles such as vectorized programming, object-oriented design, and key principles of visualization. By the end of the course you will have a fundamental understanding of the core ideas of complex systems analysis, the ability to build agent-based models across a variety of contexts, and a collection of core programming skills which will assist you in building other advanced models.
COMP 203 Agent-Based Simulation
Cross-listed with DATA 201-01 and ECON 314-03. In this course, you will expand your data science skills to explore Agent-Based Modeling using languages like Python and NetLogo. Through the semester we will explore a variety of applications in economics, sociology, ecology, and more, emphasizing data-driven simulations of complex systems. This robust method will enable you to create highly detailed models covering critical areas like supply chains and trade networks, the impact of commercial fishing on aquatic environments, the rapid disappearance of historic civilizations, the emergence of wealth inequality in economies, and the spread of misinformation in social networks. In addition to this toolkit, you will learn various programming principles such as vectorized programming, object-oriented design, and key principles of visualization. By the end of the course you will have a fundamental understanding of the core ideas of complex systems analysis, the ability to build agent-based models across a variety of contexts, and a collection of core programming skills which will assist you in building other advanced models.
ECON 314 Agent-Based Simulation
Cross-listed with DATA 201-01 and COMP 203-01. In this course, you will expand your data science skills to explore Agent-Based Modeling using languages like Python and NetLogo. Through the semester we will explore a variety of applications in economics, sociology, ecology, and more, emphasizing data-driven simulations of complex systems. This robust method will enable you to create highly detailed models covering critical areas like supply chains and trade networks, the impact of commercial fishing on aquatic environments, the rapid disappearance of historic civilizations, the emergence of wealth inequality in economies, and the spread of misinformation in social networks. In addition to this toolkit, you will learn various programming principles such as vectorized programming, object-oriented design, and key principles of visualization. By the end of the course you will have a fundamental understanding of the core ideas of complex systems analysis, the ability to build agent-based models across a variety of contexts, and a collection of core programming skills which will assist you in building other advanced models.
DATA 500 Independent Study
Spring 2026
COMP 200 Data Syst for Data Analytics
Cross-listed with DATA 200-01.
DATA 200 Data Syst for Data Analytics
Cross-listed with COMP 200-01.
DATA 201 Data Visualization
How do we turn data into compelling stories, actionable insights, and effective visuals? In this course, students learn to design effective visualizations by applying best practices from visual perception, design theory, and data storytelling. Students build interactive dashboards in Microsoft Power BI and Qlik, focusing on logistics, performance monitoring, and real-world applications. Students create customizable visualizations using R or Python, emphasizing exploratory analysis, statistical graphics, and visual storytelling. By blending theory and practice, this course prepares students to communicate data-driven insights clearly and persuasively across a wide range of domains.