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
2026-2027 Academic Year
Fall 2026
COMP 180 Introduction to Data Science
Cross-listed with DATA 180-01 and MATH 180-01.
COMP 180 Introduction to Data Science
Cross-listed with DATA 180-02 and MATH 180-02.
DATA 180 Introduction to Data Science
Cross-listed with COMP 180-01 and MATH 180-01.
DATA 180 Introduction to Data Science
Cross-listed with COMP 180-02 and MATH 180-02.
MATH 180 Introduction to Data Science
Cross-listed with COMP 180-01 and DATA 180-01.
MATH 180 Introduction to Data Science
Cross-listed with COMP 180-02 and DATA 180-02.
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.
Spring 2027
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 Special Topics
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.