
EPPS Math and Coding Camp
The EPPS Math and Coding Camp is designed to offer first-year EPPS graduate students one week of training in fundamental Math and basic programming. We focus on preparing and inspiring students with applicable math and data analysis techniques for upcoming graduate research methods courses.
Duration
5-day intensive program
Venue
- Math Camp: JO 3.516 (3rd floor, Erik Jonsson Academic Center)
- Coding Camp: SCI 1.210 (1st floor, Sciences Building)
Objectives
- Strengthen foundational mathematical and coding skills necessary for data-driven research.
- Prepare students for research in varied disciplines in EPPS.
- Motivate and engage students in mathematics and data-driven research to enhance their future academic and professional projects.
- Introduce tools and software for statistical analysis and data handling.
Curriculum Outline
Day 1 & 2: Mathematical Foundations
- Day 1: Core Mathematics
- Morning: Linear Algebra essentials
- Afternoon: Functions and Relations
- Day 2: Statistics and Probability
- Morning: Calculus fundamentals
- Afternoon: Probability
Day 3 to 5: Coding and Data Analysis
- Day 3: Introduction to R
- Morning: R Programming Basics
- Afternoon: Data and Object types, Data Manipulation
- Day 4: Applied Coding Data Project
- Morning: Data Visualization
- Afternoon: Linear models
- Day 5: Project Day and Case Studies
- Morning: Advanced Math topics
- Afternoon: Group project preparation and Presentations
Teaching Methods
- Interactive Lectures: Introduce each concept with real-world applications.
- Hands-on Labs: Problem sets, including data manipulation and analysis.
- Group Projects: Encourage collaboration on research questions.
- Guest Lectures: Invitations to experienced researchers and professionals.
Resources Provided
- Course Materials: Comprehensive notes and online resource links.
- Software Training: In-person lecture and optional online illustrations
- Support: Continuous access to teaching assistants and faculty for guidance.
Assessment
- Practical Exercises: Daily tasks to ensure understanding of core concepts.
- Group Project: Final day presentation to apply concepts to a chosen problem.
This camp design aims to motivate interest in using math and coding techniques for future learning and research.
Meet the Instructors

Karl Ho
Karl Ho, Ph.D. is Professor of Instruction and Organizing faculty of the EPPS Math and Coding Camp. He is also the Director of Graduate Studies of Political Science in the School of Economic, Political and Policy Sciences at the University of Texas at Dallas. He co-founded the Social Data Analytics and Research program at UTD. Currently he offers data science courses in preparing data scientists in different disciplines. His research areas cover elections, public policy and political economy with a regional focus on East Asia and data science methods including data collection and production, data visualization, database and language models. He is the Principal Investigator of the Taiwan Studies Program at UTD and co-Principal Investigator of DFW Quality of Life project, He is the author or co-author of articles in journals such as Asian Affairs, Asian Politics & Policy, Asian Survey, Electoral Studies, Human Rights Quarterly, Journal of African and Asian Studies, Journal of Electoral Studies, Journal of Information Technology and Politics and Social Science Quarterly. His recent works were published in the books The Taiwan Voter (University of Michigan Press) and Taiwan’s Political Re-Alignment and Diplomatic Challenges (Lynne Riener). He is co-editor of the 2021 book Taiwan: Environmental, Political and Social Issues (Nova Science).

Brennan Stout
Brennan Stout is currently a second year Ph.D. student in Geospatial Information Sciences at the University of Texas at Dallas. His research interests focus on spatial statistics and remote sensing. Brennan’s current research involves the study of the spatial distribution of risky behaviors, namely alcohol and tobacco consumption and census data. Additionally, modelling supply and demand of alcohol and tobacco for the purpose of supporting epidemiological research of diseases related to consumption of those substances. Brennan is currently a teaching assistant for GIS classes at the University of Texas at Dallas.

Dongeun Kim
Dongeun Kim is a Ph.D. student in Geospatial Information Sciences at The University of Texas at Dallas, where she also serves as a teaching assistant and instructor. Her research focuses on spatial health disparities, location-allocation modeling, and advanced spatial analytics. She is the lead author of several peer-reviewed publications in journals such as Healthcare and Spatial Statistics, and a recipient of multiple awards including the Research/Teaching Assistant Scholarship, Pioneer Student Research Grant and Betty & Gifford Travel Award.
Prior to her doctoral studies, Dongeun earned her M.A. in Geography Education from Ewha Womans University in South Korea, where she developed expertise in machine learning applications to urban problems. She has contributed to government-funded research projects in Korea on smart city safety, disaster data systems, and AI-driven tourism services.
Her recent work explores spatial imputation on Location-Allocation problem solutions, spatial disparities in access to dialysis care and multilevel spatial survival analysis. Dongeun has presented at international conferences including the American Association of Geographers and the Regional Science Association International.
She is proficient in spatial tools such as ArcGIS Pro, QGIS, R, Python, and SQL, and holds certifications in SQL development, data analytics, and information processing. Committed to integrating spatial science with real-world challenges, Dongeun’s work aims to inform health equity and spatial decision-making through rigorous geospatial research.

Taowen Hu
Taowen Hu is a Ph.D. candidate in Economics at the School of Economic, Political and Policy Sciences at The University of Texas at Dallas. Her research examines how financial market volatility influences the transmission and effectiveness of monetary policy, with a focus on uncertainty, financial conditions, and macroeconomic dynamics. In addition to her academic research, Taowen serves as an instructor for the undergraduate course Money and Banking at UT Dallas. She enjoys teaching and values clear communication, patience, and thoughtful engagement with students. In her classes, she aims to help students develop a solid understanding of monetary systems by linking economic theory to real-world examples and empirical research.