EPPS Math and Coding Camp

Dr. Karl Ho

Dr. Karl Ho is a 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 PhD student in Geospatial Information Sciences at The University of Texas at Dallas. His research interests focus on spatial statistics and remote sensing. His 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. He is also a teaching assistant for GIS classes at The University of Texas at Dallas.

Dongeun Kim

Dongeun Kim is a PhD 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, she 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, her work aims to inform health equity and spatial decision-making through rigorous geospatial research.

Taowen Hu

Taowen Hu is a PhD 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, she 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.

Xingyuan Zhao

Xingyuan Zhao is a PhD student in Political Science at The University of Texas at Dallas. His research focuses on leveraging Natural Language Processing (NLP) techniques to convert political text information into structured knowledge and derive meaningful insights. By leveraging cutting-edge NLP algorithms and domain expertise in political science, he aims to uncover hidden patterns and trends in political discourse that can inform policy-making and enhance our understanding of complex political phenomena. His ultimate goal is to bridge the gap between advanced NLP technologies and real-world political applications, contributing to more data-driven and evidence-based decision-making in the public sector.

Prajyna Paramita Barua Soni

Prajyna Paramita Barua is currently a PhD student in Economics from The University of Texas, Dallas. Her research interests lie in applied macroeconomics and labor economics, with a particular focus on their implications for monetary policy. Her current research delves into the dynamics of the U.S. labor market from a macroeconomic perspective. Specifically, she is examining the trade-off between vacancies and unemployment in the U.S. labor market under time variation, and assessing labor market efficiency and inefficiencies through the lens of the unemployment gap. In addition to her research, she is also engaged in teaching Principles of Macroeconomics at The University of Texas, Dallas.