EPPS Math and Coding Camp

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).   

Dohyo Jeong

Dohyo Jeong is instructor of the EPPS Math and Coding Camp (2024). His research focuses on identifying and addressing regional disparities in resource allocation within global public health systems, emphasizing public health crisis management, public health services planning, and the social impacts of epidemiology. He has researched geographic patterns of infectious diseases such as tuberculosis and access to treatment, revealing regional disparities that affect treatment outcomes. His work on emergency medical services (EMS) highlights the importance of demand forecasting and resource optimization using spatial-temporal machine learning techniques. Dohyo also explores the social impacts of public health crises, including the distribution of COVID-19 treatments, the influence of pandemics on education and crime patterns, and the role of social media in managing public hysteria. His future research aims to investigate disparities from regional and individual perspectives, utilizing causal inference, machine learning, and spatial statistics to enhance public health policy and reduce health disparities. At UT Dallas, Dohyo Jeong served as an instructor for the EPPS Math and Coding Camp (2024), taught the EPPS 2302 Methods of Quantitative Analysis in the Social and Policy Sciences course, and delivered various guest lectures.

Azharul Islam

Azharul Islam is currently pursuing a Ph.D. in Economics at the School of Economic, Political, and Policy Sciences at UT Dallas. Prior to this, he earned a Master of Arts in Economics from Central Michigan University and Virginia Tech. Azharul’s research focuses on analyzing the impact of consumer sentiment on macroeconomic variables in the US, including GDP growth, unemployment, inflation expectations, and consumer price indices. He is also working on another independent project and three co-authored projects, all of which revolve around the common theme of inflation expectations within the context of the US macroeconomy. In addition to his research, Azharul teaches economics courses at UT Dallas as an instructor, where he relates economic theories to research findings to illustrate real economic phenomena. He is passionate about exploring the intersection of economics and policy, and aspires to make meaningful contributions to the macroeconomic field as an academic. Originally from Dhaka, Bangladesh, Azharul received his undergraduate degree in economics. Despite being physically separated by distance, he enjoys staying connected with his family members and relatives.

Shreyas Meher

Shreyas Meher is a PhD candidate in Public Policy & Political Economy at the University of Texas at Dallas, specializing in the intersection of digital economics, political analysis, and computational linguistics. His research primarily focuses on internet censorship, cyber law and policy, and content moderation in democratic contexts. Shreyas employs advanced machine learning techniques, including Large Language Models, to analyze political and social event data. As a key contributor to an NSF-funded project, Shreyas works on applying cutting-edge ML technologies like ConfliBERT to revolutionize event data extraction in political science. His dissertation explores the nuanced approaches of democracies to internet control, the politics of internet blackouts in India, and the global impact of major tech companies’ decisions in authoritarian markets. Shreyas’s work spans comparative politics, digital governance, and the application of computational methods to policy questions. He has presented his research at major conferences like APSA and MPSA, and has papers under review in notable journals. With a background in economics and energy management, Shreyas brings a multidisciplinary approach to studying the complex interplay between politics, economics, and digital spaces.

Xingyuan Zhao

Xingyuan Zhao is instructor of the EPPS Math and Coding Camp (2024). He is Ph.D. 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, Xingyuan 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

Prajyna Paramita Barua is currently pursuing her fifth year of Ph.D. 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. Prajyna’s 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, Prajyna is also engaged in teaching Principles of Macroeconomics at the University of Texas, Dallas.