معرفی
Helge Marahrens is a Postdoctoral Fellow at the Massive Data Institute, Georgetown University. He holds a PhD in Sociology and an MS in Applied Statistics from Indiana University. His interdisciplinary work bridges sociology, statistics, and data science, focusing on large-scale patterns of inequality and globalization.
His educational background includes:
- PhD in Sociology, Indiana University (2023)
- MS in Applied Statistics, Indiana University (2019)
Marahrens' research centers on global inequality, city development, forced migration, and cultural tastes. He employs computational methods such as webscraping, APIs, text mining, network analysis, and machine learning to study how globalization reproduces hierarchies between cities, regions, and nations, particularly between the Global North and South. He is deeply engaged in advancing computational social science through innovative data collection and analytical techniques.
Although no publications are listed, his methodological focus suggests strong contributions in data science applications to sociological questions, particularly using Python-based tools for text and network analysis.
He has received recognition through competitive opportunities such as an internship at Facebook’s core data science group and leadership in prominent methodological workshops.
Marahrens has extensive teaching experience, having led Python workshops and lab courses at Indiana University and Georgetown. He has taught topics including data collection via APIs and webscraping, predictive modeling, text mining, and network analysis. He served as a lab instructor for graduate courses such as Categorical Data Analysis and Statistical Techniques in Sociology, and taught undergraduate courses like Understanding Social Data. His pedagogical approach emphasizes making complex methods tangible through hands-on learning and interactive tools, such as web applications for understanding logistic regression.
He has been affiliated with research centers including the Complex Networks and Systems Center at Indiana University and currently works at the Massive Data Institute at Georgetown University, where he continues to develop and apply computational methods in social science research.
