معرفی
Markus Strohmaier is Professor and Chair of Data Science in the Economic and Social Sciences at the University of Mannheim, with affiliations as Scientific Coordinator at GESIS – Leibniz Institute for the Social Sciences and External Faculty Member at the Complexity Science Hub Vienna. His interdisciplinary work bridges computer science, economics, and the social sciences.
- University of Mannheim – Chair for Data Science in the Economic and Social Sciences
- GESIS – Scientific Coordinator for Digital Behavioral Data
- Complexity Science Hub Vienna – External Faculty
- Former Professor at RWTH Aachen University and University of Koblenz-Landau
- Previous Post-Doc and Visiting Roles at Stanford University, Xerox PARC, University of Toronto, and Graz University of Technology
His research focuses on computational social science, algorithmic fairness, network science, and the modeling of human behavior using machine learning and large-scale data. He develops methods to analyze textual, relational, and emerging data types to understand socioeconomic systems and digital societies.
The recent articles reflect a strong trend in studying inequality in algorithmic systems, governance in decentralized organizations (DAOs), and psychological profiling of AI. His work spans high-impact journals like Nature and Scientific Reports, emphasizing fairness, transparency, and societal impact of data-driven technologies.
Notable scientific contributions include:
- Editor-in-Chief of EPJ Data Science (2018–2022)
- Founding co-chair of the Computational Social Science section of the German Informatics Society
He advises students and leads research projects on algorithmic fairness, digital governance, and behavioral modeling. His team engages in both fundamental methodological development and applied studies in real-world digital platforms. He has been involved in significant grants and collaborative initiatives around digital behavioral data and computational social science infrastructure.
His lab and projects include the Algorithmic Fairness initiative and the interactive visualization tool Planets of Disparity, which explores how algorithms behave on different network structures. These efforts aim to enhance public understanding and technical scrutiny of algorithmic systems.
