Rüya Koçer is a statistician with a PhD in (Computational) Social Science. Koçer’s research interests center on understanding how complex dynamics underpinning societal order can be analysed through conventional statistical methods and modern machine learning techniques.

More information about Rüya Koçer

Rüya Koçer is a statistician with a PhD in (Computational) Social Science. Koçer’s research interests center on understanding how complex dynamics underpinning societal order can be analysed through conventional statistical methods and modern machine learning techniques.

Short CV

After obtaining his doctorate from the University of Amsterdam, Koçer worked at the International Labor Organization, where he analysed employment relations in Africa and contributed to the design of ILO’s decent work indicators. He then moved to the University of Geneva on a Swiss National Science Foundation Research Grant, where he examined the employment effects of development policies in six countries in Africa and East Asia. In this research, he scrutinized the social embeddedness of minimum wage dynamics and the effect of social capital on economic growth.

Upon returning to the Netherlands in 2017, Koçer began working at the University of Twente, where he developed a mathematical model to identify privileged groups within interest representation organizations and explored intuitive methods for teaching statistical inference. He later transitioned to the private sector, working as a principal data scientist in an international finance organization, focusing on algorithmic discrimination and the ethics of artificial intelligence. In 2023, he returned to academia at Leiden University. Throughout his career, in addition to his work as a computational social scientist, Koçer has collaborated with scientists from various disciplines, contributing to their research as a statistician.

Research

Koçer’s research interests center on understanding how complex dynamics underpinning societal order—with its economic, social, and ethical components—can be analysed through conventional statistical methods and modern machine learning techniques. Within this context, he is especially intrigued by (1) whether/how the interaction between artificial intelligence and humans affect the social order. How can we measure the aggregate impact of this interaction? (2) whether/how the replacement of human judgement by artificial intelligence would alter the nature of various selection processes. (3) how the use of artificial intelligence in decision making leads to discrimination among people on the basis of known and unknown sensitive characteristics and how can we diagnose and prevent such a discrimination. (4) whether/how various ethical conventions can be captured and expressed mathematically and when necessary can be incorporated into algorithm design. (5) how the use of artificial intelligence can be democratized and the transparency and accountability of artificial intelligence can be ensured.

Beyond these research areas, Koçer is also passionate about teaching statistical inference and machine learning in intuitive ways. He aims to make these subjects accessible to social scientists and laypersons alike through heuristic examples and visualizations.