Amsterdam

Diliara Valeeva

Diliara is an Assistant Professor in Computational Social Science at the Political science department of the University of Amsterdam. She received her PhD at the Amsterdam School for Social Science Research in 2021. Before joining the UvA, she worked as a postdoctoral researcher at the Geography department of the KU Leuven. Diliara's current research is on business and finance, corporate elites and power, and social networks. Diliara also works as a Lecturer at the BSc program in Computational Social Science at the UvA, and serves as a coordinator at the Social & Behavioral Data Science Center of the UvA, where she consults social scientists in utilizing data science methods, oversees community development, and coordinates funding.

Daniel Mayerhoffer

Daniel is Assistant Professor in the Bachelor Program Computational Social Science, a member of the Institutions, Inequalities, and Life courses research group in Sociology, and affiliated with the Data Science Centre. He uses Agent Based Simulation, among and in combination with other methods, to explain and predict complex socio-technical systems to enhance their governance. He applies Computational Models mainly to questions in Political Epistemology, Collective Behaviour and Economics. Furthermore, he evaluates these models from an analytical and Philosophy of Science perspective. Daniel's transdisciplinary background facilitates work on various topics and collaboration in diverse teams.

Johannes Aengenheyster

Johannes Aengenheyster is a PhD candidate in the Cultural Sociology programme group at the Sociology Department at the University of Amsterdam. He holds a Bachelor of Arts from University College Maastricht and a Master of Science from the University of Amsterdam. His research investigates the development of the population of private museums in terms of openings and closings, as well as their influence in the canonization of artists. His other interests include the structure and development of classification systems and computational methods.

Marie Labussière

Marie Labussière is a postdoctoral researcher at the Department of Sociology at the University of Amsterdam since September 2021. She studies social stratification and mobility using a variety of quantitative methods, including text mining and machine learning. Her current work in the CAREER ERC project focuses on the employment trajectories of workers in the context of changing labor markets, based on a combination of job advertisement data and panel data. Marie is also interested in improving the use and teaching of quantitative methods in the social sciences and is a strong advocate of open science. She holds an engineering degree from the French National School of Statistics and Economic Analysis (ENSAE) and a master's degree in interdisciplinary social sciences.

Reshmi G. Pillai

Reshmi is a PostDoc Researcher at the Department of Communication Science in the Vrije University Amsterdam. She focuses on the adoption and implementation of artificial intelligence techniques, specifically natural language processing, in the context of local journalism. Her current research explores the construction of structured knowledge bases in the context of regional news media organizations in the Netherlands. Previously, she was a Lecturer at the Informatics Institute, University of Amsterdam, in the Master's program in Information Studies (Data Science track). She holds a PhD from the University of Wolverhampton for her thesis on the expressions of psychological stress in tweets.