Caro holds a PhD in Survey Statistics from the University of Mannheim and over ten years of experience in statistical data analysis. She is an Assistant Research Professor at the University of Maryland, where she teaches statistics and method courses for the Joint Program in Survey Methodology (JPSM). 

Additional, Caro is a Researcher ("Akademische Rätin") at the Ludwig-Maximilians-Universität München (LMU), where she leads the Introduction to Statistics lecture and contributes to various projects at the Social Data Science and AI Lab (SODA). Her research interests span survey methodology, synthetic data, and large language models, and their implications for society.

Frauke holds the Chair of Social Data Science and AI Lab at LMU Munich, Germany and at the University of Maryland, USA, she is Co-director of the Social Data Science Center (SoDa) and faculty member in the Joint Program in Survey Methodology (JPSM). She is an elected fellow of the American Statistical Association, and received the Warren Mitofsky Innovators Award of the American Association for Public Opinion Research in 2020. In addition to her academic work, Professor Kreuter is the Founder of the International Program for Survey and Data Science (IPSDS); Co-Founder of the Coleridge Initiative, whose goal is to accelerate data-driven research and policy around human beings and their interactions for program management, policy development, and scholarly purposes by enabling efficient, effective, and secure access to sensitive data about society and the economy; and Co-Founder of the German language podcast Dig Deep (www.digdeep.de).

Helena is a student of communication science and statistics & data science at LMU Munich. She holds a degree in media science with a specialization on politics. She works as an research assistant at the Social Data Science and AI Lab (SODA) at LMU Munich and as a research assistant for DISELMA, a study to examine the role of digital media for people being affected by chronic disease.

Helena previously worked for Save the Children Germany and for the ONE Campaign in the area of policy and campaigns where she focussed on gender equality and organized events to raise awareness for issues in development policies such as food security, preventable diseases and human rights in global supply chains.

Leah is a PhD candidate at the University of Mannheim and a research associate at the Social Data Science and AI Lab (SODA) at LMU Munich. Her work centers around improving the understanding of public opinion using AI, digital traces, and social media, while identifying and mitigating biases against underrepresented groups.

Leah holds degrees in Political Science from LMU and the University of Mannheim, with specializations in quantitative methods, survey research, and political sociology. She is particularly passionate about data justice – giving a voice to those groups surveys and datasets typically overlook or are biased against. To this end, she is investigating the potential and pitfalls of new data sources for learning about public opinion, and has been involved in research projects on privacy attitudes and their implications for stakeholders and policymakers. 

Johanna is a Machine Learning Research Engineer at Pruna AI and a PhD student at TUM supervised by Stephan Günnemann (Data Analytics and Machine Learning Group). Before joining TUM for a Master's degree in computer science, she obtained her Bachelor's degree through a dual study program with IBM, which included research internships in San Francisco and Zurich. Johanna holds the MDSI / Linde PhD fellowship for her PhD research and now works on making AI accessible and sustainable by optimizing ML models for efficient inference.

Isabella is public outreach manager at MDSI. After studying Biotechnology and Molecular Biotechnology at TUM, she received her PhD in Pharmaceutical Biology from LMU. In 2024 she re-joined TUM after several years as public relations manager for a cluster of excellence at TUM/LMU/UA and in companies. 

Iulia Pasov is an Engineering Manager for Data Science at SIXT SE. With a background in software engineering and more than 10 years of experience in working with AI solutions, she focuses on building data driven services meant to optimise car rental processes. Iulia relies on her experience to empower others to reach successful data science or software engineering careers. She is also pursuing a PhD with LMU & Politehnica University of Bucharest.

Wiebke is the Scientific Manager at the Social Data Science and AI Lab (SODA) at LMU, Munich and Research Fellow at the  Research and Expertise Centre for Survey Methodology (RECSM) of Universitat Pompeu Fabra (Barcelona, Spain).

Her research focuses mainly on measurement quality and comparability of survey items. As a survey consultant, she advises on questionnaire design and survey data analyses (with correction for measurement error). Wiebke received her PhD from UPF in 2013, in the areas of political science and survey methodology. Her dissertation dealt with measurement equivalence and the meaning of left-right orientation using data from the ESS.