AI Engineer with 10+ years in Computational Social Science & Economics
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Highly accomplished computational social scientist with extensive experience in computational social science, behavioral economics, and AI applications. Proven ability to lead research, design digital voting systems, and leverage machine learning for social welfare. Strong background in interdisciplinary research across economics, law, and data science, with a focus on ethical AI and participatory urban planning. Recognized for a robust publication record and strong technical skills in machine learning, NLP, and various programming languages.
University of Cologne
Ph.D. · Economics
August 1, 2017 – June 30, 2020
University of Passau
M.Sc. · Economics
August 1, 2014 – June 30, 2017
University of Augsburg
B.Sc. · Global Business Management
August 1, 2011 – June 30, 2014
University of Konstanz
ASSISTANT PROFESSOR (NON TENURE TRACK)
January 1, 2026 – Present
Switzerland
ETH Zurich
SENIOR SCIENTIST
January 1, 2023 – December 31, 2025
Switzerland
Caltech
POSTDOCTORAL RESEARCHER
January 1, 2022 – December 31, 2023
Switzerland
VU Amsterdam
VISITING RESEARCHER
January 1, 2020 – December 31, 2020
Switzerland
ETH Zurich
POSTDOCTORAL RESEARCHER
January 1, 2020 – December 31, 2022
Switzerland
FU Berlin
VISITING RESEARCHER
January 1, 2019 – December 31, 2019
Switzerland
ETH Zurich
VISITING RESEARCHER
January 1, 2019 – December 31, 2019
Switzerland
Max Planck Institute
PHD STUDENT
January 1, 2017 – December 31, 2020
Switzerland
Stanford University
VISITING RESEARCHER
January 1, 2016 – December 31, 2017
Switzerland
Ifo Institute Munich
RESEARCH ASSISTANT
January 1, 2014 – December 31, 2014
Switzerland
University of Passau
RESEARCH ASSISTANT
January 1, 2014 – December 31, 2015
Switzerland
Identifying Latent Intentions via Inverse Reinforcement Learning in Repeated Linear Public Good Games
Unknown
January 1, 2026 – Present
Comparing Human-Only, AI-Assisted, and AI-Led Teams on Assessing Research Reproducibility in Quantitative Social Science
I4R Discussion Paper Series
January 1, 2025 – Present
Social perception of faces in a vision-language model
ACM Conference on Fairness, Accountability, and Transparency (FAccT)
January 1, 2025 – Present
Beyond the Townhall: Spatial Anchoring and LLM Agents for Scalable Participatory Urban Planning
Unknown
January 1, 2025 – Present
Proportional Multi-Model Selection Increases Social Welfare
Unknown
January 1, 2025 – Present
Designing digital voting systems for citizens: Achieving fairness and legitimacy in participatory budgeting
Digital Government: Research and Practice
January 1, 2024 – Present
LLM voting: Human choices and AI collective decision making
AAAI Conference on AI, Ethics, and Society
January 1, 2024 – Present
Replicating “Run-off elections in the laboratory"
I4R Discussion Paper Series
January 1, 2024 – Present
How voting rules impact legitimacy
Humanities and Social Sciences Communications
January 1, 2024 – Present
Exploring citizen perception of future street scenarios: A virtual reality experiment
Scientific Reports
January 1, 2024 – Present
Early morning hour and evening usage habits increase misinformation spread
Scientific Reports
January 1, 2024 – Present
Social perceptions predict callback rates in North American labor market experiments
PLOS ONE
January 1, 2024 – Present
Color me honest! Time pressure and dis(honest) behavior
Frontiers in Behavioral Economics
January 1, 2024 – Present
Predicting compliance: Leveraging chat data for supervised classification in experimental research
Journal of Behavioral and Experimental Economics
January 1, 2024 – Present
Exploring legitimacy in a municipal budget decision in Switzerland: empirical insights into citizens' perceptions
Philosophical Transactions A 382(2285):20240098. Royal Society
January 1, 2024 – Present
Socio-economic implications of the digital revolution
Handbook of Complexity Economics, Routledge
January 1, 2024 – Present
Democracy by design: Perspectives for digitally assisted, participatory upgrades of society
Journal of Computational Science
January 1, 2023 – Present
The impact of neural synchrony on cooperation in social networks
Frontiers in Physics
January 1, 2023 – Present
Votelab: a modular and adaptive experimentation platform for online collective decision making
Unknown
January 1, 2023 – Present
Participatory resilience: Surviving, recovering, and improving together
Sustainable Cities and Society
January 1, 2022 – Present
Ethics of smart cities: Towards value-sensitive design and co-evolving city life
Sustainability
January 1, 2021 – Present
Text classification of ideological direction in judicial opinions
International Review of Law and Economics
January 1, 2020 – Present
Behavioral economics enhanced: Machine learning and decision making
University of Cologne
January 1, 2020 – Present
Cultural Fit Analysis
The candidate's background is heavily academic, with roles primarily focused on research and teaching at universities and research institutes. While the research topics align with AI ethics, social impact, and collective decision-making, the transition to a corporate AI Engineer role would require adapting to different operational rhythms, team structures, and product development cycles. The diversity of research topics and collaborations across various institutions indicates adaptability and a broad intellectual curiosity, which are positive for cultural fit. However, the lack of industry experience or commercial project involvement might require a period of adjustment.
Soft Skills & Operational Fit
The candidate's academic background and extensive publication record suggest strong analytical thinking, problem-solving, and independent research skills. Experience as a researcher and assistant professor implies good presentation and collaboration skills within academic settings. However, the resume lacks explicit details on project management, team leadership in a corporate environment, or direct experience with agile methodologies, which are common in operational roles.