Giuseppe Alessandro Veltri

Professor of Computational Social Science and Behavioural Science

Behavioural and Implementation Science Interventions (BISI)
Yong Loo Lin School of Medicine, National University of Singapore

Full Professor of Computational Social Science
University of Trento

80+ Publications

10 Books

20+ Grants

3 R Packages

Research Focus

Behavioural Science

Designing and analyzing randomized controlled trials for behavioural interventions and public policy

Computational Social Science

Applying computational methods to understand social phenomena and human behaviour at scale

Research Methods

Experimental design, online experiments, multiverse analysis, and quantitative methods for social science

Recent Publications

Veltri, G. A., & Gilbert, J. (2026). Results from Randomized Controlled Trials are Highly Sensitive to Data Preprocessing Decisions: A Multiverse Analysis of 97 Outcomes. MetaArXiv. Preprint

Veltri, G.A.(2026). Time-Sensitive RCTs in Behavioural Public Policy: A Pragmatic Framework Using Sequence Methods, Personalisation, and Reinforcement Learning. Frontiers in Behavioral Economics. In press. DOI

De Duro, E. S., Franchino, E., Improta, R., Veltri, G. A., & Stella, M. (2025). Cognitive networks identify AI biases on societal issues in Large Language Models. EPJ Data Science. DOI

Veltri, G.A. (2025). The Effects of Data Preprocessing Choices on Behavioral RCT Outcomes: A Multiverse Analysis. Multivariate Behavioral Research. DOI

Veltri, G.A. (2025). From Evidence to Delivery: An Implementation‑Science Blueprint for Behavioural Policy. Behavioural Public Policy. DOI

Andrei, F., & Veltri, G. A. (2025). Signalling strategies and opportunistic behaviour: Insights from dark-net markets. PLOS ONE, 20(3), e0319794. DOI

Banerjee, S., & Veltri, G. A. (2024). Harnessing pluralism in behavioral public policy requires insights from computational social science. Frontiers in Behavioral Economics, 3. DOI

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