Prof. Giuseppe A. Veltri
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Prof. Giuseppe Alessandro Veltri
Giuseppe Alessandro Veltri

Professor of Computational Social Science and Behavioural Science

Department of Sociology and Social Research
University of Trento

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

90+ Publications
11 Books
20+ Grants
3 R Packages
University of Trento National University of Singapore

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

Featured Article

This Month's Choice

Time-Sensitive RCTs in Behavioural Public Policy: A Pragmatic Framework Using Sequence Methods, Personalisation, and Reinforcement Learning

Veltri, G.A. (2026)

Frontiers in Behavioral Economics

This article proposes a pragmatic framework for analysing behavioural RCTs through sequence methods and Markov modelling, capturing how interventions unfold over time. Rather than relying on average outcomes alone, the approach tracks individual transitions between behavioural states, producing decision-oriented outputs such as transition probabilities, expected persistence durations, and trajectory clusters. The framework extends to personalised interventions and reinforcement learning, and is operationalised through sequenceRCT, an open R package. Applications include booster scheduling, resource triage, and programme exit criteria for behavioural policy.

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Recent Publications

Veltri, G. A. (2026). Navigating evidence, legitimacy and delivery: A three-dimensional framework for behavioural policy design. Policy and Society. In press.

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. (2026). 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

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© 2023-2026 Giuseppe A. Veltri

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Last updated: March 2026