Place: Lecture hall T4, The Computer Science Building, Aalto University
Date: April 2, 2026
Format: 20 min talk + 10 min Q&A
Organizers: Tomomi Kito, Graduate School of Creative Science and Engineering, Waseda University; Petter Holme, Department of Computer Science, Aalto University.
Program
13:00–13:45
Omar Guerrero, University of Helsinki
Modeling sustainable development from the bottom up
The explicit acknowledgement of the complexity of the Sustainable Development Goals (SDGs) is one of the main innovations of this international agenda. However, the formal analysis of complex systems in the SDG literature remains scant, as most of the focus is given to (top-down) aggregate models such as systems dynamics and networks of indicators. In this talk, I will argue that an adequate treatment of complexity requires viewing development as a bottom-up process, with macro-level outcomes emerging from micro-level interventions. From a quantitative point of view, popular methodologies such as statistical analysis and machine learning are inadequate to address this vertical causation, as the available data are aggregate and coarse-grained (typically annual development indicators). To resolve this, models with explicit agent-level causal mechanisms are needed, and agent computing is the right tool to create them. I will present the research program of Policy Priority Inference (oguerr.com/ppi), which employs agent computing to model the SDGs from the perspective of public expenditure interventions. I will discuss several applications related to policy coherence, policy resilience, feasibility, fiscal federalism, accelerators, and bottlenecks, as well as the country case studies in which they have been applied. This programme provides a fresh perspective on the challenges of multidimensional development and a rigorous approach to exploiting not only indicators but also new sources, such as open spending data.
14:00–14:45
Juhi Kulshrestha, Aalto University
Decoding our Internet-mediated lives: Behaviour, attitudes, and wellbeing
Much of our everyday life now unfolds online, from the information we consume to the opinions we form and the decisions we make, leaving behind rich digital traces of human behaviour. In this talk, I will discuss how digital behavioural data can be used to study our internet-mediated lives. By combining passive web browsing traces with online surveys, experiments, and computational analysis of web content, we can link patterns of online behaviour to attitudes, decisions, and mental health & wellbeing. These approaches offer new ways to understand how digital environments shape behaviour and experiences both online and offline.
Petter Holme 