My research focuses on the intersection of environmental and energy policy, economics, technology and society. I am interested in viable and beneficial transformations of energy systems, and how these are affected by emerging technologies, policy development and human behavior. By combining engineering, data science and social science methods, I aspire to develop interdisciplinary scientific tools to effectively guide energy, environmental, and technology policy towards a cost-effective and beneficial energy future for all. Examples of methods I uses include, but are not limited to, artificial intelligence simulation models (machine learning and fuzzy logic), energy systems modeling, econometrics, behavioral experiments and surveys.
My work can be best described on the basis of the following themes:
*Theme 1: Viable and beneficial energy innovations for all. The research objectives within this theme include i) deciphering the social, economic and environmental effects of energy innovation policies with a particular focus on working class households and communities, and ii) identifying optimal policy designs for accelerating innovation while securing energy system affordability and reliability.
*Theme 2: Energy behaviors and technology adoption. With this theme, I aim to understand how individual and collective behaviors concerning investment in new technology and demand side management are shaped within specific policy and technology contexts. Furthermore, I explore public acceptance of energy innovations and designs for behavioral change interventions based on information, peer influence and incentives.
*Theme 3: Interdisciplinary models of socio-technical energy systems. While the previous two themes focus on understanding the behavioral, economic and environmental aspects of energy innovation policies, this third theme concerns innovative methods to integrate these findings into quantitative models of socio-technical energy systems. The target is to develop interdisciplinary policy-informing models that go beyond the state-of-the-art and take into account consumer behavior heterogeneity in energy-relevant contexts. This will enable more realistic projections of energy innovations' viability, pace, and effectiveness.
