Decision-making processes for infrastructure and construction projects involve a set of steps and tools that allow strategic decisions to be made in the planning phase. This is a complex and uncertain area that involves many distinct technical areas, such as the ability to estimate life-cycle costs (Monteiro et al., 2021), estimate revenues (Cruz and Sarmento, 2019), direct and indirect impacts of projects (Januário et al., 2021; Cruz et al., 2017). The fields of application are also diverse, from the analysis of greenfield projects, that is, construction of new projects whether public infrastructures (for example: water supply system, bridge) or private real estate developments (for example, a new commercial building), but also rehabilitation projects (feasibility analysis).

Objectives of our research: To understand and predict the costs of projects in contexts of uncertainty; to carry out whole life cost analyses that incorporate the intangible benefits; Contribute to improve the decision-making process in engineering projects; use advanced data analytics to improve decision processes.

State of the art: The problem of contracting projects can be summarized in the search for models and contracting options that ensure the achievement of the most valuable proposal, minimizing the risks of non-compliance. At this level, the candidate has developed some research in order to identify what impacts, for example, changes in the public procurement code have on the level of the proper execution of contracts (for example, on the level of compliance with budgets and deadlines) (Catalão, Cruz and Sarmento, 2019a, 2019b). Regarding infrastructure management models, all models and options related to the ownership and responsibility of infrastructure construction and maintenance are considered. These models that, in the past, were essentially based on contract construction and direct asset management, have moved to more complex models, with variable configurations, in which different agents (private and public), can build and manage directly, or delegate this responsibility to third parties (Cruz and Sarmento, 2019). The increasing outsourcing of maintenance activities has created challenges from the point of view of contingency design, in the long term, and in a regime of significant uncertainty. This is a vital research area, not only from the point of view of teaching, but also to ensure research know-how that can be capitalised on in connection with industry. This is not the area with the greatest scientific results of the candidate, but it is probably the one that has attracted the most external visibility (in society).

Objectives of our research: How to improve the contracting processes of engineering works reducing the probability and impact of cost and time deviations? How to increase the efficiency and effectiveness of the contract formation process in engineering projects? What are the main determinants of cost and time deviations? How to make asset management more efficient? How to improve project productivity through digital integration? How to design long-term maintenance contracts and integrated asset management? What steps and tasks can be outsourced through outsourcing? How to extract benefits from the wave of digitalization from the perspective of the built environment?

State of the art: The PPP contracting model is unavoidable in the universe of public infrastructures, for various reasons, whether in developed economies or emerging economies. On a global scale, the use of the model has grown, and so has academic interest. There are several topics of great interest within PPPs, however, it takes particular prominence, the aspects related to risk sharing and contract structuring, public sector comparator and decision process, and, more recently, the renegotiations of contracts, which is perhaps one of the topics where the candidate has the largest number of scientific articles, and is among the dozen world authors with the most relevant contributions. This will also be a very relevant topic to explore a strategy of internationalization of the service delivery component.

Objectives of our research: How to increase the efficiency and effectiveness (value for money) of contracting engineering projects using PPPs? How to improve the performance of long-term contracts in contexts of increasing uncertainty? How to adapt models focused on the construction of new projects to models focused on their maintenance and conservation?

State of the art: This area of research is intended to ensure that, in such a pressing and priority matter, such as rehabilitation, there is know-how that ensures an adequate level of scientific performance in this subject. Thus, although the priority has been the development of master's dissertations, scientific articles have already been produced, one of which was distinguished with the André Jordan Prize in Real Estate Economics. The subject of real estate economics is broad, but of vital importance in the Construction and Civil Engineering sector. This importance has been exacerbated in recent years, due to the economic cycle experienced in this sector. Despite this conjunctural relevance, the candidate is of the opinion that this topic should deserve permanent attention within a research group in Civil Engineering and, in particular, in the area of Construction. Thus, a significant effort has been made to leverage this area, and it has been possible to create, very recently, critical mass at the level of PhD students, which will ensure that in the short-medium term, the scientific outputs will be visible, which is not yet the case at the time of writing this report. Among the various themes that converge in the real estate economy, it is worth mentioning the aspects related to the pricing models that will be described below.

Objectives of our research: What are the challenges, at each moment, of the construction sector in Portugal? How to evaluate rehabilitation projects? What are the risks and externalities involved in rehabilitation projects? What determines the dynamics of the real estate market (in the short, medium and long term)? What is the impact from the perspective of the construction sector? How to develop smarter, automatic, and reliable real estate valuation models?