J.M. Oliveira dos Santos PhD (Joao)

Assistant Professor

About Me

Born in 1988, João Santos is an Assistant Professor at the department of Construction Management and Engineering at the Faculty of Engineering Technology at the University of Twente (UT) since 2018.

In 2016, João Santos completed the doctoral program in Transportation Systems provided by the Faculty of Science and Technology of the University of Coimbra (FCTUC), the Technical University of Lisbon (UTL), and the Faculty of Engineering of University of OPorto (FEUP), Portugal. During his graduate studies in Transportation Systems at the FCTUC, he spent a year and a half as visiting scholar at the Centre for Sustainable Transportation Infrastructure (CSTI), at the Virginia Tech Transportation Institute (VTTI), USA.

Prior to his position at the UT, he was a recipient of a Marie Skłodowska-Curie Post-Doctoral Fellowship working on an EU Framework 7 funded project SUPR&R ITN (www.superitn.eu), at IFSTTAR in Nantes.

He conducts research at the interface of civil engineering, operation research and environmental technology. His work develops assessment methodologies, frameworks and operation search methods, such as optimization algorithms, to handle from a data-driven and optimized-based perspective the commonly existing trade-off relationships underlying to the application of sustainability, resilience and circularity principles, when planning, designing, maintaining and operating infrastructures, transportation systems and cities.


João Santos' research work emphasizes the development and application of advanced computational models, optimization algorithms, statistical machine learning methods, systems analysis tools and industrial ecology methods to tackle multiple and varied real-world problems and global challenges faced by today’s infrastructures, transportation systems and cities in order to promote a more sustainable future.

He is also interested in (1) investigating the impacts of climate change on pavement and urban transport systems and (2) combining machine learning and statistical models to create predictive models intended to improve the knowledge of physical and mechanical properties, characteristics and processes influencing the infrastructure and transportation systems condition and the urban environment, based on the combination of data collected in the field, existing databases and novel sensing platforms. He is particularly thrilled by the prospect of integrating modern systems models with real-world data sources in research that requires carefully applied state-of-the-art operation research and industrial ecology methods along with new theoretical insights.

The common thread that ties his research together is the concept of enhancing the frameworks, platforms and tools that decision-makers use to design and manage their systems. Whether this entails advancing the state of knowledge about (1) the impact of infrastructure, transportation systems and cities on the natural environment and (2) operation research methods or solving applied research questions regarding the enhancement of their management, the outcome is a more informed decision process that decision-makers can use to help promoting a transition towards a more sustainable future. This requires implementing new models and data to solve complex problems related to social, environmental, and economic aspects of engineered systems and make environmentally benign, cost-effective, and socially acceptable policies, all of which drive his long-term research interests.


Rincón, C. A. R. , Santos, J. , Volker, L., & Rouwenhorst, R. (2021). Identifying Institutional Barriers and Enablers for Sustainable Urban Planning from a Municipal Perspective. Sustainability (Switzerland), 13(20), [11231]. https://doi.org/10.3390/su132011231
Amarh, E. A., Flintsch, G. W. , Santos, J., & Diefenderfer, B. K. (2021). Development of Roughness Prediction Models for Life Cycle Assessment Studies of Recycled Pavement Projects. Transportation research record, 2675(12), 449-463. https://doi.org/10.1177/03611981211029928
Oliveira dos Santos, J. M., Pham, A., Stasinopoulos, P., & Giustozzi, F. (2021). Recycling waste plastics in roads: A life-cycle assessment study using primary data. Science of the total environment, 751, [141842]. https://doi.org/10.1016/j.scitotenv.2020.141842
Oliveira dos Santos, J. M., Torres-Machi, C., Morillas, S., & Cerezo, V. (2020). Multiple objective optimization of sustainable pavement maintenance and rehabilitation strategies: a clustering procedure for selecting preferred Pareto optimal solutions. In T. Lusikka (Ed.), TRA2020 Helsinki: Transport Research Arena
Guo, Y., Chen, N., Ni, G., Wang, L., Qiao, Y., Stoner, A. , & Oliveira dos Santos, J. M. (2020). A life cycle costs analysis of the economic impacts of future climate change on flexible pavement performance. In A. Chen, F. Biondini, & M. Sarkisian (Eds.), IALCCE 2020: The seventh international symposium on life-cycle civil engineering
Qiao, Y., Liu, S., Wang, Z., Liu, Y., Li, W., Geng, D., Feng, Y. , Oliveira dos Santos, J. M., & Parry, T. (2020). Comparing environmental impacts of reclaimed asphalt pavement and hot mix asphalt pavement using life cycle assessment. In A. Chen, F. Biondini, & M. Sarkisian (Eds.), IALCCE 2020: the seventh international symposium on life-cycle civil engineering
Pena Acosta, M. , Vahdatikhaki, F. , Santos, J. , & Dorée, A. G. (2020). A conceptual framework for more efficient simulation of the interplay between road pavements and the Urban Heat Island phenomenon. In L-C. Ungureanu, & T. Hartmann (Eds.), EG-ICE 2020 Workshop on Intelligent Computing in Engineering: 1st–4th July 2020, Online, Proceedings (pp. 264-274). Berlin University Press.
van Eldik, M. A. , Santos, J. , Vahdatikhaki, F., Visser, M. , & Dorée, A. (2020). BIM-based life cycle assessment framework for infrastructure design. In L-C. Ungureanu, & T. Hartmann (Eds.), EG-ICE 2020 Workshop on Intelligent Computing in Engineering, Proceedings (pp. 254-263). Berlin University Press.
van Eldik, M. A. , Vahdatikhaki, F. , dos Santos, J. M. O., Visser, M. , & Doree, A. (2020). BIM-based environmental impact assessment for infrastructure design projects. Automation in construction, 120, [103379]. https://doi.org/10.1016/j.autcon.2020.103379
Vega A, D. L. , Santos, J., & Martinez-Arguelles, G. (2020). Life cycle assessment of hot mix asphalt with recycled concrete aggregates for road pavements construction. International journal of pavement engineering. https://doi.org/10.1080/10298436.2020.1778694
Santos, J., Bressi, S., Cerezo, V., & Lo Presti, D. (2019). SUP&R DSS: A sustainability-based decision support system for road pavements. Journal of cleaner production, 206, 524-540. https://doi.org/10.1016/j.jclepro.2018.08.308
Castro, A., Martínez, G., Fuentes, L., Bonicelli, A., Preciado, J. , & Santos, J. (2019). Environmental and mechanical benefits of cold recycled bituminous mixes with crumb rubber. In M. Crispino (Ed.), Pavement and Asset Managemen: Proceedings of the World Conference on Pavement and Asset Management (WCPAM 2017), June 12-16, 2017, Baveno, Italy Routledge Tailor & Francis Group. https://doi.org/10.1201/9780429264702-57
Santos, J., Ferreira, A., & Flintsch, G. (2019). An adaptive hybrid genetic algorithm for pavement management. International journal of pavement engineering, 20(3), 266-286. https://doi.org/10.1080/10298436.2017.1293260
Santos, J., Cerezo, V., Flintsch, G., & Ferreira, A. (2019). A many-objective optimization model for sustainable pavement management considering several sustainability metrics through a multi-dimensionality reduction approach. In R. Caspeele, L. Taerwe, & D. M. Frangopol (Eds.), Life-Cycle Analysis and Assessment in Civil Engineering: Towards an Integrated Vision: Proceedings of the 6th International Symposium on Life-Cycle Civil Engineering, IALCCE 2018 CRC Press. https://doi.org/10.1201/9781315228914
Vega, D. L., Gilberto, M. A. , & Dos Santos, J. (2019). Life Cycle Assessment of Warm Mix Asphalt with Recycled Concrete Aggregate. IOP Conference Series: Materials Science and Engineering, 603(5), [052016]. https://doi.org/10.1088/1757-899X/603/5/052016

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Contact Details

Visiting Address

University of Twente
Faculty of Engineering Technology
Horst Complex (building no. 20)
De Horst 2
7522LW  Enschede
The Netherlands

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Mailing Address

University of Twente
Faculty of Engineering Technology
Horst Complex
P.O. Box 217
7500 AE Enschede
The Netherlands