Catarina Delgado

Domains

Artificial Intelligence and Decision Support

Projects

FAST-manufacturing

This project focus is on manufacturing flexibility and sustainability. The former is researched by optimizing scheduling operations in flexible manufacturing systems through the cumulative integration of the several sub-problems faced in manufacturing flexible systems. Sustainability is promoted via optimizing resource consumption and pollutant emissions along with the usual efficiency measures (makespan, tardiness, workload, etc.) for production operations scheduling problems. Regarding the emissions, it also accounts for the possibility of buying and/or selling pollution permits. Mathematical programming models are proposed, as well solutions methods to solve them. In addition, and due to the NP-hardness nature of the problems under consideration, solution approaches based on evolutionary algorithms that are capable of finding good solutions in a reasonable are also proposed. Project datasheet

HALM

Publications

Brand Love, Attitude, and Environmental Cause Knowledge: Sustainable Blue Jeans Consumer Behavior

Magano J.;Brandão T.;Delgado C.;Vale V.;

2024

Sustainability (Switzerland)

Intention to purchase sustainable fashion: Influencer and worth-of- mouth determinants

Moráis, CF;Pires, PB;Delgado, C;Santos, JD;

2023

Social Media and Online Consumer Decision Making in the Fashion Industry

Green Cosmetics: Determinants of Purchase Intention

Rodrigues, AC;Pires, PB;Delgado, C;Santos, JD;

2023

Handbook of Research on Achieving Sustainable Development Goals With Sustainable Marketing

Intra-hospital virtual communities and wellbeing of cancer patients: Impact of features on healthcare relationships

Silva, RJ;Pires, PB;Delgado, C;Santos, JD;

2023

Effective Digital Marketing for Improving Society Behavior Toward DEI and SDGs

View all publications

Supervised theses

Detection of Driver Fatigue and Distraction Using Mobile Device Sensors and AI

Gonçalo Fernandes Diogo de Almeida

M - 2024

UP-FEUP

Centres

Artificial Intelligence and Decision Support

Our Laboratory of Artificial Intelligence and Decision Support (LIAAD) conducts research in the fields of Artificial Intelligence, Machine Learning, Data Science, and Modelling. These areas are cross-cutting and apply to all sectors of society and the economy. The vast amounts of data being collected, alongside the ubiquity of digitalisation and sensorisation, are increasingly creating opportunities and challenges for automating decision support. The combination of Machine Learning and complex models is transforming the economy, healthcare, justice, industry, science, public administration, and education. This encourages us to invest in diverse technological and scientific approaches and perspectives. Our overarching strategy is to explore the flow and diversification of data, and to invest in research lines that will lead to the development of applied Artificial Intelligence foundations and models that are responsible and human centred.