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SSPM
About Project
Student Success Prediction Model
Acronym
SSPM
Responsible
Luís Miguel Moreira Guardão
Status
Closed
Start
January 4, 2021
End
January 30, 2022
Effective End
January 30, 2022
Global Budget
€57,850.00
Financing
€57,850.00
Members
Team Leaders
Luís Guardão
I’m a Senior Researcher and Project Manager at INESC TEC. I started my work at this institution back in 1992 as a software developer and systems & database administrator. Soon, in 1995, I embraced the project manager role and have since then led a large number of projects in multiple domains (Operations Management, Internal Logistics, Automation, Knowledge Management, Systems Architecture & Integration, Planning & Scheduling, Benchmarking & Business Intelligence) and industries (Shoe, textile, metal tooling, Civil Construction, Chemical, Architecture, Government, Universities).
I hold a Degree in Electronics and Telecommunications by the University of Aveiro and postgraduates degrees in Management (by EGP-UP) and Medical Informatics (by the Faculty of Medicine and Faculty of Sciences of UP).
My current main research area of interest at INESC TEC is Integrated Planning & Scheduling in the context of Industry 4.0.
João Mendes Moreira
Areas of research:
- Knowledge discovery
- Intelligent transportation systems
Associated 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.
Enterprise Systems Engineering
The research carried out at the Centre for Enterprise Systems Engineering (CESE) has a direct impact on industrial transformation, developing sustainable, resilient, and human-centred solutions to address the challenges of the digital and green transitions. Through a co-creation and development approach with scientific and industrial partners, CESE contributes to improve organisational capabilities and driving systemic innovation in complex industrial contexts. As a multidisciplinary research centre, CESE bridges science and practice in the field of Systems Engineering, focusing on value creation within industrial ecosystems. This mission is structured around five research lines that define CESE scientific and technological expertise: Manufacturing Systems Design and Management, Supply Chain and Collaborative Networks Management, Architectures and Industrial Information Systems, Technology Management in Industry, Transportation and Logistics.
