INESC TEC
INESC TEC
INESC TEC
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MDIGIREC

INESC TEC

About Project

Context Recommendation in Digital Marketing

Acronym

MDIGIREC

Responsible

Rui Diogo da Costa Gama Lima Rebelo

Status

Closed

Start

January 1, 2017

End

January 30, 2018

Effective End

January 30, 2018

Global Budget

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Financing

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Website

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Members

Team Leaders
Rui Diogo Rebelo
Rui Diogo Rebelo

Rui Rebelo has a degree in Electrical and Computer Engineering from the Faculty Lusíada, Famalicão (1994). His research interests include balancing, scheduling and development of new production systems.

His work comprehends different cases from development of decision support tools to industrial robotics. Since May 1995 until now he is a Senior Researcher in the Manufacturing Systems Engineering Unit (UESP) of INESC-Porto, Project Leader, actively participating in the institutions’ Research and Development (R&D) activities. He has participated in several R&D projects, including: “CEC-made-shoe: Custom, Environment and Comfort made shoe”, “EUROShoE – extended user oriented shoe enterprise“, “CICLOP - Computerised and integrated closing operations”, “FIT4U - Framework of Integrated Technologies for User Centred Products (2 European patents) 

Alípio Jorge
Alípio Jorge

I am an associate professor at the Department of Computer Science of the Faculty of Science of the University of Porto and the coordinator of LIAAD , the Artificial Intelligence and Decision Support Lab of UP. LIAAD is a unit of INESC TEC (Laboratório Associado) since 2007. I am a PhD in Computer Science by U. Porto, MSc. on Foundations of Advanced Information Technology by the Imperial Collegeand BSc. in Applied Maths and Computer Science, currently Computer Science (U. Porto). My research interests are Data Mining and Machine Learning, in particular association rules, web and text intelligence and data mining for decision support. My past research also includes Inductive Logic Programming and Collaborative Data Mining. I lecture courses related to programming, information processing, data mining, and other areas of computing. While at the Faculty of Economics, where I stayed from 1996 to 2009, I launched, with other colleagues, the MSc. on Data Analysis and Decisison Support Systems, which I coordinated from 2000 to April 2008. I lead research projects on data mining and web intelligence. I was the director of the Masters in Computer Science at DCC-FCUP from June 2010 to August 2013. I co-chaired international conferences (ECML/PKD 2015, Discovery Science 2009, ECML/PKDD 05 and EPIA 01), workshops and seminars in data mining and artificial intelligence. I was Vice-President of APPIA the Portuguese Association for Artificial Intelligence.

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.

Artificial Intelligence and Decision Support

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.

Enterprise Systems Engineering