
About Project
Randtech Update and Test Environment
Acronym
RUTE
Responsible
Alípio Mário Guedes Jorge
Status
Closed
Start
January 1, 2018
End
January 13, 2020
Effective End
January 13, 2020
Global Budget
€105,250.00
Financing
€105,251.00
Members
Team Leaders

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.
Ana Cristina Paiva
Ana Paiva (publishes as Ana C. R. Paiva). Ana Paiva is Assistant Professor at the Informatics Engineering Department of the Faculty of Engineering of University of Porto (FEUP) where she works since 1999. She is a researcher at INESC TEC in the Software Engineering area and member of the Software Engineering research group which gathers researchers and post graduate students with common interests in software engineering. She teaches subjects like Software Testing, Formal Methods and Software Engineering, among others. She has a PhD in Electrical and Computer Engineering from FEUP with a thesis titled"Automated Specification Based Testing of Graphical User Interfaces". Her expertise is on the implementation and automation of the model based testing process. She has been developing research work in collaboration with Foundation of Software Engineering research group within Microsoft Research where she had the opportunity to extend Microsoft's model-based testing tool, Spec Explorer, for GUI testing. She is PI of a National Science Foundation funded project on Pattern-Based GUI Testing (PBGT). She is a member of the PSTQB (Portuguese Software Testing Qualification Board) board general assembly, member of TBok, Glossary, and the MBT Examination Working Groups of the ISTQB (International Software Testing Qualification Board), member of the Council of the Department of Informatics Engineering, and member of the Executive Committee of the Department of Informatics Engineering.
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.

Human-Centered Computing and Information Science
The Centre for Human-Centered Computing and Information Science (HumanISE) brings together engineers, scientists, and designers with expertise in Human-Centred Computing (HCC), Computer Science (CS), and Information Science (IS). Interdisciplinarity, one of the Centre’s defining features, fosters the development of software systems, methods, and tools designed to empower individuals and their communities. The excellence and impact of HumanISE’s research, innovation, and consultancy activities allow addressing increasingly complex, volatile, heterogeneous, ambiguous, and uncertain challenges, while ensuring compliance with legal, ethical, and organisational standards and frameworks. Value transfer is achieved through close collaboration with academia and industry partners. HumanISE’s core research areas include Human-Computer Interaction; Computer Graphics and Interactive Digital Media; Information Management and Information Systems; Software Engineering; and Large-Scale and Special-Purpose Computing Systems, Languages, and Tools; as well as Computing for Embedded and Cyber-Physical Systems. HumanISE also explores innovation domains like Earth, Ocean and Space Sciences; Personalised Health Research; Geospatial Information Systems Engineering; and Applied Information Systems and Computing.
