Master Degree

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Accredited
6 Years
31 Jul 2025
Accreditation DGES
Initial registry R/A-Ef 1081/2011 de 18-03-2011
Update registry R/A-Ef 1081/2011/AL01 de 27-05-2015 | R/A-Ef 1081/2011/AL02 de 02-06-2020 | R/A-Ef 1081/2011/AL03 de 18–03-2025
Contacts
School of Technology and Architecture
Secreatariat
Sedas Nunes Building (Building I), room 1E07
secretariado.ista @iscte.pt
(+351) 210 464 013
9:30 - 18:00
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Lectured in Portuguese
Teaching Type In person

Faculty for (2024/2025)

Business Intelligence Systems Project Management
 Elsa Cardoso is an associate professor at ISCTE - Instituto Universitário de Lisboa (ISCTE-IUL), in the Department of Information Science and Technology of the School of Technology and Architecture, and director of the Master's Degree in Integrated Business Intelligence Systems. She is a researcher at the Information Science, Technology and Architecture Research Center (ISTAR-Iscte) and the Information Systems and Decision Support Group at INESC-ID Lisbon, Portugal. She has a PhD (European Doctorate) in Information Sciences and Technologies from ISCTE-IUL, specializing in Business Intelligence. She is co-coordinator of the data visualization area at the DAViD Lab-Iscte (Advanced Data Digitization and Visualization Laboratory) created in February 2025, in collaboration with the Portuguese Mobility and Transportation Institute (IMT). She is a member of the executive committee of the Artificial Intelligence Competence Center for Public Administration (IA>>AP) of the ISCTE CI-CVTT Association. His research interests include Business Intelligence & Analytics, data visualization, Data Warehouse, and strategic information systems (Balanced Scorecard) applied to Higher Education, Science and Public Administration. She is a member of the Business Intelligence Special Interest Group of EUNIS (European University Information Systems organization). She was the leader of this SIG from 2013 until 2019. Since 2022, she is also a member of the Enterprise Architecture SIG of EUNIS, working on capability maturity models for Higher Education. She has participated in several national and international research projects. She is currently working on the following projects: xSHARE: Expanding the European EHRxF to share and effectively use health data within the EHDS (101136734 - Horizon-HLTH-2023-IND-06) [2023-2026] National Programme for Open Science and Open Research Data (PRR). [2024-2026]   Projects already finalized: Study for the knowledge of fraud in the structural funds in Portugal (POAT-01-6177-FEDER- 000126). Principal Investigator. [2022-2023] Digital Transformation in Research: Science Management and Open Science (POCI-05-5762-FSE-000438). [2021-2023] MAIPro – Project Non-compliance Monitoring and Alert (06/POAT/2021). [2022-2023] IRIS – Summarizing and Informing Decisions: Application of Artificial Intelligence Techniques at the Supreme Court of Justice. Researcher, integrating the INESC ID team. [2021-2022] Healthcare Insight – Units Performance Management (HI-UPM/2014/38567; FEDER-QREN). Principal Investigator from Iscte. [2014-2015] GRADUA – Graduates Advancement and Development of University capacities in Albania (Erasmus+ project No. 585961-EPP-1-2017-1-AL-EPPKA2-CBHE-SP (2017 -2926/001 -001). [2019-2021] iLU – Integrative Learning from Urban Data (DSAIPA/DS/0111/2018). Researcher, integrating the INESC ID team. [2018-2022] IA-Incentivos – Artificial Intelligence in Incentive Management (POCI-05-5762-FSE-000231). [2020-2021] https://ciencia.iscte-iul.pt/authors/elsa-cardoso/cv
Text Mining
Eugénio Ribeiro is an Assistant Professor in the Department of Information Science and Technology (ISTA) at ISCTE - University Institute of Lisbon and a researcher at INESC-ID Lisboa. He obtained his BSc (2010), MSc (2012), and PhD (2023) degrees in Computer Science and Engineering from Instituto Superior Técnico, with his PhD being awarded with distinction and honor. His research interests encompass a broad range of topics in Artificial Intelligence and Machine Learning, with a primary focus on Natural Language Processing. He has contributed to multiple research projects and authored several publications in international journals and scientific events. He has been recognized for his research and teaching skills through best paper awards, top placements in research challenges, and teaching excellence awards. Additionally, he has been actively involved in organizing scientific events, serving as a reviewer, participating in knowledge-transfer projects, supervising students, and providing training in various contexts.
Text Mining
Ricardo Ribeiro is an Associate Professor at Iscte - Instituto Universitário de Lisboa, since 2020, where he is the coordinator of the Artificial Intelligence scientific area and the director of the Master in Computer Engineering (previously, he was the director of the undergraduate program in Computer Engineering), and a researcher at INESC-ID Lisboa since its creation, working on Human Language Technologies. He received a Ph.D. (2011) in Information Systems and Computer Engineering and an M.Sc. (2003) in Electrical and Computer Engineering from Instituto Superior Técnico and an undergraduate five year degree (1996) in Mathematics/Computer Science from Universidade da Beira Interior. From 1999 to 2011, he was a Lecturer at Iscte, where he was an Assistant Professor from 2011 to 2020. Since 1996, he has been a researcher at INESC/INESC-ID Lisboa, Portugal, working in speech and language processing. He has participated in several European and Nationally-funded projects. He was the Human Language Technologies INESC-ID team coordinator in RAGE (2015-2019) European-funded project and the principal investigator of a Ministry of National Defence funded project on information extraction from text. He was also one the coordinators of the technology transfer project IRIS, a contract with the Supreme Court of Justice of Portugal. He has participated in several scientific events, either as organiser or as member of the program committee (IJCAI, ECAI, LREC, Interspeech, ICASSP) and was the editor of a book on the computational processing of Portuguese. He has successfully co-supervised 3 Ph.D. students and more than 70 M.Sc. students.
Data Analysis for Business Intelligence
Contacts
School of Technology and Architecture
Secreatariat
Sedas Nunes Building (Building I), room 1E07
secretariado.ista @iscte.pt
(+351) 210 464 013
9:30 - 18:00
Apply
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