Master Degree

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Accredited
6 Years
31 Jul 2019
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
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 (2023/2024)

Design and Development of Business Intelligence Applications
Patterns and Knowledge Extraction Guided by Data | Data-Driven Decision Making
Design and Development of Business Intelligence Applications | Dissertation in Integrated Decision Support Systems | Business Intelligence Systems Project Management | Data Warehouse Systems I | Data Warehouse Systems II
Elsa Cardoso is an Associate Professor at ISCTE- Instituto Universitário de Lisboa (ISCTE-IUL), in the Information Science and Technologies Department of the School of Technology and Architecture, and the director of the master program in Integrated Business Intelligence Systems. She is a researcher at the Centre for Research and Studies in Sociology (CIES-IUL) and at the Information and Decision Support Systems Group of INESC-ID Lisboa, Portugal. She has a PhD (European Doctorate) in Information Sciences and Technologies from ISCTE-IUL, with a specialization in Business Intelligence. Her research interests include business intelligence and analytics, data visualization, data warehouse, and strategic information systems (Balanced Scorecard) applied to Higher Education and Healthcare. 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
Fernando Batista received his PhD (2011) in Computer Science and Engineering from Instituto Superior Técnico (IST). He is currently Associate Professor at Iscte - University Institute of Lisbon, and integrated researcher at INESC-ID, Lisbon. He is the Executive Coordinator of the Human Language Technologies Scientific Area at INESC-ID (2021-), and member of the Supervisory Board of CVTT - Iscte-Conhecimento e Inovação (since Apr.2021). He was President of the Pedagogical Council of ISCTE-IUL  (2017-2019), member of the Permanent Committee of the Pedagogical Council of ISCTE-IUL (2015-2017), and member of the Pedagogical Committee of the ISTA School (2015-2017). He is the scientific coordinator of the AppRecommender (2019-2021) project, has coordinated the INESC-ID team in the SpeDial project (2014-2015), and participated in several other European and National projects. His current research focuses on spoken and written Natural Language Processing, Machine Learning, and Text Mining for social media. He has been member of the organisation team of the LxMLS - Lisbon Machine Learning Summer School (since 2016), and was also member of the LxMLS technical staff between (2011-2015). He has participated in the organisation of several scientific events: editorial co-chair of PROPOR 2020, editorial chair of EAMT 2020, web chair of the IPMU 2020, co-chair of the Human-Human languages track of SLATE 2019, co-chair of the demos session in PROPOR 2018, publication chair of IberSPEECH 2016, co-chair of the PROPOR 2016 Student Workshop, publication chair of IberSPEECH 2016, co-chair of the PROPOR 2016 Student Workshop, and handbook chair of EMNLP 2015. He is Senior Member of the IEEE (since 2016), and member of the ISCA Speech (since 2008).
Data Analysis for Business Intelligence
Graça Trindade is an Assistant Professor of the Departament of Quantitative Methods for Management and Economics. She got the PhD in Quantitative Methods - Econometrics in 2007 from ISCTE on "Models of Latent Segments of a Market with Aggregate Data". She has published in Journals such as Social Indicators Research Journal, The International Review of Retail, Distribution and Consumer Research (IRRDCR) and the European Journal of Operational Research (EJOR). Her research interests include Mixture models for longitudinal data, Optimization methods, Multivariate data analysis and Statistical Analysis.
Dissertation in Integrated Decision Support Systems | Patterns and Knowledge Extraction Guided by Data | Data-Driven Decision Making
João C. Ferreira is Assistant Professor with habilitation at ISCTE-IUL. He graduated in Physics from the Technical University of Lisbon (UTL / IST), Portugal, received an MSc in Telecommunications and a PhD in Computer Engineering from UTL / IST and a second PhD in Industrial Engineering at the University of Minho. His research interests are in: data science, Text Mining, IoT, Blockchain AI, and AI application to health, energy, transportation, Electric Vehicle, Intelligent Transportation Systems (ITS) and sustainable mobility systems. He has authored more than 250 papers in computer science. He has executed more than 40 projects (6 as PI), more than 200 scientific paper reviews and more than 30 scientific project evaluations. IEEE CIS Chair 2016-2018 and current vice-chair of IEEE Blockchain PT, CIS PT chapter and Bruxels AI and robotics.  Main organizer of international conferences such as: OAIR 2013, INTSYS from 2018 to 2022. IEEE senior member since 2015. Guest Editor and topic editor of MDPI in the topics of energies, electronics and Sensors. President of the IEEE CIS in PT (2017-2018). Author of a patent in the area of Edge Computer in a monitoring system for fishing vessels Coordinator of the Master of Decision Support Systems, Professional Master for the Digitalization of Business and of the summer (smart cities) and winter (IoT Systems and Blockchain) schools. Vice-Chair Computational Intelligence Society and IEEE Blockchain in Portugal and Industry Ambassador in Portugal   He is participating in the following projects - H2020 Infrastress, Sparta, ENSURECEC, EFFECTOR, MARISA, ANDANTE, Interreg Block4Coop, BALCAT, AIM Health, PT2020 Monitoring persistent track and Multicam and the Digital Demo, EEagrants Fish2fork (PI) and Social IoT (PI)
Patterns and Knowledge Extraction Guided by Data | Data-Driven Decision Making
Luís Manuel Nobre de Brito Elvas, with a degree in Computer Engineering and a Master's degree in Integrated Decision Support Systems, is a researcher at the Technologies and Architecture Research Center (ISTAR) and at the Association for Research and Development of the Faculty of Medicine of the University of Lisbon (AIDFM).In the context of health informatics, he has worked on data mining techniques, computer vision and artificial intelligence, to extract data patterns, perform image classification and text reports, respectively. In 2022 his work was distinguished by the Portuguese Order of Engineers. He is also Chair of IEEE Computational Intelligence Society Student Branch Chapter at iscte.
Text Mining
Ricardo Ribeiro (PhD) is an Associate Professor at Iscte - Instituto Universitário de Lisboa, where he is the coordinator of the Artificial Intelligence scientific area, and an integrated researcher at INESC-ID Lisboa, working on Human Language Technologies. His current research interests focus on high-level information extraction from unrestricted text, speech or music, and improving machine-learning techniques using domain-related information. He has participated in several European and Nationally-funded projects and 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 has participated in several scientific events, either as organiser or as member of the program committee (IJCAI, ICASSP, LREC, Interspeech) and was the editor of a book on the computational processing of Portuguese.
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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