Rodrigo Miragaia Rodrigues is a full professor at the Instituto Superior Técnico (ULisboa) and a researcher at INESC-ID since 2015. He previously held roles as an associate professor at Universidade Nova de Lisboa, tenure-track faculty at MPI-SWS, and completed his PhD at MIT in 2005 under Barbara Liskov. Education: PhD in Computer Science, MIT, 2005 Research Interests: Focuses on distributed systems, fault-tolerant computing, cloud infrastructure, and consistency models. His work bridges theoretical foundations and practical implementations, addressing challenges in geo-replication, secure analytics, and resource allocation in serverless environments. He emphasizes scalable systems and resilient data management. Awards: Best Paper Award at SOSP ERC Starting Grant Google Faculty Research Award Advising & Grants: Has advised 7 PhD students as main advisor, with graduates in top institutions like Purdue, TU Munich, and USTC. Secured funding from the European Research Council (ERC) and Google, focusing on projects like DependableCloud (ERC Grant 307732). Labs & Teams: Leads research at INESC-ID and previously directed the Dependable Systems Group at MPI-SWS. Active in academic leadership roles, including President of the Scientific Council at IST.
Francisco Almeida Maia is a Senior Researcher at HASLab (High Assurance Lab) affiliated with the University of Minho and INESC TEC. His research focuses on distributed systems, cloud computing, large-scale data management, and gossip-based protocols. He holds a Ph.D. in Computer Science from the MAP-i Doctoral Program (Universities of Minho, Aveiro, and Porto, 2015), advised by Professor Rui Oliveira. His doctoral work introduced DataFlasks, a scalable and resilient data store for large-scale systems using gossip protocols. Current research explores enhancing DataFlasks’ guarantees while maintaining scalability. Education: Ph.D. in Computer Science, MAP-i Doctoral Program (2015) Research Interests: Distributed systems security, privacy-aware cloud storage, scalable data architectures, and fault-tolerant protocols. Recent work emphasizes secure multi-cloud databases and distributed system testing frameworks. Publications: Focus on scalable systems, privacy in distributed environments, and testing methodologies. Notable contributions include d'Artagnan (secure NoSQL on untrusted clouds) and Minha (large-scale distributed testing). Advising & Grants: Supervised two theses at INESC TEC. Active in collaborative projects on distributed systems and security. Labs/Teams: Core member of HASLab, contributing to interdisciplinary research on high-assurance software and distributed computing.
Luis Antunes Veiga is an Associate Professor and Senior Researcher at INESC-ID Lisbon, affiliated with the Distributed Systems Group and the Computing Systems and Communication Networks Laboratory. His research focuses on Cloud Computing, Edge Computing, Distributed Systems, and Big Data processing. He teaches courses such as 'Cloud Computing and Virtualization' and 'Operating Systems, Virtualization and Cloud Computing.' His work emphasizes scalable systems, network-aware workflows, and resource-efficient data processing. Research Interests: His primary areas include distributed systems architectures, edge computing frameworks, graph processing algorithms, and software-defined systems. He explores topics like latency-aware network design, resource auction mechanisms for edge environments, and interoperable service workflows. His contributions span theoretical frameworks and practical implementations, such as the RATEE system for edge resource trading and the VeilGraph incremental graph processing framework. Publications: His recent work addresses challenges in distributed systems, such as elastic scaling of stream processing, efficient graph processing in Spark, and latency optimization in internet-scale workflows. These publications reflect a trend toward integrating software-defined approaches with edge and cloud infrastructures. Notable Awards: Best Young Researcher INESC-ID, Excellence in Teaching (IST 2012), and a Best-Paper Award at ACM/IFIP/Usenix Middleware 2007. Labs & Teams: Active in the Computing Systems and Communication Networks Laboratory, leading projects on edge computing and distributed systems.
David R. Matos is an Assistant Professor at the College of Engineering, University of Lisbon, and a researcher at the Distributed, Parallel and Secure Systems Group (DPSS) of INESC-ID. He is also a member of the BIG ERA Chair Team. His primary research interests include distributed systems, cybersecurity, and cloud computing, with a specific focus on intrusion recovery mechanisms for cloud environments and microservice architectures. Education: BSc in Informatics Engineering, University of Lisbon MSc in Informatics Engineering, University of Lisbon PhD in Computer Sciences and Engineering, Instituto Superior Técnico His research applies machine learning techniques to associate application requests with database statements, enabling identification and reversal of malicious operations. Key themes include decentralized storage, blockchain recovery, secure communication protocols, and pluggable intrusion recovery systems. David has contributed to projects such as PATI, SITAN, SafeCloud, SEAL, and the BIG ERA Chair. He developed the Rectify system for intrusion recovery in PaaS clouds, which is deployable alongside applications without software modifications.
Ana Maria Neves de Almeida Baptista Figueiredo is a Coordinator Professor and academic leader at the Institute of Engineering of Polytechnic of Porto (ISEP/IPP). She currently serves as President of the ISEP Scientific Council (since 2018), Sub-Director of post-graduation programmes in Big Data & Decision Making and Industry 4.0, and holds numerous leadership roles in accreditation processes including A3ES, EUR-ACE, and ABET. She is a Senior Researcher at GECAD (Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development) and member of LASI (Associated Laboratory of Intelligent Systems). Education: PhD in Industrial and Systems Engineering (2003) from University of Minho MSc in Electronic and Computer Engineering - Specialization in Industrial Informatics (1996) from University of Porto BSc in Industrial Informatics (1993) from Polytechnic Institute of Oporto - Institute of Engineering BSc in Electronic Engineering (1990) from Polytechnic Institute of Oporto - Institute of Engineering Professor Figueiredo specializes in Ambient Intelligence, Decision Support Systems, and Intelligent Systems with applications spanning multiple domains. Her research combines artificial intelligence, big data analytics, and user-centered design to develop innovative solutions. She has particular expertise in creating personalized systems that adapt to user needs and contexts, with strong emphasis on practical applications in real-world settings. Her publication record reveals consistent research activity across three main application domains: tourism technology (personalized recommendation systems, smart travel planning), Industry 4.0 (intelligent manufacturing, production scheduling), and healthcare (respiratory monitoring, medical diagnostics). The research demonstrates a clear trajectory from foundational work in scheduling algorithms to increasingly sophisticated intelligent systems incorporating machine learning, sensor networks, and emotional computing. Awards and Recognition: 2017 Award of merit for scientific publication in TELEMATICA AND INFORMATICS journal 2017 Prémio SPAIC – AstraZeneca for FRASIS respiratory monitoring project 2013 PIPED honorable mention for Android e-learning platform 2012 1st place in POLIEMPREENDE entrepreneurship competition with NearTour project 1995 Best student award in Industrial Informatics Engineering Professor Figueiredo has supervised 3 completed PhD theses with 1 ongoing, and more than thirty MSc dissertations. She has participated as Principal or Co-Principal Investigator in 6 projects and as Researcher in more than 20 projects, securing funding from FCT and other agencies. Her work has been supported by significant grants including TheRoute, GROUPLANNER, Smartravel, ATT, InVALUE, INVALUE_PT, NIS, PIANISM, Cyberfactory, SECOIIA, and produtech_R3. She leads research activities within GECAD and LASI, collaborating with international teams from Spain, Canada, USA, Czech Republic, Turkey, and Italy. Her work bridges academic research with practical applications through partnerships with business organizations, public entities, and professional associations across multiple sectors.
Amílcar Moreira serves as an Assistant Professor at the Lisbon School of Economics & Management (ISEG), University of Lisbon, where he teaches quantitative methods and sociology. He concurrently holds research roles as a Board Member of SOCIUS (Research Centre in Economic and Organizational Sociology) and contributor to EUROMOD-Portugal. Previously, he held academic appointments at Trinity College Dublin and OsloMet. His educational background includes a PhD in Social and Policy Sciences (specializing in Social Policy) from the University of Bath (2006), a Master in Economic Sociology from ISEG (2000), and a BA in Social Sciences from Universidade da Beira Interior (1998). Moreira's research centers on comparative social policy frameworks, demographic ageing impacts on pension systems, welfare-to-work policy design, and microsimulation modeling. His work examines political economy dynamics in social policy development, with particular focus on Southern European welfare states. Recent investigations analyze crisis responses to the Great Recession, COVID-19 pandemic, and inflationary pressures through rigorous policy evaluation frameworks. His publication record demonstrates consistent engagement with evolving social policy challenges, particularly the inflation-social policy nexus, gendered pension disparities, and cross-national care responsibility impacts. Methodologically, he specializes in dynamic microsimulation techniques through the EUROMOD platform to model policy effects on income distribution and poverty. Moreira actively supervises Master's students at ISEG, guiding research on topics including robot taxation impacts, public sector employee wellbeing, gendered work-life balance, multicultural leadership, and child poverty interventions. He contributes to SOCIUS research initiatives and EUROMOD-Portugal's national policy analysis, supporting evidence-based social security reforms through advanced modeling of demographic and economic trends.
Paulo Carreira is an Associate Professor at Instituto Superior Técnico , Universidade de Lisboa. His research focuses on Building Automation , Energy Management , and Data Integration , with a particular emphasis on Smart Urban Environments and Cyber-Physical Systems . Fields: Building Automation, Energy Management, Data Privacy, Query Optimization, ETL, Streaming Query Processing Research Trends : His recent work spans from SQL Injection Attacks in LLM-integrated systems to Multi-Paradigm Modeling for Cyber-Physical Systems. Publications highlight his expertise in Energy Efficiency in buildings and BIM Integration with real-time data. Scientific Awards : Best Student Paper Award Nomination for Best Paper Award
Maribel Yasmina Campos Alves Santos serves as a Full Professor in Information Systems in Organisations and Society at the Department of Information Systems, School of Engineering, University of Minho, Portugal. She is a Senior Researcher at the ALGORITMI Research Centre and the CCG/ZGDV ICT Innovation Institute, where she leads the data engineering and analytics group. Previously, she led the Software-based Information Systems Engineering and Management Group (2017-2022) and currently coordinates the 'Organisational and Analytical Data-intensive Systems' research track since 2009. Her research focuses on Business Intelligence and Analytics, with particular emphasis on Big Data Analytics including data architectures, processing, analysis, and visualization. She contributes to international classifications through the Association for Information Systems (AIS) Topics in Decision Support and Analytics, Geographic Information Systems, and Big Data Application Processes, as well as IFIP Technical Committee on Information Systems. Dr. Santos has held significant administrative roles including Vice-Dean of the School of Engineering (2019-2022), Dean of the Pedagogical Council (2019-2022), and Associate Director of the Department of Information Systems (2010-2014). Since February 2024, she has served as Director of the Doctoral Program in Information Systems and Technologies. She was actively involved with AGILE as Secretary-General (2013-2015) and remains a member of the Association of Information Systems (AIS). Her recent publication portfolio demonstrates strong focus on emerging technologies, with 15 most recent works spanning large language models for conceptual modeling, storytelling dashboards for Industry 4.0, data mesh adoption, and model-to-model transformations. These publications reveal consistent themes in data architecture innovation, visualization techniques, and the integration of AI in information systems. Associate Editor, Business & Information Systems Engineering Journal (Q1, since January 2022) Scientific/Program/Organizing Committee member for over 140 international conferences Co-inventor of two patents (one national, one international) Dr. Santos has supervised 7 PhDs, 60 MSc, and 2 post-doc students, and currently mentors 4 PhD students, 4 MSc students, and 1 post-doc. She has supervised over 45 research grants and participated in more than 30 funded research projects. Her leadership extends to coordinating the Doctoral Program in Information Systems and Technologies and contributing to European research initiatives including a Marie Skłodowska-Curie Actions Joint Doctorate Program in Geoinformatics.
Orlando Manuel Oliveira Belo is an Associate Professor with Habilitation at the School of Engineering, University of Minho, Portugal, where he has been a member of the Department of Informatics since 1986. He is also a Senior Researcher at the ALGORITMI R&D Centre, and a member of both the CST R&D Group and ISLab R&D Lab. His academic career spans over three decades, with significant contributions to the fields of Business Intelligence, Data Warehousing, and Data Mining. His educational background includes: 5-year degree in Systems and Informatics Engineering (1986) "Provas de Aptidão Pedagógica e Capacidade Científica" (MSc equivalent) in Expert Systems (1991) Ph.D. in Multi-Agent Systems (1998) Habilitation (2013) Professor Belo's research primarily focuses on Business Intelligence and related areas including Data Warehousing Systems, OLAP, Dashboarding, and Data Mining. His work has significant practical applications in fraud detection and control in telecommunication systems, data quality evaluation, and ETL systems for industrial data warehousing. In recent years, his research has expanded into Ontology Learning and Sentiment Analysis, with applications in healthcare analytics, particularly in cardiovascular health monitoring and dermatology. His interdisciplinary approach bridges computer science with practical business and healthcare applications, demonstrating the versatility of data analytics across different domains. His recent publications (2023-2025) show a clear trend toward integrating advanced machine learning techniques with domain-specific knowledge, particularly in healthcare applications. He has published extensively on sentiment analysis, ontologies, and data warehousing, with a growing emphasis on medical applications including atopic dermatitis and cardiovascular health. His work demonstrates a progression from foundational data warehousing and ETL research to more specialized applications in precision medicine and well-being analytics, reflecting the evolving landscape of data science applications. Professor Belo has an impressive publication record with 181 publications, including 26 in Q1/Q2 journals, and has accumulated 468 citations, resulting in an h-index of 11. His editorial contributions further demonstrate his standing in the academic community. As a dedicated researcher and educator, Professor Belo has been instrumental in developing computational platforms for specific applications and has contributed significantly to the advancement of Business Intelligence methodologies. His work with the ALGORITMI R&D Centre has fostered numerous collaborative projects and has positioned him as a key figure in data analytics research at the University of Minho. His laboratory affiliations include the CST R&D Group and ISLab R&D Lab, where he continues to lead research initiatives in Business Intelligence, Data Mining, and their applications across various domains including healthcare, telecommunications, and business analytics.
Miguel Matos is an Assistant Professor at Instituto Superior Técnico (IST) of Universidade de Lisboa and a Researcher at INESC-ID's Distributed Systems Group. His research focuses on Persistent Memory systems, blockchain scalability, distributed systems evaluation, and database performance. He has led major projects such as Angainor (reproducible evaluation tools) and ACT-PM (crash-consistency testing). Research interests include exploring persistent memory's challenges, blockchain Layer-2 limitations, automated bug detection (HawkSet, Mumak), and decentralized network emulation (Kollaps). He has received awards like the Gilles Muller Best Artefact Award at EuroSys 2025 and Best Paper Awards at DAIS 2017 and IPDPS 2012. He coordinates multi-million Euro grants including EU's Qualichain and national FCT projects. Teaching includes courses like 'Highly Dependable Systems' and 'Large-Scale Systems Engineering' at IST. His work bridges academia and industry, collaborating with startups like MIMA Housing and LeanXcale.
Fábio André Coelho is a Senior Researcher at HASLab, a research unit within INESC TEC, since January 2014. He holds a PhD in Computer Science from the universities of Minho, Aveiro, and Porto (Portugal) through the MAP-i Doctoral Programme. Research Focus: His work spans cloud HTAP databases, distributed systems, P2P/ledger systems, and benchmarking. Recent efforts include advancing data center sustainability via hybrid cooling solutions and exploring adaptive transactional consistency for georeplicated databases. He also investigates edge/fog databases and energy grid flexibility platforms. Projects & Collaborations: Participated in national/EU projects (CoherentPaaS, LeanBigData, CloudDBAppliance). Currently collaborates with INESC TEC's Power and Energy Centre on ICT solutions for distributed communication and energy systems. Publications: Active contributor to top-tier conferences (SRDS, DAIS, ICPE) and journals like IEEE Transactions on Cloud Computing and ACM Computing Surveys. Recent work includes studies on cooling optimization and georeplicated database consistency models. Advising: Supervised theses on topics like edge time series benchmarks, distributed IoT data management, and Hyperledger Fabric permissions.
Paulo Sérgio Almeida is an Assistant Professor at the Department of Informatics, University of Minho, and a Senior Researcher at HASLab / INESC TEC since November 2011. He holds a PhD in Computer Science from Imperial College London (1998) and an MSc from University of Porto (1994). Research Interests Distributed Systems Causality Tracking Mechanisms Conflict-free Replicated Data Types (CRDTs) Eventually Consistent Databases Network Protocols Fault-tolerant Algorithms His recent publications focus on Byzantine fault tolerance, consistency models, and network protocols. Notable works include the Blocklace universal CRDT framework and the Exon protocol for oblivious exactly-once messaging. Advising: Ziad Ali Kassam – thesis on Exactly-once Exchanges (2021–2023) Ricardo Oliveira Vaz – thesis on Blockchain-based Payment Systems (2022) Labs/Teams: Associate researcher at HASLab / INESC TEC, contributing to distributed systems research.
Jorge Sousa Pinto is an Associate Professor at the Department of Informatics, University of Minho, and a researcher at HASLab/INESC TEC since 2011. He holds a PhD (2001) from École Polytechnique and a Habilitation (2015) from the University of Minho. His research focuses on deductive program verification, model checking, and formal methods, with contributions to tools like Frama-C and Why3. He co-authored the textbook Rigorous Software Development: an Introduction to Program Verification . Education: Docteur de L'Ecole Polytechnique (Paris), 2001 Habilitation, University of Minho, 2015 Research Interests: Deductive verification, formal methods, dynamic logic, distributed systems, and database application validation. Recent publications emphasize verification tool development (e.g., Why3-do for distributed systems) and applying formal methods to space software and databases. His work on the AVIACC project highlights contributions to verification frameworks. No scientific awards explicitly mentioned, but his roles include coordinating major research initiatives and contributing to foundational textbooks. Advised multiple theses on topics like blockchain systems, Why3 formalizations, and distributed algorithm verification. Collaborates on projects such as DBverify and the Why3 platform. Associated with the High-Assurance Software Centre at INESC TEC, focusing on software safety and reliability.
Manuel Filipe Vieira Torres Santos is an Associate Professor with Habilitation at the School of Engineering of the University of Minho, Portugal. He serves as a Senior Researcher at Centro ALGORITMI (Associate Laboratory in Intelligent Systems) where he coordinates the Intelligent Data Systems research lab and the Information Systems and Technologies research group. His academic career combines teaching responsibilities with extensive research activities focused on data science applications in healthcare settings. Dr. Santos' research interests center on applying advanced computational techniques to healthcare challenges. His primary areas include Machine Learning, Knowledge Discovery from Databases, Data Mining, Agent-based Systems, and Intelligent Decision Support Systems. He has pioneered work in Pervasive and Adaptive Business Intelligence specifically tailored for healthcare environments. His research spans both theoretical advancements in data science methodologies and practical implementations in real-world medical settings, particularly in intensive care units, hospital management, and precision medicine applications. Analysis of his recent publications reveals a strong trend toward integrating emerging technologies like blockchain, Internet of Things, and openEHR standards into healthcare information systems. His work demonstrates a progression from foundational data mining techniques to increasingly sophisticated architectures that support real-time decision making, predictive analytics, and personalized patient care. The publications show particular emphasis on standardization efforts, interoperability challenges, and the development of maturity models for digital transformation in healthcare institutions. Coordinator of Intelligent Data Systems research lab Coordinator of Information Systems and Technologies research group Principal Investigator for multiple funded projects including: Intelligent hospitalization management (2021-present) Data Science applied to diabetes (2021-present) Intelligent Decision Support for response times optimization (2020-present) Intelligent Hospital Infection Control (2020-present) Dr. Santos has secured significant research funding for healthcare analytics projects, demonstrating the practical value of his work. His approach combines technical expertise in data science with deep understanding of healthcare workflows and challenges, resulting in solutions that address real clinical needs while advancing the state of the art in health informatics.
Sérgio Duarte is an Assistant Professor at the Department of Informatics, Faculty of Sciences and Technology, Universidade Nova de Lisboa (FCT/UNL). His research focuses on distributed systems, cloud computing, and database management, particularly in consistency models and replication mechanisms. Research Interests: Distributed Systems, Cloud Computing, Conflict-free Replicated Data Types (CRDTs), Consistency Models, Geo-replication, Event-based Systems. Key Contributions: Work on causal consistency, invariant preservation in databases, and client-side fault tolerance in geo-replicated environments. Email: smd@fct.unl.pt
