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.
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.
João Carlos Antunes Leitão is an Associate Professor in the Informatics Department at Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa , and an Integrated Member of NOVA Laboratory for Computer Science and Informatics (NOVA LINCS) . His research focuses on the scalability and dependability of large-scale distributed systems, particularly in cloud computing , peer-to-peer networks , and geo-distributed environments . He leads work packages in European research projects such as TaRDIS and contributes to projects like Syncfree and LightKone. Research interests include: Scalability of distributed systems Causal consistency in geo-replicated storage Self-organizing overlay networks Edge and fog computing Searchable encryption on trusted hardware Framework development for distributed protocols Publication trends show consistent work on distributed hash tables , causal consistency , edge computing , and secure protocols . His framework Babel is designed for performant and dependable distributed protocol development with applications in self-configuration and security. Scientific awards : Best student paper at IEEE NCA13 (2013) Best Paper Award at Inforum 2018 Best Student Paper at CPDLA Track, Inforum 2023 Best Paper Award at Inforum 2011 Advising and grants : João earned his Ph.D. from Instituto Superior Técnico (IST) under Prof. Luis Rodrigues . He has supervised students like Pedro Fouto, Pedro Ákos Costa, and Nuno Preguiça. His research is supported by European projects TaRDIS , Syncfree , and LightKone . Labs and teams : João works with the Computer Systems Group at NOVA LINCS and contributes to open-source frameworks like Babel and Yggdrasil for distributed protocol development and wireless edge systems.
Francisco Miguel Cruz is an External Research Collaborator and postdoctoral researcher at INESC TEC's High-Assurance Software Centre since January 2012, holding a PhD from the University of Minho (2016) where he completed all academic degrees. His research trajectory spans cloud infrastructure and distributed database systems with emphasis on practical scalability solutions. Educational background: B.Sc. in Computer Science, University of Minho (2007) M.Sc. in Computer Science, University of Minho (2009) Ph.D. in Informatics Engineering, University of Minho (2016) His research focuses on bridging theoretical database concepts with cloud deployment realities, particularly in NoSQL ecosystems. Key contributions include predictive resource modeling for key-value stores, transactional middleware development, and workload-aware data partitioning techniques that address critical bottlenecks in massive-scale data management. His work demonstrates consistent innovation in enhancing elasticity and performance characteristics of distributed databases. Analysis of his 2014-2016 publications reveals a cohesive research thread targeting practical optimization of NoSQL systems through novel prediction mechanisms and architectural innovations. The publications collectively advance understanding of cache behavior, resource allocation, and transactional guarantees in cloud-native data stores, showing strong alignment with industry scalability challenges. Dr. Cruz supervised João Pedro Nóbrega Rei's 2018 thesis on IoT medical sensor platforms and contributed to the HPLabs-funded DC2MS project (Dependable Cloud Computing Management Services). His research methodology combines rigorous experimental validation with real-world system implementation, as evidenced by throughput impact measurements in transactional middleware development. As a core member of HASLab (High-Assurance Software Laboratory) at INESC TEC, he participates in developing dependable software systems with emphasis on cloud infrastructure reliability and performance predictability.
José Orlando Pereira is an Associate Professor at the Department of Informatics, University of Minho, and Research Coordinator at INESC TEC (INESC Technology and Science). His primary research interests lie in dependable distributed systems, with a focus on data management, group communication protocols, and tools for distributed system evaluation. He leads the High-Assurance Software Laboratory (HASLab) , part of INESC TEC and the University of Minho. Roles: Academic supervisor, conference committee member (e.g., SRDS 2025 General Co-Chair), and grant recipient (e.g., ADAPQO funding from CMU Portugal 2024). Key Projects: Includes CYBERACTIONING (cybersecurity education), EUMaster4HPC (European HPC master's program), and AIDA (adaptive assurance platform). Research Themes: Database replication, georeplicated systems, consensus protocols, edge computing, and fault injection tools like LAZYFS. His work emphasizes practical applications, such as improving transactional performance in hybrid workloads (TiQuE) and designing scalable NoSQL middleware (CloudMdsQL). He has authored over 200 publications, including seminal contributions to gossip protocols (HyParView) and consensus algorithms. Awards: Honorable Mention at ACM SIGMOD 2025 for CRDV research. Active in organizing conferences such as SRDS, DSN, and EuroSys. Teaching: Offers advanced courses on distributed systems, database administration, and large-scale data replication at both undergraduate and graduate levels.
Rogério António Pontes serves as an External Research Collaborator at INESC TEC's High-Assurance Software Centre (HASLab) since July 2014, contributing to cutting-edge research in computer security and data privacy. His work bridges academic innovation with industry-relevant solutions for secure data systems. He completed his Master's thesis on "Linear Algebra Approach to OLAP systems" and is currently pursuing his PhD through the MAP-i Doctoral programme, focusing on data privacy challenges in collaboration with the European SafeCloud-eu project. His educational trajectory demonstrates a clear progression from theoretical foundations to applied security research. Pontes' research centers on practical implementations of privacy-preserving technologies across distributed environments. His expertise spans cryptographic protocols for secure computation, oblivious database operations, and multi-cloud storage architectures. He addresses critical gaps in data security by developing systems that maintain confidentiality without sacrificing performance, with particular emphasis on real-world deployability in cloud and distributed infrastructures. His publication record reveals a consistent trajectory toward increasingly sophisticated secure system designs. Early work established foundations in secure file systems (SafeFS, 2017) and multi-cloud databases (d'Artagnan, 2019), evolving toward optimized oblivious search (CODBS, 2021) and general-purpose secure CRDTs (2023). This progression demonstrates mastery in combining cryptographic theory with systems engineering to solve concrete privacy challenges. As an integral member of HASLab at INESC TEC, Pontes collaborates within a high-assurance software research ecosystem focused on developing verifiable security solutions. His work directly impacts how sensitive data is processed in untrusted environments, contributing to Portugal's growing reputation in cybersecurity research through both theoretical contributions and open-source implementations.
Pedro Ramos is a Full Professor and Director at the Department of Information Science and Technology (ISTA), ISCTE-IUL University Institute of Lisbon. He is also an Integrated Researcher at ISTAR-Iscte, a leading research center in Information Sciences, Technologies, and Architecture. His academic leadership includes directing various degree programs and serving on institutional governance bodies such as the Scientific Committee and General Council. PhD in Information Sciences and Technologies (ISCTE-IUL, 1999) Master's in Business Sciences (ISCTE-IUL, 1992) Bachelor's in Business Organization and Management (ISCTE-IUL, 1988) His research focuses on Information Systems , NoSQL databases , formal modeling of organizations , and big data management . He explores applications in distributed systems, semantic web, and data mining for business intelligence and public policy. His work bridges theoretical modeling and practical implementation in enterprise IT environments. His recent publications span high-impact journals in transportation, tourism, education, and information systems. Key themes include semantic interoperability in bibliographic data , passenger rail disruption management , data mining for guest satisfaction , and social media engagement in sports and fashion . His research consistently applies computational and analytical methods to real-world organizational challenges. Pedro Ramos has played a central role in developing and coordinating master's programs in Information Systems and related fields. He actively supervises both Master’s and PhD students, with ongoing projects in formal ontologies, public policy, business performance, and decision support systems. He has also contributed to institutional research projects funded by European programs. He leads research at ISTAR-Iscte and has held key administrative roles, including Director of the Department of Information Science and Technology and leadership in academic councils. His work integrates research, teaching, and institutional development.
Carlos Fernando da Silva Ramos is a Full Professor at the School of Engineering , Polytechnic Institute of Porto (ISEP/IPP), with over 30 years of experience in Artificial Intelligence and Smart Systems . He holds a PhD and Habilitation in Electrical and Computer Engineering from the University of Porto and has held leadership roles including Vice-President for R&D at IPP and Pro-President for International Relations. His research spans AI Planning , Multiagent Systems , and Smart Grids , with applications in Energy Systems , Smart Cities , and Tourism . He founded GECAD, an FCT-ranked Excellent R&D unit, and contributes to LASI, Portugal's AI Associated Lab. Recent work focuses on Electricity Market Simulation , Smart Grid Data Management , and Context-Aware Tourism , as evidenced by high-impact publications in IEEE , Elsevier , and Springer venues. His projects include LAPASSION (ERASMUS+, €999k), MUWO (ITEA3, €7.478M), and ARANOUA (Samsung, €144k). Scientific Awards: 2024 Stanford Top 2% Scientist Ranking He has supervised 13 completed PhD projects and 2 ongoing , with grants from FCT, European Commission, and industry partners. His lab, GECAD, leads research in Intelligent Engineering and Computing for Advanced Innovation .
Rui Oliveira is an Associate Professor at Universidade do Minho in Portugal, affiliated with the Distributed Systems Group. His research focuses on dependable distributed systems, fault-tolerant database systems, and large-scale distributed systems. He teaches Distributed Systems across undergraduate, master's, and doctoral programs. Research Interests His work spans epidemic communication protocols, data management in cloud environments, and high-performance transactional middleware. Recent contributions include frameworks for privacy-preserving machine learning (SOTERIA), distributed tracing (CAT), and fault-diagnosis tools for I/O behavior analysis. Key Contributions Developed the Loom disaggregated database system, the TADA distributed agreement toolkit, and the DATAFLASKS epidemic storage substrate. His work emphasizes practical implementations of scalable and resilient distributed systems. Labs/Teams Affiliated with HASLab (Hardware and Software Systems Laboratory), focusing on distributed systems research. Collaborates with industry on cloud computing and cybersecurity challenges.
