Nuno Preguiça

Nuno Preguiça is a Full Professor at the Department of Computer Science, Faculty of Science and Technology, Universidade NOVA de Lisboa, where he also serves as the Coordinator of the Computer Systems research area at NOVA LINCS. His research focuses on distributed systems, with particular emphasis on data replication, consistency models, and cloud/edge computing architectures. He has made significant contributions to the field of Conflict-free Replicated Data Types (CRDTs) and their application in geo-replicated systems.

His research interests encompass distributed systems, cloud computing, edge computing, database systems, replication techniques, consistency models, Conflict-free Replicated Data Types (CRDTs), geo-replication, mobile computing, and fault tolerance. Preguiça's work bridges theoretical foundations with practical implementations, developing systems that balance strong consistency guarantees with high availability and performance requirements. He has made notable contributions to understanding the trade-offs between different consistency models and developing practical systems that implement these models efficiently.

His recent publications reveal a strong focus on practical implementations of distributed systems, with particular attention to CRDTs, causal consistency, and geo-replication techniques. His work spans both theoretical foundations and real-world implementations, addressing challenges in environments ranging from highly volatile networks to secure settings and edge computing infrastructures. The research shows a consistent trajectory toward making distributed systems more efficient, reliable, and accessible while maintaining appropriate consistency guarantees.

As an academic advisor, Preguiça has mentored numerous PhD and Master's students, many of whom have gone on to successful careers in academia and industry, including positions at Google, ElectricSQL, and research institutions. His research has been supported by multiple projects including Tardis, SAMOA, LightKone, and AntidoteDB, funded by organizations such as FCT/MCTES, UE H2020, and ANR.

He leads the SwiftCloud and SwiftComp research initiatives, which focus on developing efficient storage and computation solutions for cloud environments using CRDTs. His work has resulted in several open-source software projects including AntidoteDB, AQL, and Legion, which have been adopted by both academic and industrial communities.