We are looking for new Postdocs, PhD students and Master/Bachelor students to join HASLab and work on storage research topics.
If you are interested in working with us, please send me an email.

Meet the team

João Paulo

Assistant Professor
(Coordinator)

Ricardo Macedo

Assistant Researcher

Tânia Esteves

Assistant Researcher

Cláudia Brito

Assistant Researcher

José Pereira

Associate Professor

Mariana Miranda

PhD Student

Rúben Adão

PhD Student

Maria Ramos

PhD Student

Pedro Peixoto

PhD Student

Bruno Pereira

MSc Student

Rui Pedro Oliveira

MSc Student

Mariana Amorim

MSc Student

José Fernandes

MSc Student

Diana Rodrigues

MSc Student

Guilherme Fernandes

MSc Student

Francisco Neves

MSc Student

Carlos Machado

MSc Student

Gonçalo Sousa

MSc Student

André Ferreira

MSc Student

Bruno Gião

MSc Student

Ana Rita Vaz

MSc Student

Daniel Pereira

MSc Student

Edgar Araújo

BSc Student

Paula Rodrigues

Communication

Alumni

  • Sara Pereira (MSc Thesis) - Towards Fine-grained, Holistic Energy Control in Large-Scale Computing Infrastructures, 2024.

  • Diogo Costa - Research on SPDK and I/O Profiling, 2024.

  • Cláudia Brito (PhD Thesis) - Towards a Privacy-Preserving Distributed Machine Learning Framework, 2024.

  • Tânia Esteves (PhD Thesis) - Flexible Tracing and Analysis of Applications’ I/O Behavior, 2024.

  • Rúben Adão (MSc Thesis) - Co-designing Log-Structured Merge Key-Value Stores with a Non-Volatile Storage Hierarchy, 2024.

  • Maria Ramos (MSc Thesis) - Reproducible Fault Injection for Local Storage Systems, 2024.

  • Maria Beatriz Moreira (MSc Thesis) - I/O Optimizations for Distributed Deep Learning Training, 2024.

  • Ricardo Macedo (PhD Thesis) - User-level Software-Defined Storage Data Planes, 2023.

  • Pedro Rodrigues (MSc Thesis) - Analysis of I/O patterns for Data Management Systems, 2023.

  • Alexandre Ferreira (MSc Thesis) - Fault-tolerant and Large-scale Storage for POSIX-compliant Applications, 2023.

  • Alexandre Miranda (MSc Thesis) - Realistic Assesment of Failures in the SPDK Platform, 2023.

  • João Azevedo (MSc Thesis) - Realistic Fault Assessment for Distributed Storage Systems, 2022.

  • Marco Dantas (MSc Thesis) - Accelerating Deep Learning Training on High-Performance Computing with Storage Tiering, 2022.

  • Diogo Leitão - Research work on I/O optimizations for deep learning and persistent memory, 2022.

  • Alberto Faria - Research on userspace storage block devices, 2022.

  • César Borges - Research on fault-injection benchmarking, 2022.

  • Diogo Ribeiro - Research work on storage tiering, 2021.

  • Rogério Pontes (PhD Thesis) - Trade-offs between privacy and efficiency on databases, 2021.

  • Diogo Leitão (MSc Thesis) - RSafeFS: Modular File System for Remote Storage, 2021.

  • Carlos Pedrosa (MSc Thesis) - HIODS: Hybrid Inline and Offline Deduplication System, 2021.

  • Cláudia Correia (MSc Thesis) - PRISMA: A Prefetching Storage Middleware for Accelerating Deep Learning Frameworks, 2021.

  • Daniel Fernandes (MSc Thesis) - LSFS: Large-scale fault-tolerant file system, 2021.

  • Mariana Miranda (MSc Thesis) - S2Dedup: SGX-enabled Secure Deduplication System, 2020.

  • Alexandre Silva (MSc Thesis) - DEDISBench++: Realistic evaluation of storage systems supporting deduplication and compression, 2020.

  • Tânia Esteves (MSc Thesis) - Configurable and Secure Storage Systems, 2018.