جست‌وجوی استاد و پژوهشگر

• Cloud Computing
• Distributed Systems
• Data Processing
• +۴ مورد دیگر

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.

Diogo Ribeiro Ferreiraمشاهده پروفایل

دانشیار

• Data Science
• Applied Machine Learning
• Deep Learning
• +۶ مورد دیگر

Diogo Ribeiro Ferreira is an Associate Professor of Information Systems at Instituto Superior Técnico (IST) , part of the University of Lisbon . He is also a researcher at the Institute of Plasmas and Nuclear Fusion (IPFN) . His career spans teaching, research, and collaboration with institutions like JET (Joint European Torus) in nuclear fusion. His research focuses on Data Science , Applied Machine Learning , Deep Learning , and Process Mining , with applications in Nuclear Fusion (plasma diagnostics, disruption prediction) and Information Systems (workflow management, healthcare process analysis). He has taught courses like Data Administration in Information Systems and Data Analysis and Integration since 2003. His work bridges Computer Science and Physics , particularly in using Graph Neural Networks for plasma modeling and GPU Acceleration for high-performance computing. He has supervised over 20 PhD and MSc students, including André C. Santos and Fernando Szimanski, and co-authored 15+ recent publications in journals like Journal of Plasma Physics and Fusion Engineering and Design . Scientific Awards: 2012 ICGA Journal Award Best Paper Award at 9th IEEE International EDOC Conference 2005 Collaborations: Affiliated with JET Contributors and IPFN, focusing on real-time tomography and fusion reactor optimization.

• Building Automation
• Energy Management
• Query Optimization
• +۷ مورد دیگر

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

• Compilation
• High-level Synthesis
• Domain-specific Languages
• +۴ مورد دیگر

João Manuel Paiva Cardoso is a Full Professor at the Department of Informatics Engineering, Faculty of Engineering, University of Porto, and a research member of INESC TEC. He currently serves as Department Director and Chairman of the Department Council for the Department of Informatics Engineering. His educational background includes: Electronics Engineering degree from the University of Aveiro (1993) MSc in Electrical and Computer Engineering from the Technical University of Lisbon (1997) PhD in Electrical and Computer Engineering from the Technical University of Lisbon (2001) His research focuses on compilation and high-level synthesis techniques, domain-specific languages, reconfigurable computing, and hardware/software codesign. He has co-authored over 200 scientific publications including a Springer book, two edited Springer books, and three LNCS volumes. His conference leadership roles include General Chair for IEEE ASAP'2023 and FPL'2013, demonstrating significant contributions to reconfigurable computing and embedded systems domains. He has coordinated major research projects such as the EU FP7 REFLECT project (2010-2012) as co-scientific coordinator and the H2020 FET-HPC ANTAREX project as technical manager, alongside nationally funded initiatives. He holds senior memberships in IEEE and ACM, and is a member of the IEEE Computer Society.

José Orlando Pereiraمشاهده پروفایل

دانشیار

• Dependable Distributed Systems
• Data Management
• Database Replication
• +۷ مورد دیگر

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.

Aleksandar Ilicمشاهده پروفایل

استادیار

• High-Performance Computing
• Computer Architecture
• Heterogeneous Systems
• +۴ مورد دیگر

Aleksandar Ilic is an Assistant Professor at the Department of Electrical and Computer Engineering (DEEC) at Instituto Superior Técnico (IST), University of Lisbon, and a Senior Researcher at the Signal Processing Systems (SiPS) Group at INESC-ID, Lisbon. His research focuses on high-performance computing, energy-efficient architectures, and heterogeneous systems. He holds a Ph.D. from IST, supervised by Prof. Leonel Sousa. Education: Ph.D. in Electrical and Computer Engineering, Instituto Superior Técnico (2014) M.Sc. in Electrical and Computer Engineering, University of Niš, Serbia (2007) Research Interests: His work emphasizes optimizing computational performance and energy efficiency in modern architectures, including GPUs, FPGAs, and multi-core CPUs. Key areas include epistasis detection in bioinformatics, cache-aware performance modeling (CARM), and parallel processing frameworks for heterogeneous systems. Recent projects like SparCity and IntelCARM aim to enhance sparse computation and roofline model applications. Awards & Grants: Intel Innovator Award (2020) HiPEAC Tech Transfer Award (2017) Multiple Excellence in Teaching Awards from IST students (2015–2020) Intel Research Grants (2018–2020) Advising & Labs: He supervises M.Sc. students in topics like FPGA acceleration for epistasis detection, GPU performance modeling, and secure embedded systems. His lab develops tools like CARM and collaborates on EU-funded projects such as SparCity.

• Artificial Intelligence
• Computational Biology
• Medical Data Privacy
• +۳ مورد دیگر

Dr. Matthias Becker is a researcher at the German Center for Neurodegenerative Diseases (DZNE) , leading projects at the intersection of artificial intelligence, molecular generation, and privacy-preserving data utilization. His work focuses on advancing generative modeling techniques and deploying them in collaborative initiatives across institutions. Developed DrugDiff , a latent diffusion model for controlled generation of drug-like molecules with adjustable molecular properties. Contributed to the PriSyn project, pioneering synthetic data generation via differentially private machine learning to enable privacy-compliant medical research. Active in Swarm Learning , applying decentralized AI to high-dimensional flow cytometry, medical imaging, and large language model fine-tuning. Leverages HPC/GPU clusters and evaluates FPGA technologies for energy-efficient computational pipelines. His research emphasizes sustainability in AI by optimizing model architectures for reduced energy consumption and data efficiency, while addressing critical challenges in neurodegenerative disease studies and personalized medicine. Publications include a 2024 study in Journal of Cheminformatics analyzing autoencoder architectures for molecular data. Collaborations span the CISPA Helmholtz Center, QuantPi, and Hewlett Packard Enterprise.

João Tiago Pauloمشاهده پروفایل

استادیار

• Distributed Systems
• Storage Systems
• Database Systems
• +۶ مورد دیگر

João Tiago Paulo is an Assistant Professor at the University of Minho and a Senior Researcher at INESC TEC. He obtained his PhD in Computer Science from the MAP-i Doctoral Program, focusing on large-scale distributed systems, storage, and database scalability, performance, security, and dependability. His work addresses complex data management challenges in Cloud Computing and HPC environments. Research Interests: João specializes in Reliable Distributed Storage Systems Software-Defined Storage architectures Privacy and security in data management Fault injection for debugging storage systems Performance benchmarking and optimization Publication Trends: His recent work spans distributed systems, storage scalability, fault reproduction, and privacy-preserving machine learning. He has published in venues like Transportation Engineering , Proceedings of the VLDB Endowment , and SC24-W , with keywords intersecting computer science, HPC, and data security. Supervised Theses: João has supervised multiple MSc theses at INESCTEC, covering topics like edge time series database benchmarking, distributed storage optimizations, privacy-preserving ML frameworks, and fault injection in storage systems.

Ricardo Gonçalves Macedoمشاهده پروفایل

استادیار

• Storage Systems
• Operating Systems
• High-Performance Computing (HPC)
• +۳ مورد دیگر

Ricardo Gonçalves Macedo is an Invited Assistant Professor at the University of Minho and a Researcher at INESC TEC's Distributed Storage Research (DSR) team since 2016. He holds a PhD in Computer Science (2023) from the MAP-i program at Universities of Minho, Aveiro, and Porto, focusing on user-level software-defined storage data planes. His research emphasizes storage systems and operating systems, addressing performance, reliability, and energy efficiency in large-scale I/O infrastructures. Key areas include kernel-bypass storage stacks, disaggregated resources, and HPC storage challenges. Recent work includes tools like LAZYFS for fault injection and PADLL for metadata QoS control. He leads projects like DisaggregatedHPC (energy-efficient resource disaggregation) and CDMS (healthcare data management). Ricardo has supervised over 10 theses at the University of Minho and contributes to open-source projects in storage optimization. His work is published in top venues like VLDB, IEEE Cluster, and FAST.

Ricardo Jorge Bessaمشاهده پروفایل

پژوهشگر

• Renewable Energy
• Sustainable Energy Systems
• Smart Grids
• +۶ مورد دیگر

Ricardo Jorge Bessa is the Coordinator of the Center for Power and Energy Systems at INESC TEC. He holds a Licenciado in Electrical and Computer Engineering (2006, FEUP), M.Sc. in Data Analysis (2008, FEP), and Ph.D. in Sustainable Energy Systems (2013, MIT Portugal Program). His research focuses on renewable energy integration, smart grids, and decarbonization strategies. He leads European projects such as Horizon 2020 UPGRID and collaborates with Argonne National Laboratory. As an IEEE Senior Member and Associate Editor of IEEE Transactions on Sustainable Energy, he has authored over 60 journal papers and 120 conference papers. His work addresses challenges in energy storage, AI-driven forecasting, and carbon-aware infrastructure design. **Education**: Licenciado (5-year), Electrical and Computer Engineering, FEUP (2006) M.Sc., Data Analysis and Decision Support Systems, FEP (2008) Ph.D., Sustainable Energy Systems (MIT Portugal), FEUP (2013) **Research Interests**: Renewable energy forecasting and market mechanisms Smart grid flexibility and decarbonization High-performance computing sustainability Electric vehicle infrastructure optimization **Key Projects**: European FP6/FP7/Horizon 2020 initiatives, Argonne collaboration, and national energy storage consulting. **Awards**: ESIG Excellence Award (2022). **Advising**: Supervised 8+ theses on energy systems optimization and sustainability. **Labs/Teams**: Leads the INESC TEC Power and Energy Systems team, collaborating with academia and industry on grid resilience and green hydrogen production.

• Heterogeneous Architectures
• High-Performance Computing
• Computer Systems Technologies
• +۴ مورد دیگر

Leonel Augusto Pires Seabra de Sousa is a Full Professor at the University of Lisbon's Instituto Superior Técnico and a principal researcher at INESC-ID. His primary research focuses on heterogeneous architectures for high-performance computing, computer systems technologies, and cryptographic hardware acceleration. He holds a Fellow status with the IET and has been recognized as a Senior Member of both ACM and IEEE. Roles: Full Professor, Researcher (INESC-ID) Education: Details not explicitly provided in text His work spans parallel computing, embedded systems, and bioinformatics applications. Key contributions include energy-efficient architectures, RNS-based cryptographic accelerators, and GPU-driven phylogenetic analysis. Over 150 publications highlight his impact in these areas. Recent projects include COPMA (post-quantum cryptography hardware) and low-power 5G positioning systems. Awards include the HiPEAC Paper Award and multiple academic recognitions. Advising focuses on PhD/MSc students in HPC and embedded systems. Collaborates with industry partners on FPGA and GPU-based solutions.

António Luís Sousaمشاهده پروفایل

استادیار

• Dependable Distributed Systems
• Distributed Database Systems
• Cloud Computing Management
• +۵ مورد دیگر

António Luís Sousa is an Assistant Professor at the Department of Informatics, University of Minho, and a Senior Researcher at HASLab/INESC TEC. He has served as Centre Coordinator since 2011, focusing on high-assurance software systems. His research emphasizes dependable distributed systems, cloud computing, and applications in healthcare informatics. He actively supervises graduate students, with recent theses addressing topics like cloud-based medical imaging systems, workflow engines, and IoT platforms for medical sensors. Research interests include distributed database systems, scalable cloud architectures, and AI-driven solutions for medical imaging. Notable projects involve GAN-based MRI generation in HPC environments and privacy-preserving DICOM systems using Kubernetes. His work bridges distributed computing with healthcare challenges, leveraging frameworks like ChainerMN and Apache HBase. Publications span medical imaging generation, IoT healthcare monitoring, and deep learning for ECG classification. He collaborates with institutions like INESC TEC and has advised over a dozen students. No scientific awards are explicitly mentioned, but his contributions highlight advancements in both theoretical and applied computing for healthcare.