جست‌وجوی استاد و پژوهشگر

Rui Soares Barbosaمشاهده پروفایل

پژوهشگر

• Quantum Foundations
• Quantum Computer Science
• Mathematics of Quantum Theory
• +۶ مورد دیگر

Rui Soares Barbosa is a Staff Researcher at the Quantum and Linear-Optical Computation group at the International Iberian Nanotechnology Laboratory (INL). He holds a BSc in Computer Science from Universidade do Minho (2009), an MSc in Mathematics and Foundations of Computer Science from the University of Oxford (2010), and a DPhil in Computer Science from Oxford (2015) with a thesis on Contextuality in quantum mechanics and beyond. Prior to joining INL, he held post-doctoral positions at Oxford (2015–2019) and the University of Edinburgh (2019–2020), and a Research Fellowship at the Simons Institute for the Theory of Computing, UC Berkeley (2017). Barbosa's research lies at the intersection of Computer Science, Physics, and Mathematics, focusing on quantum foundations, quantum computer science, and the mathematics of quantum theory. His work emphasizes logical, structural, and compositional aspects, particularly investigating non-locality and contextuality - phenomena that distinguish quantum theory from classical physics and have been linked to quantum informatic advantage. He employs mathematical tools from category theory, logic, probability, algebraic topology, and operator algebras to achieve a structural understanding of quantum systems' non-classical features. His recent publications demonstrate a strong focus on contextuality as a quantum resource, exploring its connections to causality, computational advantage, and logical structures. The research spans theoretical foundations to practical quantum computing applications, with particular attention to mathematical frameworks like sheaf theory that elegantly express quantum contextuality. His work often involves collaborations with leading researchers in quantum foundations and theoretical computer science. Barbosa actively advises multiple PhD and MSc students including Angelos Bampounis, Rafael Wagner, Nico Witrock, and others. His research group at INL, the Quantum and Linear-Optical Computation group, conducts cutting-edge research at the intersection of quantum theory and computer science, regularly presenting findings at major conferences like the International Conference on Quantum Physics and Logic (QPL).

Rodrigo Venturaمشاهده پروفایل

دانشیار

• Robotics
• Artificial Intelligence
• Human-Robot Interaction
• +۴ مورد دیگر

Rodrigo Ventura is an Associate Professor at the Department of Electrical and Computer Engineering, Instituto Superior Técnico (IST), University of Lisbon. He is also a senior researcher at the Institute for Systems and Robotics (ISR-Lisbon), leading the Space and Aeronautics thematic line. His research focuses on the intersection of Robotics and Artificial Intelligence, emphasizing human-robot interaction, space robotics, and cognitive architectures. He coordinates the Minor in Space Sciences and Technologies at IST and the MBE on Space Systems for Tecnico+. As Adjoint Faculty at the International Space University (ISU), he contributes to global academic initiatives. His work includes experiments on the International Space Station and participation in analog space missions. Research interests span biologically inspired systems, machine learning, and teleoperation interfaces. Recent publications address reinforcement learning for UAVs, microgravity experiments, and pseudo-haptic feedback for robotic control. He teaches subjects like Artificial Intelligence and Decision Systems, Satellite Engineering, and Autonomous Systems.

• Artificial Intelligence
• Healthcare Informatics
• Data Science
• +۵ مورد دیگر

Luís B. Elvas is an Assistant Professor at ISCTE-University Institute of Lisbon's Department of Social and Business Sciences (SINTRA) and a Research Assistant at ISTAR-Iscte Research Center. He holds qualifications including a Technical Specialization in TensorFlow for AI (Coursera, 2021) and certifications in IoT/Blockchain from ISCTE and cybersecurity from Palo Alto Networks. His research spans artificial intelligence, healthcare informatics, smart cities, and blockchain, with applied work in medical imaging, data sharing, and urban analytics. Research interests include: Healthcare AI : Developing deep learning models for cardiac diagnostics, medical imaging analysis, and blockchain-based health data systems Smart Cities : Implementing IoT solutions for urban mobility optimization, disaster management, and sustainable transportation Data Science : Creating predictive analytics frameworks for clinical decision support and urban planning His publications demonstrate a strong focus on AI-driven healthcare solutions (67% of recent works) and smart city technologies (33%), with emerging interests in blockchain and NLP. Research consistently targets real-world applications in clinical settings and urban environments. Awards: Award for best internship, Order of Engineers (2022) Distinction for best internship, Order of Engineers (2021) He leads/contributes to multiple EU research consortia including AMR-EDUCare (antimicrobial resistance education), NEEM (e-health in Nepal), and Blockchain.PT. Coordinates the IEEE Computational Intelligence Society Student Branch Chapter at ISCTE and developed the ManagiDiTH master's program in digital health transformation.

• Indoor Positioning
• Mobile Computing
• Context-aware Computing
• +۷ مورد دیگر

Adriano Jorge Cardoso Moreira is an Associate Professor with Habilitation at the Department of Information Systems, School of Engineering, Universidade do Minho, Portugal. He is also a Senior Researcher at the Algoritmi Research Centre and Scientific Coordinator of the Urban and Mobile Computing department at Centro de Computação Gráfica. His research focuses on indoor positioning , mobile and context-aware computing , urban computing , and simulation of wireless networks . Research Interests : Indoor Positioning, Mobile Computing, Urban Mobility, Sensor Networks, Wi-Fi and UWB Localization, Smart Cities. Leadership : Coordinated the Computer Communications and Pervasive Media Group (2008-2016), Scientific Committee member (Director of MAP-tele PhD program in multiple terms), and leads the Master in Telecommunications and Informatics since 2021. Publications : Over 100 papers, including IEEE Transactions and Sensors journal articles, with an h-index of 23 and 2136 citations. Awards : First and second prizes in EvAAL-ETRI Indoor Localization Competitions (2015, 2016, 2017).

• Complex Systems
• Computational Modeling
• Network Science
• +۷ مورد دیگر

Jorge Louçã is a Full Professor in the Department of Information Science and Technology at ISCTE-IUL, where he has been a faculty member since 2000. He is also an Integrated Researcher at ISTAR-Iscte, the Research Center in Information Sciences, Technologies and Architecture, and leads the research group The Observatorium . He holds a PhD in Computer Science and Artificial Intelligence from Université Paris Dauphine and the University of Lisbon, and completed his Aggregation in Complexity Sciences in 2019. PhD in Computing – University of Lisbon & Université Paris-Dauphine (2000) Master’s in Informatique: Intelligent Systems – Université Paris-Dauphine (1995) Aggregation in Complexity Sciences – ISCTE-IUL (2019) His research centers on computational modeling of social systems, focusing on data-intensive analysis of human communication, knowledge generation in large networks, and the dynamics of complex systems. He founded the Doctoral Program in Complexity Sciences and has been instrumental in advancing the field through international collaborations such as the UNESCO Unitwin network for the Complex Systems Digital Campus and participation in the Conference on Complex Systems (CCS/ECCS). The recent publications highlight a strong interdisciplinary focus, combining network science, data analysis, and social theory. Key themes include the modeling of malaria transmission, information diffusion in social media, structural inequality in education, and the dynamics of opinion and popularity. His work often employs agent-based models, temporal network analysis, and entropy-based measures, reflecting a deep integration of computational and theoretical approaches. Research Methods for Doctorate in Complexity Sciences Advanced Topics in Complexity Sciences Data Science Fundamentals Development for the Internet and Mobile Applications Web Interfaces for Data Management Advanced Network Analysis Jorge Louçã has supervised over a dozen doctoral and master’s students, with completed theses on topics such as malaria modeling, information diffusion, temporal networks, and social inequality. His research has been supported by projects like NESS (Non-Equilibrium Social Science in ICT and Economics), reflecting his leadership in interdisciplinary science. He has held significant academic management roles, including Director of the Department of Information Science and Technology and head of multiple degree programs. His work continues to bridge computer science, social science, and policy, positioning him as a key figure in the global complexity science community.

Giorgio C. Buttazzoمشاهده پروفایل

استاد

• Real-Time Systems
• Heterogeneous Computing
• Robotics
• +۴ مورد دیگر

Giorgio C. Buttazzo is a Full Professor of Computer Engineering at the Scuola Superiore Sant'Anna in Pisa, Italy, and founder/director of the RETIS Lab. His career includes roles at the University of Pavia and co-founding Evidence s.r.l. (a real-time embedded systems company). He holds an IEEE Fellowship (2012) and the IEEE TC RTS Outstanding Technical Contributions Award (2013). Education: Electronic Engineering (University of Pisa, 1985), Master in Computer Science (University of Pennsylvania, 1987), PhD in Computer Engineering (Scuola Superiore Sant'Anna, 1991). Affiliations: TeCIP Institute, RETIS Lab, and leadership roles in IEEE Technical Committees. Research focuses on real-time systems, robotics, and AI integration. He has authored 10 books, over 300 papers, and pioneered frameworks like the ERIKA/SHARK kernels. Current projects include RETICULATE, OPERAND, and NANCY (5G networks). Teaching includes Real-Time Systems, Neural Networks, and Jazz Guitar Improvisation. Advised over 150 master and PhD students. Active in conferences like ECRTS, RTSS, and RTAS.

• intelligent systems
• Machine Learning
• evolutionary algorithms
• +۴ مورد دیگر

Teresa Cristina de Freitas Gonçalves is an Associate Professor at the Department of Informatics, School of Sciences and Technology, University of Évora, where she has been employed since 1999. She serves as an integrated researcher at the ALGORITMI research centre and is the Director of the VISTA Lab (Video, Image, Speech and text Analysis Lab), the unit of the ALGORITMI research centre at University of Évora. Her leadership roles include Director of the Master programme in Informatics Engineering and deputy Director of both the Master programme in Artificial Intelligence and Data Science and the Doctoral program in Computer Science. She earned her PhD in Computer Science from University of Évora and a MSc degree in Informatics Engineering from New University of Lisbon. Her academic journey at University of Évora has included significant leadership positions including Head of the Computer Science Department (2011-2015), Director of the Bachelor programme in Informatics Engineering (2016-2021), and Deputy Director roles for various undergraduate and graduate programs. Dr. Gonçalves' research focuses on intelligent systems, particularly Machine Learning approaches, with substantial contributions in evolutionary algorithms, information extraction and retrieval, and supervised learning across multiple data modalities including tabular data, text (in both Portuguese and English), and images (medical and satellite). Her work bridges theoretical advances with practical applications in healthcare, remote sensing, and natural language processing. She has successfully supervised 6 doctoral theses, 19 master theses, and 3 postdocs, and currently mentors 5 doctoral and 6 master students from diverse international backgrounds including Bangladesh, Cabo Verde, Nepal, Philippines, India, Sri Lanka, China, Mongolia, and Portugal. Her publication record includes over 100 scientific articles indexed by Scopus with 640 citations and an h-index of 12, demonstrating significant international impact with 56% of her work involving international collaboration. Her recent research shows a strong trend toward applying advanced machine learning techniques to healthcare applications, information retrieval systems, and remote sensing analysis, with particular emphasis on transformer networks, learning-to-rank methodologies, and multimodal data analysis. Dr. Gonçalves has made substantial contributions to the academic community through her service as a reviewer for over 50 articles in prestigious international journals and conferences, and as chair for major international conferences including IDEAL 2023, PROPOR 2020, SKIMA 2017 and 2018, and CLEF 2016. She serves on the board of APRP (Associação Portuguesa de reconhecimento de Padrões) and as a jury member for APRP prizes for best MSc and PhD theses. Her current research portfolio includes coordination of the Horizon Europe MSCA Staff Exchange HarmonicAI project and local coordination of WP6 in the NewSpace Portugal mobilising agenda. She is also actively involved in numerous other international research initiatives including Interreg VI-B Sudoe SenforFire, PRR CANTE, La Caixa INCOME, Erasmus+ KA220-HED REDINEST, Interreg POCTEP TID4AGRO, and ATTRACT DIH projects. Previously, she led the FCT AI in the Public Administration SNS24.Scout.IA project and coordinated the FEDER R&D NIIAA project. As Director of the VISTA Lab, Dr. Gonçalves leads a dynamic research team focused on video, image, speech, and text analysis. The lab serves as the Évora hub of the ALGORITMI research centre and has established strong international collaborations. Under her leadership, the VISTA Lab has developed innovative approaches in medical image analysis, natural language processing for Portuguese, and satellite image classification, with applications spanning healthcare, environmental monitoring, and public administration.

• Machine Learning
• Molecular Modeling
• Drug Discovery
• +۴ مورد دیگر

Sungsoo Ahn is an Assistant Professor at the Graduate School of AI, KAIST, where he leads the Structured and Probabilistic Machine Learning (SPML) Lab. His research focuses on developing machine learning algorithms for molecular science, particularly in drug discovery, material design, and generative modeling. He directs a team of 13 researchers (including 2 post-docs and 11 students) and maintains collaborations with institutions like Mila and industry partners. His core research integrates probabilistic machine learning , generative models , and AI for science , with applications spanning molecular dynamics simulation, language model reasoning, combinatorial optimization, and graph neural networks. Key methodologies include flow matching, diffusion models, GFlowNets, and equivariant neural networks applied to chemical and biological domains. Recent publications (2023–2025) demonstrate strong emphases on: (1) Molecular generation/optimization for drug design, (2) Enhancing reliability and reasoning in large language models, (3) Graph-based machine learning for scientific discovery, and (4) Efficient training paradigms for generative samplers. These appear predominantly in NeurIPS, ICML, ICLR, and ACL. He advises multiple PhD/master's students and post-doctoral researchers in the SPML Lab. Current research directions include torsion-aware molecular generation, causal AI safety, neural operators for quantum chemistry, and multi-agent systems for molecular optimization.

• Embedded real-time systems
• Computer architectures
• Hardware/software co-design for IoT
• +۵ مورد دیگر

Tiago Manuel Ribeiro Gomes is an Assistant Professor at the Department of Industrial Electronics within the School of Engineering at the University of Minho, Portugal. He is also a Senior Researcher at Centro ALGORITMI and a member of both the IE R&D Group and the ESRG R&D Lab. Holding a Ph.D. in Electronics and Computers Engineering, his research focuses on embedded real-time systems, computer architectures, and hardware/software co-design for IoT devices. Academic Degree: Ph.D. in Electronics and Computers Engineering Current Position: Assistant Professor, School of Engineering, University of Minho Gomes has led extensive research in IoT systems over 15 years, particularly in hardware acceleration for automotive LiDAR sensors, secure embedded systems, and efficient OS frameworks for low-end devices. His work includes the EU-funded CROSSCON project and spans hardware-assisted security, dynamic binary translation, and wireless sensor networks. Recent publications highlight his expertise in automotive sensor technology, with articles like FOG-Zip for LiDAR compression, SecureQNN for TinyML security, and Hardware-Assisted Range Image Generation for LiDAR processing. His work bridges IoT, embedded systems, and cybersecurity, focusing on real-time performance and hardware-software co-design. Projects include the development of reliable/secure automotive sensor solutions and EU project CROSSCON. He contributes to open-source frameworks like UTango for IoT security and investigates heterogeneous fault tolerance architectures using Arm/RISC-V processors. Labs: IE R&D Group, ESRG R&D Lab Education: Ph.D. in Electronics and Computers Engineering, Master’s in Telecommunications Engineering (both from University of Minho)

• 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.

Pedro Alexandre Simões dos Santosمشاهده پروفایل

دانشیار

• Machine Learning
• Social Artificial Intelligence
• Game Design
• +۳ مورد دیگر

Pedro Alexandre Simões dos Santos is an Associate Professor at Instituto Superior Técnico, with dual appointments in the Mathematics Department and Computer Science and Engineering Department. His work spans Machine Learning, Social Artificial Intelligence, and Game Design, focusing on convergence analysis of ML algorithms, Social AI, and AI for Games. He actively contributes to game design, both digital and analogic, with a special interest in historical themes. Affiliations: Mathematics Department, Instituto Superior Técnico Computer Science and Engineering Department, Instituto Superior Técnico INESC-ID Research Unit GAIPS - Group of AI for People and Society His research integrates theoretical and applied aspects, including reinforcement learning in non-stationary environments, neural network optimization, and socially intelligent agent authoring tools. He explores AI applications in games, mental health support systems, and legal domains. His recent publications highlight trends in NFT-based game ecosystems, dialogue systems for mental health, and multi-agent reinforcement learning frameworks. Pedro teaches subjects such as Mathematics for Machine Learning and the 1st Cycle Integrative Project in Applied Mathematics and Computing, bridging mathematical foundations with computational applications.

• Signal Processing in Wireless Communications
• Multi-antenna systems (MIMO)
• Wireless Power Transfer
• +۱۴ مورد دیگر

Francisco A. Monteiro is an Associate Professor in the Department of Information Science and Technology at ISCTE – University Institute of Lisbon, and an Integrated Researcher at Instituto de Telecomunicações (IT), Lisbon, Portugal. He holds a PhD in Engineering from the University of Cambridge and prior degrees from Instituto Superior Técnico, University of Lisbon. His academic journey includes progressive roles at ISCTE-IUL, culminating in his promotion to Associate Professor in May 2024. Education: PhD in Engineering, University of Cambridge, UK (2012) MSc in Electrical and Computer Engineering, Instituto Superior Técnico, University of Lisbon (2003) Licenciatura in Electrical and Computer Engineering, Instituto Superior Técnico, University of Lisbon (1998) His research focuses on signal processing in wireless communications, particularly in MIMO systems, network coding, quantum communications, and advanced decoding techniques like GRAND. He has made significant contributions to quantum error correction, entanglement purification, and low-latency decoding for 5G/6G systems. His recent work bridges classical wireless theory with emerging quantum networking paradigms, as evidenced by publications in Quantum , IEEE Access , and IEEE Transactions . The trend in his recent publications (2023–2024) shows a strong shift toward quantum information processing—especially quantum error correction via noise-guessing decoding (QGRAND), entanglement routing, and purification—while maintaining a foundation in classical MIMO, full-duplex communications, and network coding. His work is highly interdisciplinary, combining information theory, signal processing, and quantum computing. Scientific Awards: Best Paper Award, ECWT 2007 Best Student Paper Award, ECWT 2004 Exemplary Reviewer Award (2014, 2015), IEEE Wireless Communications Letters Innovation Young Engineer Prize (3rd place), Ordem dos Engenheiros, 2002 College Senior Scholarship, Fitzwilliam College, Cambridge, 2007 Fellowship from Fundación Endesa & Fundación Carolina, 2019 Francisco Monteiro has advised several MSc students, including Francisco Rosário and João Sande Lemos, both winners of the Luís Vidigal Prize. He has co-supervised PhD-level research and served on multiple thesis committees. His research has been funded through competitive grants and collaborations with institutions in Canada, Finland, Spain, and the UK. He has served as General Chair of ISWCS 2018, Lead Guest Editor for EURASIP Journal, and organizer of the Quantum Internet Alliance Workshop. He is actively involved in research groups such as the Radio Systems Group at IT and has led projects on MIMO, wireless energy transfer, and quantum networking. His lab work emphasizes algorithmic innovation for practical implementations in next-generation wireless and quantum systems.

• High-Performance Computing
• Parallel Computing
• Heterogeneous Computing
• +۷ مورد دیگر

Alberto José Gonçalves Carvalho Proença serves as Full Professor in the Department of Informatics at the School of Engineering, University of Minho, and holds the position of Senior Researcher with Dr. habil at Centro ALGORITMI. His academic career spans over 45 years, beginning at the University of Porto in 1976 before transitioning to the University of Minho in 1977 where he has remained ever since. His educational foundation includes: Licentiate in Electrical Engineering from Coimbra, Portugal (1976) MSc in Digital Electronics from UMIST, Manchester, UK (1979) PhD from Manchester, UK (1982) Dr. habil (Habilitation) from the University of Minho (1998) Professor Proença's research spans from digital electronics to cutting-edge high-performance computing, with core expertise in computer architecture, parallel computing, and heterogeneous computing systems. His work bridges theoretical computer science with practical applications across diverse domains including particle physics (LHC data analysis), forensic science (DNA library systems), materials science (crystallographic imaging), and cultural heritage preservation. Current research focuses on optimizing computational efficiency across heterogeneous resources for scientific applications, addressing challenges in big data processing, parallel random number generation, and scheduling algorithms for distributed environments. Throughout his career, Professor Proença has successfully supervised numerous MSc dissertations and PhD theses while contributing significantly to institutional computing infrastructure. He chaired the University Computer Centre for 17 years (1985-2002), establishing Portugal's first national parallel computing service. For 11 years (2006-2017), he led the Advanced Computing theme in the University of Texas at Austin-Portugal cooperation program. Since 2005, he has directed the university's SeARCH heterogeneous computing cluster, supporting research across multiple scientific disciplines. His research group has developed several influential frameworks including JaSkel (Java Skeleton-Based Framework for Cluster and Grid Computing), HEP-Frame (for LHC data analysis), Im2Cr (crystallographic imaging tool), and CROSS-Fire (risk management decision support system). These platforms demonstrate his commitment to translating theoretical advances into practical tools that address real-world scientific and societal challenges.

• Business Intelligence
• Data Warehousing
• OLAP
• +۷ مورد دیگر

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 Matosمشاهده پروفایل

استادیار

• Persistent Memory
• Blockchain Scalability
• Systems Evaluation
• +۳ مورد دیگر

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.