جست‌وجوی استاد و پژوهشگر

• Compilers
• Automatic Software Verification
• Compiler Optimization
• +۷ مورد دیگر

Nuno Pereira Lopes is an Associate Professor at Instituto Superior Técnico , part of Universidade de Lisboa , and a researcher at INESC-ID . He also serves as an advisor at FuriosaAI , focusing on tensor contraction processors for AI workloads. Research Interests : Compilers, formal verification of LLVM optimizations, machine learning frameworks, undefined behavior exploitation, probabilistic model checking, blockchain security, and many-core code generation. Teaching : Compilers and Computer/Informatics Engineering projects. Funding : Supported by Google, Matter Labs, NLnet, Oracle, PRACE, RNCA, and Woven by Toyota. Recent Publications focus on LLVM backend validation , PyTorch pipeline parallelism , C++ dynamic cast optimization , undefined behavior in C/C++ , and AI tensor processors . His work bridges compiler design, formal methods, and AI hardware. Academic Service includes representing Portugal in ISO/IEC JTC 1/SC 22 (C++), organizing FLoC'26 , and serving on program committees for PLDI, EuroLLVM, and CGO.

Emanuele Borgonovoمشاهده پروفایل

استاد

• Sensitivity Analysis
• Decision Analysis
• Risk Analysis
• +۳ مورد دیگر

Emanuele Borgonovo is a Full Professor and Director of the Department of Decision Sciences at Bocconi University. He serves as a Research Affiliate at MIT's Department of Nuclear Science and Engineering, co-editor-in-chief of the European Journal of Operational Research , and advisor for the Springer International Series in Management Science and Operations Research. His leadership roles include President of the Decision Analysis Society of INFORMS (2020-2022) and Co-Chair of the ESRA Technical Committee on Uncertainty Analysis. Affiliation: Bocconi University Collaboration: MIT, NASA, DARPA, Idaho National Laboratory, EDF His research focuses on Sensitivity Analysis, Decision Analysis, Risk Analysis, and Uncertainty Quantification. He pioneered techniques like the differential importance measure, now adopted in NASA's PRA Guide. Recent work explores explainable AI via Shapley values and optimal transport methods for sensitivity analysis. 2025: Explainable risk assessment modeling 2025: Sensitivity analysis of climate models 2024: AI impact on job markets Scientific honors include: Excellence in Research Award (2020) IBM Faculty Award (2015) Best Risk Analysis Paper Award (2014) Multiple Best Reviewer Awards (2006-2022) At SDA Bocconi, he leads the Artificial Intelligence and Data Science for Executives program and taught in MBA/DBA courses. His work has been supported by grants from US Department of Energy, NASA, and Electricité de France.

• Verification of Secure Systems
• Software Security
• Web Security
• +۵ مورد دیگر

Pedro Adão is an Assistant Professor at the Department of Computer Science and Engineering (DEI) of the Instituto Superior Técnico (IST) , University of Lisbon . He is affiliated with the SQIG - Security and Quantum Information Group at the Institute of Telecommunications , formerly part of CLC - Logic and Computation Centre . His work bridges formal methods and computational cryptography , focusing on security protocols , software security , and quantum information security . PhD in Mathematics (2006, IST) with thesis "Formal Methods for the Analysis of Security Protocols" Graduated in Applied Mathematics and Computation (2002, IST) with thesis "Electronic Money" His research interests include verification of secure systems, composition of secure systems, mathematical foundations of cryptography, and physical/day-life security. His publications span topics like firewall configuration tools , smart contract verification , quantitative protocol analysis , and computationally sound symbolic cryptography . He has collaborated with institutions such as the University of Pennsylvania, Microsoft Research Cambridge, and INRIA-Microsoft Research Paris. Key teaching contributions include courses in Introduction to Algorithms and Data Structures , Computational Models in Security , and Software Security . He is a member of the SQIG research group and has organized the SQIG Information Security Seminar . Past teaching roles include lecturing at the Catholic University of Portugal and the Air Force Academy.

Jose Nuno Oliveiraمشاهده پروفایل

استاد

• Formal Methods
• Programming Algebra
• Functional Programming
• +۳ مورد دیگر

Jose Nuno Oliveira is a Professor at the Department of Informatics of the University of Minho and a researcher at HASLab/INESC TEC. He is a member of the IFIP WG 2.1 (Algorithmic Languages and Calculi) and the Formal Methods Europe (FME) Association. He serves on the editorial board of Springer's Formal Aspects of Computing . His research focuses on formal methods, programming algebra, and functional programming, with recent work on relation algebra and linear programming algebra for software verification. He has supervised multiple theses in areas like quantum programming, probabilistic model verification, and functional programming applications. Key research interests include applying theoretical constructs (e.g., adjunctions, difunctions) to practical software systems. His publications (2022–2024) explore fuzzy logic extensions in Alloy, historical relational program analysis, and foundational programming concepts. He leads efforts in trusted software development through collaborations at INESC TEC.

• Smart Grids
• Energy Communities
• Data Mining Applications in Power Systems
• +۷ مورد دیگر

Sérgio Filipe Carvalho Ramos serves as Coordinator Professor at the School of Engineering (ISEP) of the Polytechnic Institute of Porto (IPP), where he has held academic positions since 2001. Since 2021, he directs the Bachelor Program in Electrical Engineering - Electrical Power Systems and previously served as deputy director of the Electrical Engineering Department (2018-2020). He maintains active research collaborations with international institutions including Universidade de Vigo and Universidade da Coruña in Spain, and UNESP in Brazil. His educational background includes a PhD (2015) and MSc (2006) in Electrical and Computer Engineering from the University of Lisbon - IST. His research focuses on smart grids, energy communities, data mining applications in power systems, and renewable energy optimization . He has pioneered work in smart buildings optimization, shared PV generation, and flexible power contracts through significant R&D projects. The analysis of his recent publications reveals strong trends in energy community modeling , with 8 of the 15 most recent papers addressing peer-to-peer energy sharing, community optimization, and local market design. His work increasingly integrates machine learning for forecasting (particularly for EV integration and PV generation) and employs advanced optimization techniques including game theory and MBNLP methods. The research consistently targets practical implementation in smart grid contexts with emphasis on real-world applicability. Premio REN 2008 Scientific Publication Merit from IPP (2011, 2015, 2023) Ramos has supervised 2 PhD students (ongoing), 29 MSc, 6 ERASMUS, and 116 BSc students. His grant portfolio demonstrates exceptional success in securing competitive funding, including FCT projects BENEFICE and SPET as PI/Co-PI, the EU-funded SATCOMM project coordinating Atlantic energy pilots, and multiple Honda Research Institute consultancies. His research group has successfully coordinated over 20 national and international R&D projects with total funding exceeding €5M. As a core researcher in the GECAD research group, he leads initiatives in smart buildings and energy communities. He serves as General Secretary for IPP at ATHENA European University and participates in the CARPE Network's Sustainable and Smart Cities working group, demonstrating institutional leadership beyond his departmental responsibilities.

José Bacelar Almeidaمشاهده پروفایل

استادیار

• Cryptography
• Information Security
• Program Verification
• +۳ مورد دیگر

José Bacelar Almeida is an Assistant Professor at the Department of Informatics at Universidade do Minho and a Senior Researcher at HASLab/INESC TEC since 2011. He holds a PhD in Computer Science from Universidade do Minho (2003). His research focuses on Cryptography, Information Security, and Program Verification, with an emphasis on formal methods for ensuring cryptographic software correctness and security. He has contributed to high-assurance implementations of cryptographic systems, bridging theoretical security with real-world applications. His research interests include provable security, formal verification of cryptographic proofs, and secure cryptographic software implementations. Notable work includes formally verified implementations of Kyber (a post-quantum cryptosystem) and machine-checked proofs for security protocols like ML-KEM. He also explores leakage-free probabilistic programs and secure compilation frameworks. Almeida has supervised multiple theses on topics such as cryptographic implementation verification, cloud security, and password management systems. His publications span conferences like CRYPTO and CPP, journals like the Journal of Logical and Algebraic Methods in Programming, and venues on formal methods and secure computation. He is part of the High-Assurance Software research center at INESC TEC and actively contributes to projects involving certified cryptographic software and secure multiparty computation. His work emphasizes practical, high-performance solutions with rigorous formal guarantees.

• Cyber-Physical Systems
• Quantum Computing
• Programming Languages
• +۶ مورد دیگر

Renato Jorge Neves is a Senior Researcher at the University of Minho and an Auxiliar Professor affiliated with the High-Assurance Software Centre (INESC TEC) . His research focuses on the foundations of cyber-physical systems, quantum computing, and programming language semantics. He holds a PhD from the MAP-i doctoral program, specializing in logics and calculi for cyber-physical components. His academic contributions span coalgebraic methods, proof theory, and institutional frameworks. He has led and participated in projects such as Ibex (quantitative cyber-physical programming) and CTRL-F (computational effects). He teaches courses on cyber-physical systems, quantum computing, and program calculus at the University of Minho. Neves has supervised multiple theses, including works on quantum language integration (e.g., iQbricks ) and hybrid system simulation. His recent publications explore quantitative lambda-theories, metric-enriched categories, and probabilistic concurrency models. He actively engages in academic service, including invited talks at FACS'22 and contributions to venues like CSL, CONCUR, and TCS.

Ana Vianaمشاهده پروفایل

استاد

• Combinatorial Optimization
• Integer Programming
• Operations Research
• +۵ مورد دیگر

Ana Viana serves as Coordinator Professor at the Polytechnic Institute of Porto, School of Engineering, and as Coordinator Researcher at the Centre for Industrial Engineering and Management of INESC TEC. She has maintained these dual appointments since December 9, 1997, demonstrating sustained commitment to both academic instruction and advanced research in industrial engineering. Her research centers on Combinatorial Optimization, specializing in the development of exact algorithms and meta-heuristic approaches to complex decision problems. Dr. Viana's work bridges theoretical advancements with practical applications in healthcare logistics and transportation systems, where optimization techniques solve real-world challenges in resource allocation and matching problems. Her recent publications reveal a strong trajectory in applying operations research to kidney exchange programs and last-mile delivery optimization. She has pioneered concepts like locally stable exchanges in kidney matching and developed innovative data-driven approaches to crowd-sourced delivery systems. Her work consistently appears in premier journals including European Journal of Operational Research, Mathematics of Operations Research, and Computers & Operations Research. As an academic supervisor, Dr. Viana has guided numerous graduate students through thesis research on photovoltaic systems, production planning in footwear manufacturing, logistics network analysis, and power grid optimization. She has led multiple publicly funded research projects that translate theoretical insights into practical industrial applications.

Mathieu Blondelمشاهده پروفایل

پژوهشگر

• Differentiable Programming
• Machine Learning
• Deep Learning
• +۹ مورد دیگر

Mathieu Blondel is a Researcher at Google DeepMind in Paris, France. He obtained his PhD in Machine Learning from Kobe University in 2013. From 2013 to 2019, he worked at NTT's Communication Science Laboratories in Kyoto, Japan. Research Interests: Differentiable programming Language models and deep learning Loss functions for structured prediction Optimization algorithms Optimal transport theory Polynomial networks Machine learning software Scientific Awards: Open-science honorable mention at ECML PKDD 2013 Software Contributions: Mathieu is a core contributor to scikit-learn , a foundational Python library for machine learning. He also maintains open-source projects on differentiable sorting, optimal transport, and Fenchel-Young losses.

Andreia Mordidoمشاهده پروفایل

استادیار

• Programming Languages
• Type Systems
• Logic
• +۲ مورد دیگر

Andreia Mordido serves as an Assistant Professor in the Department of Informatics at the Faculty of Sciences, University of Lisbon, and is an integrated researcher at LASIGE. She previously conducted research as a visiting scholar at Carnegie Mellon University's Principles of Programming (PoP) group during Fall 2019. Her academic credentials include: Ph.D. in Information Security (2017), Instituto Superior Técnico, University of Lisbon M.Sc. in Mathematics and Applications (2011), Instituto Superior Técnico, University of Lisbon B.Sc. in Mathematics (2009), Faculty of Sciences and Technology, New University of Lisbon Her research centers on programming languages and type systems for specifying and verifying communication protocols, with earlier contributions to probabilistic/equational logics for cryptographic protocol security and probabilistic satisfiability solvers. Primary interests span Programming Languages, Type Systems, Logic, Satisfiability Problems, and Probabilistic and Equational Reasoning. Analysis of her 15 most recent publications reveals a concentrated research trajectory in session types and protocol verification, with increasing sophistication in handling nested protocols, context-free session types, and higher-order abstractions. Her work bridges theoretical foundations in type theory with practical applications in concurrent and distributed systems, particularly evident in blockchain and smart contract domains. Scientific recognition includes: Distinguished Paper Award at POPL 2024 for "Parametric Subtyping for Structural Parametric Polymorphism" Dr. Mordido has secured involvement in multiple research initiatives: SafeSessions: Safe Concurrent Programming with Session Types Confident: Communication contracts for distributed systems development ASGARD: Analysis system for gathered raw data ECOSSIAN: European Control System Security Incident Analysis Network ComFormCrypt: Computational Semantics of Formal Methods in Cryptography Co-evolution and self-organization of cooperation Her teaching portfolio spans Domain-Specific Languages, Object Oriented Development, Introduction to Programming, and Theory of Computation across Faculty of Sciences (2018-present) and Instituto Superior Técnico (2012-2016), demonstrating consistent engagement with both theoretical and applied computer science education. As an LASIGE researcher, she contributes to Portugal's premier software engineering research laboratory focused on advanced computing solutions and formal methods.

José António Crispimمشاهده پروفایل

استاد

• Operations Research
• Risk Management
• Healthcare Systems Engineering
• +۳ مورد دیگر

José António Crispim is a Professor at the School of Engineering, University of Minho, specializing in Industrial Engineering. Holding a Ph.D. in Engineering and Industrial Management from the University of Porto, he maintains an active research profile with significant contributions across operations research, healthcare systems, and sustainable development. His research spans critical domains including: Risk management frameworks for military shipbuilding and clinical laboratories Performance measurement systems in public sector and healthcare Sustainable supply chain networks aligned with UN SDGs Telemedicine equity and patient-centered care models Virtual enterprise formation and dynamic manufacturing networks His work demonstrates strong interdisciplinary focus, bridging engineering methodologies with real-world healthcare and sustainability challenges. Recent publications (2020-2024) show increasing emphasis on healthcare applications and SDG implementation through collaborative networks. Crispim leads and participates in significant research projects including vehicle routing optimization funded from 2010-2013. His teaching portfolio covers advanced data analysis, production management, and operational research across doctoral, master's, and undergraduate programs at University of Minho.

Igor Sedlárمشاهده پروفایل

پژوهشگر

• Modal Logic
• Non-Classical Logic
• Dynamic Logics
• +۵ مورد دیگر

Igor Sedlár is a researcher at the Czech Academy of Sciences (CAS) in Prague, affiliated with the Institute of Computer Science (ICS CAS) in the Department of Theoretical Computer Science, where he is part of the LogICS group. He holds a part-time position in the Department of Logic at the CAS Institute of Philosophy. His work primarily focuses on modal and non-classical logics, dynamic logics, and their applications in modeling information dynamics. He has led projects such as the Czech-Taiwanese KATRA project (2025-2027) and the Czech Science Foundation-funded GRADLACT project (2022-2024). Sedlár teaches courses in dynamic logic and non-classical reasoning at Charles University and Czech Technical University. He serves as deputy head of the Department of Theoretical Computer Science at ICS CAS and on program committees for conferences like Logica, DaLí, and AiML. His research interests include epistemic logic, temporal logic, and the formal analysis of reasoning systems.

• Geostatistics
• Spatial Epidemiology
• Environmental Health
• +۴ مورد دیگر

Manuel Ribeiro serves as an Invited Assistant Professor in the Department of Mineral and Energy Resources Engineering at the School of Engineering, University of Lisbon, where he teaches Sampling and Environmental Analysis Methods, Multivariate Analysis of Regionalized Data, and Statistical Learning for Earth and Environmental Engineering. Affiliated with the CERENA research unit, his academic role bridges engineering and environmental health sciences through spatial statistics applications. His research program centers on geostatistical methodologies for environmental epidemiology, with pioneering work on lichen-based air quality indicators and spatial uncertainty quantification in health exposure studies. Core interests include multivariate geostatistics for ecological associations, spatiotemporal disease modeling, and high-resolution environmental risk mapping, particularly examining air pollution's impact on birth outcomes and pandemic dynamics. Analysis of his 15 most recent publications reveals a dominant focus on applying geostatistical simulation to public health crises (notably COVID-19) and environmental health questions. His work consistently integrates R-based open-source tools, with significant contributions to uncertainty visualization in disease mapping and agricultural resource management. The research demonstrates strong regional emphasis on Portuguese case studies while developing transferable methodological frameworks for spatial epidemiology. No scientific awards were documented in the source materials. As part of CERENA's research ecosystem, Ribeiro collaborates extensively on interdisciplinary projects involving environmental monitoring and health impact assessment, though specific advising roles or grant details were not provided in the source texts. His methodological innovations in spatial statistics directly support CERENA's mission in earth resources and environmental sustainability.

Minhyuk Sungمشاهده پروفایل

دانشیار

• Computer Vision
• Machine Learning
• Generative AI
• +۳ مورد دیگر

Minhyuk Sung is an Associate Professor in the School of Computing at KAIST, where he leads the KAIST Visual AI Group. He is also affiliated with the Graduate School of AI and the Metaverse Program. Previously, he worked as a research scientist at Adobe Research. He received his Ph.D. from Stanford University under the supervision of Leonidas Guibas and completed his M.S. and B.S. degrees at KAIST. Dr. Sung's research focuses on generating, manipulating, and analyzing various visual data, including images, videos, and 3D data. His work primarily centers around diffusion models, flow models, and other generative AI techniques applied to visual content. He has made significant contributions to the fields of 3D vision, text-to-image generation, and multi-modal AI systems. His recent publications demonstrate a strong trend toward improving the quality, efficiency, and controllability of generative models, with particular emphasis on 3D-aware generation, synchronization techniques, and grounding visual content with linguistic descriptions. His work spans multiple top-tier conferences including NeurIPS, CVPR, ICCV, and SIGGRAPH. Asiapgraphics Researcher Award (2024) Dr. Sung actively mentors students and recruits new members for his research group. He serves as an area chair for conferences like 3DV 2026 and frequently gives talks at major institutions including NVIDIA, Google, Stanford, and various universities across Asia. His research has attracted significant attention in both academic and industrial circles. He teaches advanced courses including Diffusion and Flow Models (CS492(C)), Machine Learning for 3D Data (CS479), and Diffusion Models and Their Applications (CS492(D)), demonstrating his commitment to training the next generation of AI researchers.

• Concrete Durability
• Sustainable Concrete
• Recycled Aggregate Concrete
• +۳ مورد دیگر

Rui Duarte Neves serves as a Professor in the Department of Civil Engineering at the School of Technology of Barreiro, Polytechnic Institute of Setúbal, Portugal. Previously, he conducted research at the National Laboratory for Civil Engineering (LNEC-Portugal), establishing his expertise in concrete technology and structural assessment before transitioning to his current academic role. His research specializes in concrete durability and sustainable construction materials, with primary focus on service life prediction of reinforced concrete structures and development of eco-friendly alternatives like recycled aggregate concrete. He pioneers non-destructive testing methodologies for on-site evaluation of carbonation and chloride penetration, directly addressing infrastructure longevity challenges in aggressive environments. Analysis of his publication portfolio reveals consistent innovation in sustainable concrete technologies, particularly CO 2 sequestration in recycled concrete and AI-driven predictive modeling for carbonation coefficients. His work bridges experimental validation with computational approaches, including genetic programming and tree-based algorithms, while advancing circular economy principles through industrial waste reuse in cement production. Dr. Neves actively contributes to the Resilience R&D Unit, where his research integrates field testing, statistical modeling, and materials innovation to enhance concrete performance under environmental stressors like carbonation and chloride exposure.