جستجوی استاد راهنمای دانشگاهی

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).

Rute C. Sofiaمشاهده پروفایل

دانشیار

• Internet of Things
• Edge computing
• Network architectures and protocols
• +۱۰ مورد دیگر

Rute C. Sofia is Industrial IoT Head at fortiss – the Bavarian research institute for software-intensive systems – and Invited Associate Professor at Universidade Lusófona de Humanidades e Tecnologias (ULHT). She is also an Associate Researcher at ISTAR, Instituto Universitário de Lisboa (Iscte-IUL). Previously she co-founded and served as Scientific Director of COPELABS/ULHT (2013-2017) and was Senior Researcher there from 2010-2019. Education Ph.D. in Computer Science, University of Lisbon, 2004 Visiting Scholar, Northwestern University (ICAIR) & University of Pennsylvania, 2000–2003 M.Sc. in Computer Science, University of Lisbon, 1999 B.Eng. in Computer Engineering, University of Coimbra, 1995 Research Interests Her work spans network architectures and protocols , Internet of Things (IoT) , edge and in-network computing , deterministic wired/wireless industrial networks , and network mining . A current focus is on resilient, AI-driven orchestration across the IoT–Edge–Cloud continuum for 6G and Industrial IoT systems. Scientific Awards & Recognition ACM Europe Councilor (2021–2025) ACM Senior Member & IEEE Senior Member IEEE ComSoc N2Women Awards co-chair (2020–2021) Highly Cited Paper Award, Applied Sciences MDPI (2023) Labs, Teams & Grants She currently leads the Industrial IoT competence field at fortiss, coordinating projects such as SemComIIoT (semantic communications for IIoT) and the open-source ns-3 DetNetWiFi framework. Earlier she co-founded the Portuguese startup Senception Lda (2013-2019) and the research unit COPELABS , driving EU H2020 initiatives like UMOBILE and shaping national strategies for cyber-physical systems.

João Magalhãesمشاهده پروفایل

استاد

• Vision and Language Understanding
• Multimodal Information Understanding
• Multimodal Conversational AI
• +۵ مورد دیگر

João Magalhães is a Full Professor in the Department of Computer Science at the Faculty of Science and Technology, Universidade NOVA de Lisboa, Portugal. He serves as Group Coordinator of the Multimodal Systems Group at the NOVA Laboratory for Informatics and Computer Science and leads the NOVASearch research group at FCT/UNL. His research focuses on vision and language information understanding, with particular emphasis on multimodal information understanding, multimodal conversational AI, multimedia search and summarization, temporal and memory models, and social media information quality. His work spans both theoretical foundations and practical applications across web, social media, and clinical domains. Analysis of his recent publications reveals a strong trajectory in multimodal conversational AI systems, with increasing sophistication in handling both voice and visual inputs. His research has evolved from foundational work in cross-modal embeddings to advanced large language models for dual-goal conversational settings, demonstrating consistent innovation in the field of multimodal understanding. 1st prize winner of the second Alexa TaskBot Challenge (2023) Award-winning solution in the Alexa TaskBot Challenge (2022) Best paper award at the Portuguese NLP conference (PROPOR) (2020) Best paper nominations at ACM conferences (2018) Professor Magalhães has advised numerous graduate students through the NOVASearch group and has secured substantial research funding through projects including Amazon Alexa TaskBot Challenge (2021-2023), iFetch (2020-2023), SmartyFlow (2017-2020), COGNITUS (2016-2019), GoLocal (2016-2020), QSearch (2012-2015), ImTV (2010-2013), and CS4SE (2010-2013). He actively serves the research community as ACM Multimedia 2026 Program Committee Chair and has held leadership roles in numerous conferences including ACM Multimedia 2022 General Chair and ECIR2020 General Chair. He leads the Multimodal Systems Group within the NOVA Laboratory for Informatics and Computer Science, where his team develops cutting-edge solutions for multimodal understanding with applications in conversational AI, multimedia search, and social media analysis.

Jan Theeuwesمشاهده پروفایل

استاد

• Visual Attention
• Perception
• Statistical Learning
• +۷ مورد دیگر

Jan Theeuwes is a full Professor and current Head of Department at Vrije Universiteit Amsterdam's Department of Cognitive Psychology. With over 250 peer-reviewed publications, he leads research in visual attention, statistical learning, and distractor suppression mechanisms. His work bridges fundamental cognitive science with practical applications in road design and human factors. His educational background includes: BSc in Mechanical Engineering (1981) BSc and MSc in Experimental Psychology with highest honors (cum laude) from Tilburg University (1987) PhD from Vrije Universiteit with highest honors (1992) Theeuwes' research focuses on fundamental knowledge acquisition regarding perception, attention, memory, and emotion using diverse methodologies including behavioral measurements, eye tracking, fMRI, psychophysiological recordings, patient studies, and computational modeling. His specific contributions span attentional and oculomotor capture, working memory, multimodal integration, remapping, face perception, visual search, emotion processing, unconscious processing, the attentional blink, reward processing, and applied road design research. His recent work demonstrates how statistical learning shapes attentional selection by creating predictive models of where and when to expect relevant information. Analysis of his recent publications reveals a strong focus on the neural and behavioral mechanisms of learned distractor suppression, with particular emphasis on how statistical regularities in the environment shape attentional priority maps. His research increasingly integrates electrophysiological methods with behavioral paradigms to uncover the temporal dynamics of attentional selection and suppression processes. His notable scientific achievements include: Election to the Royal Dutch Academy of Science (KNAW) in 2010 Receiving the first Bertelson Award for outstanding psychological research from the European Society for Cognitive Psychology in 2001 Serving as president of ESCOP (European Society for Cognitive Psychology) from 2016 to 2018 Theeuwes serves as principal advisor to the Dutch Department of Transportation (Rijkswaterstaat) regarding road design and signing. In 2023, he co-founded Attention Architects with two former PhD students, a company applying eye-tracking research to practical settings. His work has received substantial research funding supporting his investigations into attentional mechanisms and their real-world applications. Theeuwes has established collaborations across multiple institutions and mentored numerous researchers who have gone on to establish their own careers in cognitive science. He leads the Cognition Team at Vrije Universiteit Amsterdam, which investigates fundamental attentional processes using cutting-edge methodologies. The team maintains strong connections with applied research settings through projects with government agencies and industry partners, particularly in transportation safety. Their current work focuses on how statistical learning dynamically shapes attentional selection in complex visual environments.

João Moura Piresمشاهده پروفایل

دانشیار

• Computer Science
• Cybersecurity
• Artificial Intelligence

João Moura Pires is an Associate Professor at the Department of Informatics , NOVA School of Science and Technology , Universidade Nova de Lisboa. He is affiliated with FCT/UNL and contributes to academic and research initiatives in computer science and cybersecurity domains. His work aligns with the department's focus on cutting-edge research in areas like artificial intelligence, cryptography, and trusted AI systems, as evidenced by the department’s involvement in projects such as the Amazon Nova AI Challenge and CertiCoLab. Contact: jmp@fct.unl.pt

Chrysoula Zervaمشاهده پروفایل

استادیار

• Machine Learning
• Natural Language Processing
• Uncertainty Quantification
• +۵ مورد دیگر

Chrysoula Zerva is an Invited Assistant Professor in the Department of Electrical and Computer Engineering at Instituto Superior Técnico and a post-doc researcher in the SARDINE group at the Instituto de Telecomunicações. She holds a PhD from the University of Manchester (2019) and was awarded the EPSRC Doctoral Prize Fellowship for the “Fake Health News” project. Her research focuses on uncertainty quantification, fairness, explainability in NLP, and machine translation evaluation. Key interests include adversarial attacks, bias mitigation, and disentangled representation learning. Dr. Zerva’s work spans conformal prediction frameworks, dialect bias in reward models, and response clarity classification. Her contributions to MT evaluation and quality estimation have been highlighted in WMT shared tasks. Recent studies address ethical AI challenges, such as the societal impacts of LLMs and biases against African American language. Scientific Awards: EPSRC Doctoral Prize Fellowship Labs/Teams: Member of the SARDINE research group Her publications investigate cutting-edge topics like CLIPScore metrics, non-exchangeable conformal methods, and context-aware NMT for business dialogues. Collaborations include Unbabel and participation in international shared tasks.

• Wireless Sensor Networks
• Cyber-Physical Systems
• Network Protocols
• +۳ مورد دیگر

John Harrison Kurunathan is an Integrated PhD Researcher affiliated with the CISTER Research Centre at the University of Porto, Portugal. He holds a PhD in Electrical and Computer Engineering (2021), a Master's in Very Large-Scale Integration (2014), and a Bachelor's in Electronics and Communication (2012). Education: PhD (2021) - University of Porto, Portugal MSc (2014) - SSN College of Engineering, Anna University BSc (2012) - SRM University His research focuses on Wireless Sensor Networks (WSNs) , Cyber-Physical Systems (CPS) , and Automotive Networks , with an emphasis on Quality-of-Service (QoS) optimization, secure communication, and vehicular platooning. Notable projects include SafeCOP for safety-related CO-CPS and work on IEEE 802.15.4e DSME networks. Recent publications (2023-2025) span areas like Visible Light Communication , Vehicular Security , and Machine Learning in UAV Operations , reflecting his interdisciplinary work bridging embedded systems and transportation technologies. Scientific Awards: Best oral communication Award (in ex aequo) at DCE 2019 Reviewing Roles: Conference: ICCPS, EWSN, MSN, RTN Journal: IEEE ACCESS, IEEE Transactions on Vehicular Technology, ACM Sigbed Harrison is actively involved in workshops and conferences, including chairing roles at WIN-WIN-4S 2024 and technical demonstrations at WoWMoM 2023. His work appears in venues like IEEE Transactions on ITS, IEEE COMST, and PDP 2025.

Johan Ekerمشاهده پروفایل

استاد مدعو

• Control Theory
• Machine Learning
• Cloud Computing
• +۵ مورد دیگر

Johan Eker is an Adjunct Professor at Lund University and Principal Researcher at Ericsson. He works at the intersection of computer science and control theory, focusing on control of large-scale compute systems, machine learning, and networked control systems. His research includes optimizing cloud deployments, virtualized network functions, and edge computing for industrial applications. He collaborates closely with Ericsson to leverage real-world data and infrastructure. Education & Affiliations: Affiliated with the Department of Automatic Control at Lund University and Ericsson Research. Active in teaching and supervising projects related to systems engineering, machine learning, and control theory. Research Interests: Large-scale systems, control of interconnected systems, distributed control, and applications in industrial IoT and autonomous systems. His work emphasizes scalability and real-time adaptation in complex computing environments. Grants & Collaborations: Involved in projects like WASP (Wallenberg AI, Autonomous Systems Program) and ELLIIT (Excellence Center in Information Technology). Collaborates with Ericsson on cloud computing resource management and network dynamics. Labs & Teams: Engaged with the RobotLab LTH and initiatives like the Nordic University Hub on Industrial Internet of Things (HI2OT). His research bridges academic theory with industrial applications in autonomous systems and cloud optimization.

• Signal Processing
• Image Processing
• Smart Environments
• +۶ مورد دیگر

Manuel Reis is an Associate Professor with Agregação at the University of Trás-os-Montes e Alto Douro (UTAD), Portugal, in the Electrical Engineering Department. His research focuses on signal/image processing, smart environment systems, and multimedia education technologies. He is affiliated with the Institute of Electronics and Telematics Engineering of Aveiro (IEETA) and collaborates with Brazil's IFPA-Santarém in computing education research. Education: Bachelor's in Electrical Engineering (University of Trás-os-Montes e Alto Douro, 1991) Master's in Electronics and Telecommunications (University of Aveiro, 1996) PhD in Electrical Engineering (University of Aveiro, 2001) Research Interests: Signal & Image Processing Cybersecurity for IoT and Smart Environments Education Technology (e-learning, multimedia tools) 5G and Edge Computing Applications Artificial Intelligence in Agriculture and Healthcare Recent articles highlight his work on cybersecurity in connected vehicles, federated learning for IoT security, and IoT-based systems for drowsiness detection. He has contributed to projects involving smart city infrastructure, sustainable waste management, and low-cost biomedical devices. His educational research explores e-learning frameworks, student engagement metrics, and innovative teaching methodologies in engineering education. Lab/Affiliations: Institute of Electronics and Telematics Engineering of Aveiro (IEETA) Multidisciplinary Research Group IFPA-Santarém-Brazil (Computing in Education)

• Robot Vision
• Robot Navigation
• Computer Vision
• +۷ مورد دیگر

Helder Araujo is a Professor at the Department of Electrical and Computer Engineering, University of Coimbra. His research focuses on Robot Vision , Computer Vision , and Medical Imaging , with applications in Capsule Endoscopy , Autonomous Driving , and Sensor Fusion . Recent publications highlight advancements in 3D Object Detection using transformer networks (e.g., RetSeg3D , DDet3D ), Medical Robotics (e.g., Self-supervised monocular pose estimation ), and Federated Learning (e.g., FAIR-FATE ). Key subfields include Transformer Models , Deep Learning , and Autonomous Navigation . His projects span Medical Imaging (e.g., Multi-Cam Capsule Endoscopy ), Autonomous Robotics (e.g., Learning to Navigate Endoscopic Capsule Robots ), and Edge Computing (e.g., Benchmarking CNN Inference on Low-Power Devices ). Grants include funding from Fundação para a Ciência e a Tecnologia (e.g., PTDC/EEI-ROB/1155/2020) and the European Commission (e.g., AdvanCed Hardware/Software Components for Embedded Vision). He has served as an invited researcher at Université Blaise Pascal (2012–2014). Peer review activities cover journals like IEEE Transactions on Pattern Analysis and Machine Intelligence and Autonomous Robots . His work bridges Medical Imaging , Autonomous Systems , and AI Fairness .

• Embedded Systems
• Internet of Things
• Wireless Sensor Networks
• +۵ مورد دیگر

João Luís Marques Pereira Monteiro is a Full Professor at the Department of Industrial Electronics, School of Engineering, University of Minho, Portugal. He has been with the university since 1980, progressing from Assistant Trainee to his current position. He has held significant leadership roles including Pro-rector (2005-2009), Director of the Algoritmi Center (1998-2006, 2010-2013), and Dean of the School of Engineering (2013-2019). He currently coordinates the Embedded Systems Research Group (ESRG) and is a Senior Researcher at the Algoritmi Research Center. His educational background includes: Bachelor's degree in Electrical Engineering and Computers from the University of Porto (1980) PhD in Informatics and Systems Engineering - specialization in Computer Engineering - from the University of Minho (1991) Habilitation (Dr habil) from the University of Minho (2003) Professor Monteiro's research spans multiple domains in engineering and computer science, with a strong focus on practical applications. His work in embedded systems has led to innovations in real-time processing, sensor networks, and hardware-software co-design. In medical applications, he has developed textile-based sensors for vital sign monitoring. His recent work focuses on computer vision for autonomous vehicles, particularly 3D object detection from point clouds. He also contributes to educational initiatives in data science and AI, particularly in developing countries. His recent publications show a clear progression toward applications requiring real-time processing on resource-constrained devices. There's a strong emphasis on autonomous systems, particularly self-driving vehicles, with multiple papers on 3D object detection from point clouds. His work bridges embedded systems, computer vision, and wireless communications, often focusing on practical implementations for real-world applications like emergency responder localization and medical monitoring. Professor Monteiro has supervised more than a dozen doctoral students, many of whom have gone on to become faculty members at national and international universities. His research has been supported by various funding agencies including FCT (Portuguese), ADI (Portuguese), and FP7 (European funding), as well as industry partners. He leads the Embedded Systems Research Group (ESRG), which is part of the Algoritmi Research Center. The ESRG focuses on developing embedded solutions for various applications including autonomous vehicles, medical devices, and industrial monitoring systems. The group works on both hardware and software aspects of embedded systems, with particular expertise in real-time processing and resource-constrained environments.

• 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)

• Artificial Intelligence
• Distributed Computing
• Energy Communities
• +۳ مورد دیگر

Rafael Duarte Pereira da Silva is a Research Fellow at the Research Group on Engineering and Intelligent Computing for Innovation and Development (GECAD) within the School of Engineering of the Polytechnic Institute of Porto. He is currently pursuing his doctoral degree in Artificial Intelligence and Intelligent Systems Engineering while developing AI-driven solutions for energy communities and smart buildings. His academic background includes: Master's degree in Artificial Intelligence Engineering (2025) from the Polytechnic Institute of Porto, with a dissertation on "Distributed Intelligent Management of Citizen Communities" (grade: 19/20). Bachelor's degree in Computer Engineering (2022) from the Polytechnic Institute of Porto, featuring a green computing project for smart building energy management. Currently enrolled in a doctoral program in Artificial Intelligence and Intelligent Systems Engineering (since 2025). Rafael's research spans Artificial Intelligence, Distributed Computing, and Energy Communities, focusing on human-centric intelligent systems for resource optimization. He develops virtual energy communities using IoT devices and AI models to enable dynamic interaction with community members while managing distributed resources. His work emphasizes sustainability through green computing principles and integration of renewable energy sources in smart infrastructure. His 2024-2025 publications reveal a cohesive research trajectory centered on the Caravels framework for decentralized energy management. Key themes include container-based infrastructure for community resource sharing, peer-to-peer energy trading with storage optimization, and AI-driven demand response systems. His work bridges theoretical AI models with practical IoT implementations, particularly in energy forecasting and HVAC control, demonstrating significant contributions to sustainable consumption in smart buildings and community-scale energy systems. Advising Co-supervised three undergraduate thesis projects at the Polytechnic Institute of Porto on IoT notification systems, Linux-based single-board computer configuration, and open-source IoT devices for smart buildings. Grants and Projects Sa4CPS: Secure situational awareness for critical cyber-physical systems (COMPETE2030-FEDER and ITEA) NGS: New Generation Storage (PRR initiative) TIoCPS: Trustworthy and Smart Communities of Cyber-Physical Systems (P2020 and ITEA programs) As an active GECAD member, Rafael contributes to server infrastructure management and organizes scientific events, including public demonstrations that secured the group's "Excellent" FCT evaluation rating. He has coordinated annual team energizing events for two consecutive years and participated in developing virtual energy community systems that showcase GECAD's research impact in distributed computing and IoT integration.

Jingen Zhouمشاهده پروفایل

استادیار

• Supply Chain Risk Management
• Cruise Industry
• Collision Avoidance Technology
• +۵ مورد دیگر

Jingen Zhou serves as an Assistant Professor in the Department of Operations, Supply Chain and Information Management at KEDGE Business School, bringing international expertise from academic and professional experiences across the United States, Japan, China, and Australia. His doctoral research at the Australian Maritime College (University of Tasmania) established his specialization in maritime supply chain systems. Dr. Zhou's scholarly foundation includes a PhD in Management Science and Commerce with explicit focus on Maritime Supply Chain, reflecting his deep engagement with global maritime systems. His research portfolio demonstrates consistent thematic alignment with operational challenges in maritime contexts. His primary research thrust centers on maritime supply chain risk management, where he integrates collision avoidance technologies, ship AIS data analytics, and climate change risk assessment. This work frequently examines cruise industry dynamics through empirical studies in Shanghai and China, addressing pandemic impacts and supply chain resilience. His methodological approach combines Bayesian networks, deep learning, and complex network analysis to solve real-world navigation and logistics problems in coastal and riverine environments. Recent publications reveal a clear trajectory toward data-driven maritime solutions, with 14 articles published between 2023-2025 spanning marine traffic prediction, cruise network analysis, and multimodal hub optimization. His work consistently employs empirical methodologies focused on Asian maritime contexts, particularly China's evolving port and cruise ecosystems, while leveraging cutting-edge computational techniques for risk assessment. Dr. Zhou actively contributes to academic discourse as a reviewer for multiple journals and maintains collaborative research ties with industry partners and international scholars. His pre-KEDGE research involvement in Australian and Chinese projects demonstrates sustained engagement with maritime logistics challenges across different regulatory and operational environments.

• 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.