جست‌وجوی استاد و پژوهشگر

Sebastian Padóمشاهده پروفایل

استاد

• Computational Linguistics
• Natural Language Processing
• Computational Social Science
• +۳ مورد دیگر

Sebastian Padó is a Professor of Computational Linguistics and Chair of Theoretical Computational Linguistics at the University of Stuttgart's Institute for Natural Language Processing (IMS). He leads the research group focusing on developing methods and software to enable computers to understand language meaning, with expertise in computational semantics, digital humanities, and computational social science. His work bridges linguistic theory and practical NLP applications, including political discourse analysis and model interpretability. Research Interests: Meaning representations, cross-lingual models, derivational morphology, computational social science, fairness in NLP. Affiliations: Institute for Natural Language Processing (IMS), University of Stuttgart; Faculty 05. His research spans developing semantic frameworks, analyzing political discourse networks, and exploring historical texts. Recent work includes computational analysis of character archetypes in Spanish literature and cross-lingual evaluations of political opinions in LLMs. Publications (2025 focus): 15+ articles on topics ranging from computational literary studies to machine learning in low-resource settings. No scientific awards explicitly listed, but contributions to key conferences like ACL and EMNLP are notable. Advising/Grants: Active in guiding research projects and collaborating on interdisciplinary initiatives, though specific grant details are not provided here. Labs/Teams: Theoretical Computational Linguistics group at IMS, focusing on semantic analysis and NLP applications in social sciences.

Rubén Cuevas Rumínمشاهده پروفایل

دانشیار

• Online Advertising
• Web Transparency
• Data Privacy
• +۵ مورد دیگر

Rubén Cuevas Rumín is an Associate Professor in the Department of Telematics Engineering at Universidad Carlos III de Madrid (UC3M), where he also serves as Deputy Director of the UC3M-Santander Big Data Institute (IBiDat). He holds a PhD and MSc in Telematics Engineering from UC3M (2010, 2007), an MSc in Telecommunications Engineering from UC3M (2005), and an MSc in Network Planning and Management from Aalborg University (2006). His research focuses on Online Advertising, Web Transparency, Privacy, Internet Measurements, and their applications in economics and sociology. Notable contributions include studies on Facebook's use of sensitive data, BitTorrent ecosystem analysis, and measurement of cultural aspects through large-scale data. Rubén has authored over 70 publications in top venues like ACM CoNEXT, WWW, Usenix Security, and IEEE/ACM Transactions. He leads or co-leads 16 research projects funded by EU H2020/FP7, Spanish government, and private entities. His work has been featured in major media including BBC, The Financial Times, and Nature. Awarded the Telefonica Foundation Prize for Best PhD Thesis (2010) and the 2018 Emilio Aced Research Prize for data protection research, he teaches courses in Telecommunications, Telematics, and Computer Science. Current projects include the EU-funded TESTABLE and SMOOTH initiatives, focusing on web security and GDPR compliance.

Ivan Vidalمشاهده پروفایل

دانشیار

• Network Functions Virtualization (NFV)
• 5G networks
• Unmanned Aerial Systems (UAS)
• +۳ مورد دیگر

Ivan Vidal is an Associate Professor at Universidad Carlos III de Madrid, affiliated with the Department of Telematics Engineering at Escuela Politécnica Superior. He holds a Telecommunication Engineering degree from the University of Vigo (2001) and a Ph.D. in Telematics Engineering from Universidad Carlos III de Madrid (2008). His career includes roles as Teaching Assistant (2002–2008) and Visiting Professor (2008–2022) before his current position. Research focuses on Network Functions Virtualization (NFV), 5G networks, unmanned aerial systems, network security, Information-Centric Networking (ICN), and multimedia networking. He leads projects like H2020 FISHY (cyber resilient supply chains) and H2020 LABYRINTH (drone traffic management), and co-leads the national project TRUE5G (self-managed 5G networks). His work involves collaborations with institutions like Telefónica I+D and the Instituto de Telecomunicações (Portugal). Teaching includes courses on Audiovisual Services across three undergraduate programs. He contributes to the NETCOM research group, managing projects like the L2S-M open-source Kubernetes networking solution. Ongoing initiatives emphasize multi-site NFV testbeds and 5G vertical services integration.

Iacopo Tirelliمشاهده پروفایل

پژوهشگر ارشد

• Fluid Dynamics
• Optical Measurement Techniques
• Particle Image Velocimetry
• +۳ مورد دیگر

Iacopo Tirelli is an Italian researcher at Universidad Carlos III de Madrid (UC3M) specializing in advanced fluid dynamics diagnostics. Awarded a prestigious ERC Starting Grant in 2020 for his NEXTFLOW project, he develops innovative data-driven approaches to overcome limitations in optical measurement techniques. His research focuses on enhancing Particle Image Velocimetry (PIV) through machine learning algorithms, specifically developing super-resolution methods to surpass the Nyquist limit set by interparticle spacing. This work enables investigation of turbulent flows at previously unattainable scales, with significant implications for aerospace engineering and industrial fluid dynamics applications. Dr. Tirelli completed his doctoral research on 'Data-driven enhancement of optical measurement techniques' under supervisors Stefano Discetti and Andrea Ianiro at UC3M. He further expanded his expertise through a research stay at the Von Karman Institute for Fluid Dynamics (January-April 2023) in the Environmental and Applied Fluid Dynamics group with host Miguel Alfonso Mendez. ERC Starting Grant 2020: 949085 for NEXTFLOW – Next-generation flow diagnostics for control Actively engaged in the academic community, Dr. Tirelli has participated in Aerospace Engineering Doctoral Meetings at UC3M from 2020-2024, contributing to the development of next-generation diagnostic tools that bridge traditional fluid mechanics with modern data science methodologies.

• Explainable AI
• Uncertainty quantification in AI
• Data-Driven modelling of dynamical systems
• +۳ مورد دیگر

Sikha Okkath Krishnanunni is a Postdoctoral Researcher at the Department of Engineering SIMBIOSYS, Universitat Pompeu Fabra (Barcelona), specializing in Explainable AI and uncertainty quantification for medical imaging. Previously, she served as an Assistant Professor (Senior Grade) at Amrita School of Computing (2013-2023), where she contributed to AI curricula development and interdisciplinary research in precision agriculture and healthcare. Educations: Bachelor of Technology in IT, Calicut University (2011) Master’s in Computational Engineering & Networking, Amrita Vishwa Vidyapeetham (2013, Gold Medal) Ph.D. in Engineering, Amrita School of Engineering (2020) Research Interests: Her work focuses on interpretable AI solutions for medical imaging, including GAN-based image synthesis and uncertainty quantification in deep learning. She pioneered frameworks like VMD-DMD and MRDMD for salient region detection in images during her doctoral research. Grants & Collaborations: Secured national/international grants for machine learning projects and collaborated with Sant Joan de Déu Hospital on medical AI applications. Co-organized the CURVAS challenge at MICCAI 2024. Labs/Teams: Active in BCN MedTech, contributing to abdominal cancer analysis through AI-driven medical imaging solutions.

• Multiscale Modeling
• Mechano-transport Simulations
• Patient-Specific Modeling
• +۵ مورد دیگر

Carlos Ruiz Wills is an Assistant Professor at the Department of Information and Communication Technologies (UPF), leading the Motion Lab. His work focuses on multiscale biomechanical modeling, mechano-transport simulations, and patient-specific analyses. He earned a PhD in Material Science and Engineering from UPC (2015) and has contributed to projects like MySpine-FP7, BioDXA, and ANDAMIO. Awards include the 2017 Spanish Chapter Award at the European Society of Biomechanics (ESB) Congress. Education: Bachelor’s in Mechanical Engineering (2005), Universidad Nacional Experimental Politécnica, Venezuela. Master’s in Material Science and Engineering (2010), UPC, Spain. PhD in Material Science and Engineering (2015), UPC, Spain. Research interests include: Multiscale modeling of bone and intervertebral discs. Mechano-transport interactions in biological systems. Development of computational tools for clinical applications. Recent articles highlight advancements in DXA-based finite element modeling, intervertebral disc mechanics, and osteoporosis drug efficacy evaluation. His work bridges biomechanics with clinical needs, emphasizing personalized medicine and predictive analytics. Awards: Spanish Chapter Award (2017). He has managed grants totaling millions in projects addressing spinal biomechanics, bone densitometry, and fracture risk. Active in the ESB Executive Board, he also explores popular science outreach through audiovisual media.

• Reinforcement Learning
• Multi-Agent Systems
• Automated Planning
• +۴ مورد دیگر

Anders Jonsson is a full professor and head of the Artificial Intelligence and Machine Learning research group at Universitat Pompeu Fabra (UPF). He holds a Ph.D. in Computer Science from the University of Massachusetts Amherst (2005), supervised by Professor Andrew Barto. His research focuses on sequential decision problems, multi-agent systems, hierarchical planning, and reinforcement learning. Key interests include combining RL with automated planning, exploiting structural properties of decision problems, and analyzing computational complexity. His work bridges theoretical foundations and practical applications in wireless networks, medical diagnostics, and urban systems. Jonsson’s research addresses challenges in decentralized spatial reuse in wireless networks, optimal power control for cell-free systems, and interpretable machine learning for clinical decision-making. His interdisciplinary approach integrates AI with telecommunications, environmental science, and healthcare. He has contributed to conference and journal articles exploring topics such as bisimulation metrics, reward machine exploration, and hierarchical average-reward MDPs. His lab actively develops algorithms for efficient exploration, generalized planning, and real-world deployment of AI solutions.

• Computational Logic
• Symbolic Machine Learning
• Probabilistic Inference
• +۶ مورد دیگر

Professor Alessandra Russo is a Professor in Applied Computational Logic at the Department of Computing, Imperial College London, and leads the Structured and Probabilistic Knowledge Engineering (SPIKE) research group. She holds academic affiliations with the Distributed Software Engineering Section and the Faculty of Engineering. Her research focuses on foundational AI, including symbolic machine learning, probabilistic inference, and neuro-symbolic systems, with applications to security, healthcare, and distributed control. As the Head of Department of Computing, she oversees interdisciplinary research initiatives. She has led major projects such as the EPSRC-funded Privacy Dynamics and the International Technology Alliance (ITA) project on decentralized network security. Her work integrates formal methods with machine learning to address real-world challenges like adaptive systems and privacy management. Professor Russo has supervised numerous PhD students and postdoctoral researchers, contributing to advancements in logic-based learning and distributed systems. Her contributions have been recognized with awards such as the Rector’s Award for Excellence in Teaching (2011). She actively collaborates with institutions like IBM Watson Research Centre, the Open University, and the University of Cyprus, and serves on editorial boards of journals like IET Software and ACM Computing Surveys.

• Technology-Enhanced Learning
• Social Emotional Learning
• Music and Education
• +۳ مورد دیگر

Emily Theophilou is a postdoctoral researcher at the Department of Information and Communication Technologies at Universitat Pompeu Fabra (UPF), Barcelona. She is affiliated with the Interactive and Distributed Technologies for Education (TIDE) Group. Her academic journey includes a BSc in Multimedia Computing (First Class) from Coventry University (UK) and a Master’s in Cognitive Systems and Interactive Media from UPF, followed by a PhD from UPF. Her research focuses on Technology-Enhanced Learning, Social Emotional Learning, Music and Education, and leveraging social media for educational purposes. Her work explores innovative educational methodologies, such as AI-driven assessment tools, empathy training in cyberbullying prevention, and narrative scripts embedded in social media platforms. She investigates how technology can address challenges like algorithmic transparency, digital literacy, and collaborative learning dynamics. Her recent publications highlight trends in AI ethics, chatbot interactions, and gender dynamics in digital learning environments. She also examines the impact of nudging principles on user safety and the role of social media in adolescent behavior development. Emily’s contributions include developing tools like Soéle for evaluating social awareness in learning designs and exploring distributed learning models. She emphasizes educational narratives and collaborative scripts to enhance critical thinking and self-protection skills among students.

• Automotive Engineering
• Vehicle Safety
• Braking Systems
• +۴ مورد دیگر

SUSANA SANZ SANCHEZ is a Visiting Professor in the Mechanical Engineering Department at University Carlos III of Madrid (UC3M), affiliated with the Experimental Mechanics, Calculations and Transport Group (MECATRAN) and the Duque de Santomauro Institute of Motor Vehicle Safety. Her work spans automotive engineering, vehicle safety systems, and biomechanics applications. Her research interests focus on automotive engineering with specialization in braking systems, vehicle dynamics, and safety inspection methodologies. She has developed the fBrake software suite for measuring braking efficiency in vehicles, which has been widely adopted by vehicle inspection centers across Spain and internationally. Recently, her work has expanded into biomechanics , where she has designed low-cost assistive devices for arm exercise targeting elderly populations, demonstrating interdisciplinary reach from automotive engineering to medical applications. The analysis of her recent publications reveals a clear research trajectory from traditional automotive engineering toward more interdisciplinary applications. While her earlier work concentrated on braking systems, vehicle dynamics, and inspection methodologies, her 2023-2024 publications show a significant pivot toward assistive technology and biomechanics, particularly with the development of sensor-based devices for elderly rehabilitation. Her work consistently combines theoretical modeling with practical implementation, often leveraging IoT architectures and machine learning techniques. Dr. Sanz Sanchez leads numerous research projects funded by major automotive inspection organizations across Spain, including multiple contracts with ITV stations and TÜV Rheinland for the implementation and maintenance of the fBrake software system. She has also secured funding from the Spanish State Research Agency (AEI) for developing intelligent driving systems using low-cost IoT devices. Her laboratory work centers around the Experimental Mechanics, Calculations and Transport Group (MECATRAN), where she has established testing facilities for vehicle dynamics analysis and has recently expanded into biomechanics testing with the Polyclinic of Tor Vergata in Italy. Her current research stay at UC3M (2023-2024) focuses on refining prototypes for arm exercise devices in collaboration with medical rehabilitation specialists.

• Cybersecurity
• Hardware Security
• Embedded Systems
• +۵ مورد دیگر

Martin Gonzalez Honorio is an Associate Professor at the Department of Electronics Technology, Universidad Carlos III de Madrid. He serves as Subdirector of Students and Coordination of Final Year Projects. His research focuses on hardware security, embedded systems, and IoT security, with emphasis on physical unclonable functions (PUFs), radiation-hardened designs, and cryptographic primitives. He leads the Grupo Universitario de Tecnologías de Identificación (GUTI) research group and has contributed to over 30 publications since 2011. His work addresses challenges in secure authentication protocols, fault-tolerant electronics, and biomedical signal processing applications. Key areas: Hardware Security, IoT Infrastructure Protection, Radiation Effects on Electronics Notable contributions: SRAM PUF implementations, FPGA radiation hardening techniques, and TRNG designs using biometric data Recent research trends show strong focus on combining machine learning with hardware fingerprinting techniques for device identification, while maintaining emphasis on cryptographic protocol security. His publications reflect advancements in both theoretical foundations and practical implementations of secure embedded systems. No scientific awards or grants are explicitly listed, though his active research output indicates sustained academic engagement. His involvement in teaching and student coordination highlights commitment to academic development alongside technical research.

• Electronics Engineering
• Computer Science
• Fault-Tolerant Systems
• +۷ مورد دیگر

Marta Portela Garcia is an Associate Professor at the University Carlos III de Madrid, where she holds a position in the Academic Department of Electronic Technology. She is affiliated with the Microelectronic Design and Applications (DMA) research group and the University Institute on Gender Studies. Her expertise bridges hardware design, fault tolerance, and embedded systems reliability, with a focus on aerospace and medical technologies. Her research spans fault-tolerant hardware architectures, radiation effects on electronic circuits, affective computing for wearable devices, and cryptographic techniques for secure communication. Recent work includes advancing post-quantum cryptography for sensor networks and improving dependability in edge computing systems. Publications emphasize innovations in circuit hardening, fault injection methodologies, and FPGA-based co-design solutions. Notable contributions include radiation-resistant systems for space applications and emotion recognition via physiological signals. While no formal advisees are listed, her collaborative projects and research groups suggest strong involvement in academic mentorship. Grants and funding details are not explicitly stated in the provided texts. She actively contributes to the DMA research group and the University Institute on Gender Studies, integrating interdisciplinary approaches to solve challenges in microelectronics and technology ethics.

• Quantum Physics
• Quantum Computing
• Quantum Control
• +۵ مورد دیگر

Erik Torrontegui Muñoz is a Ramón y Cajal Research Fellow at the University Carlos III of Madrid (UC3M), where he serves as Director of the University Master's Degree in Quantum Technology and Engineering. He is affiliated with the Physics Department and leads research within the QUEST (Quantum Engineering, Science and Technology) research group. His research focuses on quantum technologies, particularly quantum control, quantum computing, quantum sensing, and quantum neural networks. His work bridges theoretical quantum physics with practical applications in quantum information processing. He has made significant contributions to the field of shortcuts to adiabaticity, which enables faster quantum operations while maintaining high fidelity. Torrontegui's recent publications demonstrate expertise across multiple quantum platforms including nitrogen-vacancy centers in diamond, superconducting qubits, trapped ions, and quantum neural networks. His research shows a consistent pattern of developing control techniques that enhance quantum system performance while addressing practical limitations. Ramón y Cajal Research Fellowship (prestigious Spanish research award) As an academic advisor, Torrontegui mentors several PhD students working on quantum technologies. His research is supported by multiple projects including collaborations with IONQ QUANTUM, INC., ARQUIMEA RESEARCH CENTER, and funding from the Spanish Agency for Research (AEI). He maintains active laboratory work in quantum engineering, with particular focus on developing quantum sensing protocols and quantum computing architectures based on NV centers and other quantum platforms.

• Wireless Sensor Networks
• Unmanned Aerial Vehicles (UAVs)
• Air Traffic Management
• +۷ مورد دیگر

Rafael Casado González is a Professor at the Department of Systems Informatics, School of Engineering, University of Castilla-La Mancha, Spain. He was previously an Associate Professor at the same institution and was promoted to Full Professor (Catedrático de Universidad) on May 23, 2023. His academic journey includes a Doctorate in Computer Engineering from UCLM (2001), a degree in Computer Engineering from Universidad de Murcia (1996), and a Technical Engineering in Systems Informatics from UCLM (1993). Doctor Ingeniero en Informática – University of Castilla-La Mancha (2001) Ingeniero Informático – Universidad de Murcia (1996) Ingeniero Técnico en Informática de Sistemas – University of Castilla-La Mancha (1993) His research spans Wireless Sensor Networks (WSNs) , Unmanned Aerial Vehicles (UAVs) , air traffic management , and high-performance network reconfiguration . He has made significant contributions to aviation safety, particularly in missed approach maneuvers , aircraft reinjection , and conflict resolution in U-Space . His work also extends to distributed forest fire monitoring and entrepreneurship education in engineering . The 15 most recent publications reflect a strong trend toward UAV traffic management , environmental sustainability in aviation , and intelligent systems for air navigation . His work combines simulation, machine learning, and real-time algorithms to improve safety and efficiency in complex airspace environments. Earlier works focus on network reconfiguration and localization in WSNs , indicating a long-standing interest in distributed and autonomic systems. Rafael Casado González has collaborated with prominent researchers such as Aurelio Bermúdez, Carlos T. Calafate, and Pablo Boronat across multiple publications. His affiliations are consistently with the University of Castilla-La Mancha, and he contributes to both technical and educational research domains. There are no listed scientific awards or honors in the provided text. He has advised or collaborated on various research projects, particularly in UAV systems and WSNs, though specific student names are not mentioned. His work has been supported through institutional affiliations and collaborative research, but no grants are explicitly listed. He is actively involved in developing simulation frameworks and real-time navigation systems for autonomous drones. While no specific lab or research group name is mentioned, his work on SensGrid , UAV navigation frameworks , and WSN-based fire monitoring systems suggests involvement in a research lab focused on intelligent distributed systems and aerospace applications.

• Wireless Networks
• Internet of Things (IoT)
• Fog Computing
• +۷ مورد دیگر

Luis Orozco-Barbosa is a full-time Professor in the Department of Systems Informatics at the Universidad de Castilla-La Mancha, Spain. He previously held academic positions at the University of Ottawa, Canada, progressing from Assistant to Full Professor in the School of Information Technology and Engineering and the Department of Electrical and Computer Engineering. His career spans over three decades, with a consistent focus on networking, wireless systems, and emerging technologies. Research Interests: His primary research areas include Wireless Networks, Internet of Things (IoT), Fog and Edge Computing, Indoor Localization, Smart Cities, and Energy-Efficient Communication Protocols. He has made significant contributions to MAC layer design, sensor networks, and the application of AI in network optimization. His work bridges theoretical modeling with practical implementation in real-world systems. Publication Trends: His recent publications (2022–2025) reflect a strong emphasis on next-generation wireless standards (e.g., IEEE 802.11ah), deep learning for localization, federated-fog architectures, and energy-aware algorithms for IoT. The interdisciplinary nature of his research is evident in journals spanning signal processing, computer-aided design, human-computer interaction, and mathematical modeling. Scientific Awards: Investigador RENACYT - Grupo Carlos Monge Medrano - Nivel I Grants and Funding: He has secured multiple competitive research grants from Spanish national and regional agencies, including the Ministry of Economy and Competitiveness and the Ministry of Education, Culture and Sport. His funded projects address high-performance server optimization, reliable data center architectures, UAV applications, and wireless sensor networks in viticulture (WISEVINE2). These grants highlight his leadership in applied research with societal and industrial impact. Labs and Research Teams: While specific lab names are not mentioned, his frequent collaborations with researchers such as Manuel Castillo-Cara, Javier Gómez, and Raúl García-Castro suggest active leadership in a research group focused on smart systems, IoT, and network protocols at Universidad de Castilla-La Mancha.