جست‌وجوی استاد و پژوهشگر

Julian Fierrezمشاهده پروفایل

استاد

• Biometrics
• Signal and Image Processing
• Artificial Intelligence
• +۶ مورد دیگر

Julian Fierrez is a Full Professor at the School of Engineering, Universidad Autonoma de Madrid. With an h-index of 74 and over 20,000 citations, his work spans biometrics, signal/image processing, artificial intelligence, and human-computer interaction. Key research areas include: Biometric anti-spoofing and DeepFakes detection Mobile and behavioral biometrics Bias/fairness in AI systems Biometric applications in e-health and education Security in multimodal biometric systems His recent publications show strong focus on deep learning applications for biometric security, with specific subfields including fake detection, keystroke authentication, facial analysis for Parkinson detection, and privacy-preserving AI. He serves as Associate Editor for multiple IEEE and Elsevier journals. Scientific distinctions include: IAPR Young Biometrics Investigator Award (2017) Miguel Catalan Award to Best Researcher under 40 (2017) EURASIP Best PhD Award (2012) EBF European Biometric Industry Award (2006) Prof. Fierrez leads the BiDA Lab and supervises students like Ruben Tolosana and Aythami Morales. Current projects include BBforTAI (Biometrics and Behavior for Unbiased & Trustworthy AI) and PRIMA (Privacy Matters). He also contributes to standardization efforts in biometric evaluation.

• Biometrics
• Biometric Systems
• Computer Vision
• +۵ مورد دیگر

Raul Sanchez Reillo is a Full Professor at Universidad Carlos III de Madrid (UC3M), affiliated with the Grupo Universitario de Tecnologías de Identificación (GUTI). His research focuses on biometric systems, mobile authentication, and security technologies. Key areas include presentation attack detection, vein recognition, and ECG biometrics. He leads projects involving smartphone-based biometric solutions, 3D printed markers, and standards development for biometric interoperability. Research interests span multiple modalities: fingerprint authentication, dynamic signature verification, gait recognition, and vascular biometrics. He emphasizes usability and accessibility in mobile environments, exploring ergonomics and user interaction challenges. His work integrates machine learning (transformers, RNNs) with hardware solutions like FPGA-based systems. Publications highlight innovations in spoofing detection, medical applications (ECG/vein analysis), and low-cost hardware implementations. He contributes to European standards (BioAPI, Hand Data Interchange Format) and evaluates security practices for R&D compliance with EU data protection regulations. Current initiatives include enhancing biometric systems for critical infrastructure security and improving accessibility for elderly users. Active in interdisciplinary collaborations, he leads the Mobile Pass project evaluating user interaction in biometric systems. His lab (GUTI) develops open testing methodologies for biometric performance under Common Criteria and environmental stressors. Recent work addresses vulnerabilities in mobile fingerprint sensors and the ethical implications of biometric-as-a-service models.

• Dependable and Real-Time Systems
• Fault-Tolerant Distributed Systems
• Adaptive Systems
• +۲ مورد دیگر

Dr. Julián Proenza Arenas is an Associate Professor at the University of the Balearic Islands (UIB) within the Mathematics and Informatics Department of the Higher Polytechnic School. As Secretary of the Politechnical School, he contributes to the management of all engineering bachelor degrees and serves as Academic Coordinator for the EU EMJMD Programme on Engineering of Data-Intensive Intelligent Software Systems (EDISS) since 2021. Ph.D. in Informatics (2007), University of the Balearic Islands Licenciatura in Physics (1989), University of the Balearic Islands His research focuses on Dependable and Real-Time Systems , particularly fault tolerance in distributed environments, Clock Synchronization , and Fieldbus Networks . Recent work emphasizes Time-Sensitive Networking (TSN) and adaptive mechanisms for industrial automation. He has co-authored over 100 publications and three patents, with multiple best paper awards at IEEE conferences (2004–2023). IEEE Workshop on Factory Communication Systems Best Paper (2004) IEEE ETFA Best Work-in-Progress Paper (2012, 2014, 2016) IEEE ETFA Factory Automation Best Paper (2023) Dr. Proenza supervises 6 completed and 2 ongoing Ph.D. theses and leads national research projects like FT4TSNgrid (2022–2025) and DFT4FTT (2016–2019). He is Principal Investigator of the Sistemas Empotrados Inteligentes y Robótica (SRV-INTER) R&D group and actively collaborates with international institutions including Mälardalen University and Universidade do Porto.

Sergi Abadal Cavalleمشاهده پروفایل

استاد

• Chip-scale Wireless Communications
• Nanocommunications
• Nanonetworks
• +۱۲ مورد دیگر

Sergi Abadal Cavalle is a distinguished Professor in the Department of Computer Architecture at the Universitat Politècnica de Catalunya (UPC), affiliated with the Escola Tècnica Superior d'Enginyeria de Telecomunicació de Barcelona (ETSETB). He leads a dynamic research group focused on revolutionary computing architectures through wireless chip-scale networks and quantum interconnects. His work is supported by prestigious grants including an ERC Starting Grant and an ERC Proof of Concept Grant. Education: PhD in Computer Architecture, Universitat Politècnica de Catalunya (2016) MSc in Telecommunication Engineering, UPC (2011) BSc in Telecommunication Engineering, UPC (2010) Sergi's research focuses on overcoming the limitations of traditional wired interconnects in computing systems by pioneering wireless communication at the chip and package level. His work spans terahertz communications, graphene-based antennas, reconfigurable metasurfaces, and quantum-coherent networks. He has led major EU projects such as WINC, EWiC, QUADRATURE, and WiPLASH, aiming to revolutionize classical and quantum computing architectures. His research integrates electromagnetics, materials science, and computer architecture to enable ultra-fast, scalable, and energy-efficient systems. His recent publications demonstrate a strong trend toward integrating wireless technologies within computing systems, particularly using novel materials like graphene and software-defined metasurfaces. The articles highlight advancements in on-chip wireless communication, channel modeling, and the application of these technologies in 6G and quantum computing. His work bridges theoretical modeling with experimental validation and practical emulation. Scientific Awards: ERC Starting Grant (2022) ERC Proof of Concept Grant (2024) ACM NanoCom Outstanding Milestone Award (2022) NanoComNet Young Investigator Award (2019) UPC Outstanding Thesis Award (2016) IN-NOVA Award to Best Master Thesis (2021) IBM Award to Best Academic Record (2021) Medal from Real Academia de la Ingeniería (2024) IEEE Senior Member (2025) Sergi actively mentors a large group of PhD and Master's students, many of whom have received awards for their thesis work. He leads the N3Cat research group and collaborates with institutions such as IBM Research, NEC Labs Europe, RWTH Aachen, EPFL, University of Nottingham, and Intel Labs. His lab is at the forefront of experimental validation of wireless interconnects and quantum architectures, with ongoing projects focusing on emulation and commercialization of chiplet communication technologies.

• Quantum Safe Cryptography
• Threat Management
• Artificial Intelligence Security
• +۵ مورد دیگر

Dr. Marc Ph. Stoecklin is a Principal Research Staff Member and head of the Security Research Department at IBM Research Europe in Zurich, Switzerland. He co-leads IBM's global research strategy on Quantum Safe Cryptography and Migration, focusing on cryptographic artifact identification and migration implementation. Previously, he directed Threat Management research, applying AI and automation to threat detection, investigation, and response. Education: PhD in Computer, Communication and Information Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Switzerland His research spans quantum safe cryptography, threat management, AI security, threat detection, identity management, cyber deception, big data analytics, and security visualization. He pioneered AI-powered security operations, contributing to Watson for Cyber Security and QRadar Advisor with Watson, and analyzes AI/quantum computing misuse in cyber attacks. His 2016-2020 publications emphasize advanced threat detection, malware analysis, and AI security, featuring evasive malware deactivation, threat intelligence computing, and neural network watermarking. These works bridge research and product development, directly influencing IBM security offerings. Dr. Stoecklin led IBM's Cognitive Cyber Security Intelligence group (2014-2019) and the Security Research Department since 2019. As tech lead for IBM's COVID-19 task force (2020-2022), he developed IBM Digital Health Pass, deployed in New York's Excelsior Pass with over 1 million passes issued in two months. He heads the Security Research Department at IBM Research Europe in Zurich and has been integral to the Global Security Analysis Lab (GSAL) and Cognitive Cyber Security Intelligence (CCSI) group at IBM T.J. Watson Research Center.

Alysson Neves Bessaniمشاهده پروفایل

دانشیار

• Distributed Systems
• Dependability
• Fault Tolerance
• +۵ مورد دیگر

Alysson Neves Bessani is an Associate Professor at the Informatics Department of Faculdade de Ciências da Universidade de Lisboa, Portugal, and a member of the LaSIGE research group. His work focuses on distributed systems, Byzantine fault tolerance, and cybersecurity, with significant contributions to blockchain consensus and intrusion-tolerant architectures. Academic Rank: Associate Professor University: Universidade de Lisboa School: Faculdade de Ciências Department: Informatics Department Research Groups: LaSIGE, Navigators Research Interests span distributed systems design, Byzantine fault tolerance, adaptive consensus protocols, and secure multi-cloud storage. His work bridges theoretical foundations with practical implementations like the BFT-SMaRt library and the Vawlt startup. Scientific Awards include multiple Test-of-Time Awards (DSN'24, DSN'21), IBM Faculty Award (2017), and Best Student Paper at Middleware'19. He has advised numerous PhD and Master’s students, contributing to advancements in fault-tolerant systems. Publications (15 most recent) reveal trends in Byzantine consensus optimization, blockchain integration, and AI-driven threat detection. His interdisciplinary work combines distributed computing with genomics and IoT security, reflecting a broad impact across computer science.

Juan Manuel Cebrian Gonzalezمشاهده پروفایل

استادیار

• Computer Architecture
• Parallel Computing
• Power Management
• +۴ مورد دیگر

Juan Manuel Cebrian Gonzalez is an Assistant Professor at the Department of Computer Engineering and Technology, Faculty of Informatics, University of Murcia. His work focuses on computer architecture, parallel systems, and energy-efficient computing. Doctorate: University of Murcia (2011), thesis on fine-grain power and thermal management in multicore processors. Research interests: Designing architectural mechanisms for optimizing power consumption and thermal management in multicore systems, cache coherence in parallel architectures, and vectorization techniques for high-performance computing. His work also explores heterogeneous architectures, fault tolerance, and efficient memory systems. Recent article trends: Focus on cache management, speculative execution, lock-free constructs, and performance-energy trade-offs in edge and heterogeneous computing. Key methodologies include gem5 simulation, Arm SVE, and AVX-512 vectorization. Collaboration: Supervised by Dr. Juan Luis Aragón Alcaraz and Dr. Stefanos Kaxiras. Active in the Computer Architecture and Parallel Systems research group.

Carlos Castilloمشاهده پروفایل

استاد پژوهشی

• Algorithmic Fairness
• Social Computing
• Artificial Intelligence Ethics
• +۳ مورد دیگر

Carlos Castillo is an ICREA Research Professor at Universitat Pompeu Fabra, leading the Social and Responsible Computing Research Group. Their work focuses on algorithmic fairness, social computing, and mitigating bias in AI systems across criminal justice, education, healthcare, and hiring. Key projects include the Horizon Europe FINDHR initiative to detect discrimination in algorithmic hiring, causal inference studies on recidivism risk prediction, and analyzing gender biases in student evaluations. Research Interests: Algorithmic fairness, bias mitigation in AI systems, social data ethics, criminal justice analytics, education technology, and health informatics. Notable contributions include the FA*IR fair ranking algorithm and foundational work on auditing algorithms in digital health. Recent Trends in Articles: Recent work emphasizes interdisciplinary applications of algorithmic fairness—e.g., improving representativeness in hiring datasets, analyzing disparities in medical AI models, and addressing bias in student satisfaction surveys. Publications also explore radicalization pathways via recommendation systems and the societal impact of algorithmic decision-making. Awards: Best Paper Awards in CIKM 2022 (Francesco Fabbri), ICAIL 2019 (Marius Miron), and ISCRAM 2013 (Muhammad Imran). Grants: Leads the Horizon Europe FINDHR project and collaborates with the European Commission on algorithmic discrimination research. Labs/Teams: Directs the Social and Responsible Computing Group, focusing on interdisciplinary projects with PhD students and industry partnerships.

• Artificial Intelligence
• Robotics
• Data Science
• +۴ مورد دیگر

Cecilio Angulo Bahón is a full Professor at the Polytechnic University of Catalonia (UPC), affiliated with the Barcelona School of Industrial Engineering (ETSEIB) and the Department of Systems, Automatics and Industrial Informatics Engineering . He leads research in Artificial Intelligence and Robotics , with significant contributions to healthcare data analytics, digital twins, and human-robot collaboration. His research spans machine learning for medical data harmonization, generative adversarial networks in health informatics, and evolutionary algorithms for control systems. Recent publications focus on synthetic healthcare data generation, climate-resilient agriculture , and UMAP-based data analysis . His work bridges AI theory with practical applications in industrial and healthcare domains. Scientific awards include the Sant Jordi 2023 Digital Polytechnic Initiative Award . He has supervised doctoral candidates like Carlos Flores-Vázquez and N. Raya, with key collaborations at the IDEAI-UPC Intelligent Data Science and AI Research Group and the Institute of Robotics and Industrial Informatics (CSIC-UPC).

Juan Carlos Cuevasمشاهده پروفایل

استاد

• Theoretical Physics
• Nanophysics
• Molecular Electronics
• +۴ مورد دیگر

Prof. Juan Carlos Cuevas is a Professor of Theoretical Nanophysics at the Universidad Autónoma de Madrid (UAM). He holds a PhD in Physics from UAM (1999) and has led research groups in molecular electronics and nanoscience. His work focuses on superconductivity, quantum transport, and radiative heat transfer at the nanoscale. Key areas of research include: theoretical analysis of molecular junctions, superconducting nanostructures, and near-field thermal phenomena. Cuevas has co-authored influential books such as *Molecular Electronics* (World Scientific, 2017) and pioneered studies on single-molecule conductance and quantum interference effects. Recent contributions include discoveries on phonon interference in molecular junctions (2025), thermodynamic uncertainty relations in superconductors (2025), and advanced machine learning approaches for radiative heat optimization (2024). His work bridges theoretical models with experimental insights from scanning tunneling microscopy and nanofabrication techniques.

Raúl Suárez Feijóoمشاهده پروفایل

پژوهشگر

• Robotized Assembly
• Fine Motion Planning
• Robotized Grasping and Manipulation
• +۴ مورد دیگر

Summary Raúl Suárez Feijóo is a Researcher at the Universitat Politècnica de Catalunya (UPC) in the Institut d'Organització i Control de Sistemes Industrials (IOC). Born in Asturias, Spain (1959), he holds an Electronic Engineering degree from the National University of San Juan, Argentina (1984), and a Doctorate in Engineering from UPC (1993). His research focuses on robotized assembly, fine motion planning, grasping, and multi-robot systems. He has led the IOC as Deputy Director (2003–2009) and Director (2009–2016). He coordinates doctoral programs in Automation and Robotics at UPC. Suárez has authored numerous publications and received awards including the Best Paper Award at IEEE ISATP (1995) and the Best Reviewer Award at ICRA (2015). Education: Electronic Engineer (1984, Argentina), Doctor Engineer (1993, UPC) Leadership Roles: Director of IOC (2009–2016), Coordinator of Doctoral Programs Research: Over 100 publications in robotics, emphasizing grasping, manipulation, and industrial automation. His work includes contributions to robotic hands, motion planning, and collaborative robotics. Notable projects involve 5G-enabled robotic systems and multi-AGV traffic management. Awards highlight his impact in both international and national robotics communities.

• Signal Processing
• Machine Learning
• Acoustics
• +۷ مورد دیگر

Luis Antonio Azpicueta Ruiz is an Associate Professor in the Department of Signal Theory and Communications at Carlos III University of Madrid. He leads research in the Signal Processing and Learning Group (GTSA) and Machine Learning for Data Science (ML4DS) group, focusing on interdisciplinary applications spanning acoustics, telecommunications, and machine learning. Research Interests: His work bridges signal processing theory with practical applications in environmental acoustics, adaptive filtering systems, and machine learning. Key research themes include: Advanced adaptive filtering architectures for nonlinear systems Distributed estimation in sensor networks Acoustic echo cancellation and room equalization Psychoacoustic evaluation methods Machine learning applications in noise monitoring and sound analysis Research Projects: Principal investigator for multiple funded projects including: Diagnóstico del ruido de chorro en aeronaves (AEI, 2022-2025) LearnINg FLow and Noise Dynamics via AI (COMUNIDAD DE MADRID, 2024-2026) BODYinTRANSIT - Sensory-driven Body Transformation (EUROPEAN COMMISSION, 2022-2026) Aprendizaje Automático para análisis Big Data (MINISTERIO DE ECONOMÍA, 2018-2021)

• Machine Learning
• Cybersecurity
• IoT
• +۳ مورد دیگر

Pedro Miguel Sanchez Sanchez is a researcher affiliated with the University of Murcia , specializing in Machine Learning , Cybersecurity , and IoT . He earned his doctorate in 2024 with the thesis Identical IoT device identification via hardware performance fingerprinting and Machine Learning , supervised by Dr. Alberto Huertas Celdrán and Dr. Gregorio Martínez Pérez. Research Interests Pedro's work focuses on applying Machine Learning and Federated Learning to solve critical challenges in Cybersecurity and IoT environments. His research includes: Developing decentralized federated learning frameworks (e.g., Flighter, ProFe) for secure and efficient model training. Designing malware detection systems using system call data and large language models . Enhancing IoT device authentication via hardware fingerprinting techniques. Exploring moving target defense strategies to counter zero-day attacks on IoT networks. Building knowledge graphs for cyber defense applications. Recent Publications Pedro's 2025–2024 publications demonstrate a strong focus on decentralized federated learning , malware mitigation , and hardware-based security . Key trends include: Advancements in zero-shot learning for multilingual tasks on edge devices. Security frameworks (e.g., Cyberforce, Sentinel) for military reconnaissance and industrial IoT . Behavioral analysis techniques for ransomware detection and continuous authentication . Robustness studies on federated learning architectures under adversarial conditions. Creation of benchmarks like LwHBench for hardware performance evaluation. Collaborations He has collaborated with researchers in the Intelligent Systems and Telematics group, contributing to projects in 5G security , crowdsensing platforms , and trusted execution environments .

• Data Mining
• Bioinformatics
• Machine Learning
• +۳ مورد دیگر

Domingo Savio Rodríguez Baena is a Professor at Pablo de Olavide University, affiliated with the Department of Computer Languages and Systems. His research focuses on data mining, bioinformatics, and computational biology, with a particular emphasis on biclustering algorithms, gene co-expression networks, and high-performance computing applications. PhD in Engineering, Data Science, and Bioinformatics (2012) from Pablo de Olavide University His work spans interdisciplinary domains, including recommender systems , livestock behavior analysis , and biological data interpretation . Recent articles highlight his contributions to multi-GPU optimization , ensemble learning , and historical database construction . Key collaborations include the DATAi Intelligent Data Analysis and DASE Data Analytics Science & Engineering research groups. He has developed tools like the CyEnGNet–App for gene network visualization and BIGO for gene enrichment analysis. Contact: dsrodbae@upo.es

• Industrial Engineering
• Maintenance Optimization
• Industry 4.0/Digital Transformation
• +۶ مورد دیگر

Aitor Goti Elordi is a Professor in the Department of Mechanics, Design and Industrial Management at the Faculty of Engineering, University of Deusto. His extensive research portfolio spans industrial engineering, maintenance optimization, Industry 4.0 implementation, and sustainable manufacturing practices. He leads multiple EU-funded and industry-collaborative research projects focused on digital transformation in manufacturing sectors. His research interests center around the intersection of industrial engineering and digital transformation, with particular focus on maintenance optimization using evolutionary algorithms, predictive maintenance systems, and the development of future skills requirements for evolving industrial sectors. His work bridges theoretical research with practical industrial applications, particularly in the Basque manufacturing ecosystem. Analysis of his recent publications reveals a strong trend toward interdisciplinary research addressing Industry 4.0 challenges across multiple sectors. His work consistently focuses on practical applications of data science and AI in industrial contexts, with growing emphasis on sustainability and circular economy principles. A distinctive pattern in his research is the development of competency frameworks to identify future skills requirements across various industrial sectors including steelmaking, renewable energy, and supply chain logistics. Professor Goti Elordi leads multiple significant research projects including SUSTASKILLS (2023-2025) focused on industrial symbiosis skills, REshaping Supply CHAins for Positive social impact (2022-2025), and Real-time acoustic sensorS and artificial Intelligence appLications (2023-2026). His work has secured funding from the European Commission, Basque Government, and major industrial partners including SIDENOR, NEMAK, and ETXE-TAR. He actively supervises student projects, particularly in the area of machinery redesign and additive manufacturing applications. His teaching and research integrate practical industrial experience with academic rigor, emphasizing the development of both technical and transversal skills needed for future industrial challenges.