جست‌وجوی استاد و پژوهشگر

Claudia Patricia Ayala Martinezمشاهده پروفایل

مدرس

• Empirical Software Engineering
• Off-The-Shelf Adoption
• Requirements Engineering
• +۴ مورد دیگر

Claudia Patricia Ayala Martinez serves as a Lecturer in the Department of Service and Information Systems Engineering at the Barcelona School of Informatics (FIB), Polytechnic University of Catalonia (UPC). She is actively involved in research through the GESSI - Group of Software and Service Engineering and the UPC inSSIDE - integrated Software, Services, Information and Data Engineering research groups. Her career spans over two decades of academic contributions in software engineering with consistent publication output. Dr. Ayala Martinez's research focuses on Empirical Software Engineering, Off-The-Shelf Adoption, Requirements Engineering, and Software and Architectural Quality. Her work demonstrates an evolution from traditional software engineering topics toward increasing integration with machine learning and AI systems. Recent publications show particular emphasis on software quality indicators, ML pipeline design principles, trustworthiness of ML models, and green computing in software systems. Analyzing her publication trends reveals a consistent research trajectory with growing focus on AI/ML integration in software engineering. Her work spans empirical studies, systematic literature reviews, and practical industrial applications. The research shows strong connections between software quality metrics, architectural decisions, and emerging technologies, with increasing attention to ethical considerations in ML systems and sustainability in software development. Most-Influential Paper Award at the 30th IEEE International Requirements Engineering Conference Dr. Ayala Martinez has participated in numerous competitive R&D projects including those funded by the Spanish National Research Plan, Horizon 2020, and the Catalan Innovation Strategy. Her collaborative network includes extensive work with Professor Javier Franch Gutierrez (69 joint publications), Silverio Juan Martinez Fernandez (26 joint publications), and Cristina Gomez Seoane (20 joint publications). Her research has been supported by various national and European funding programs focusing on software engineering, quality assessment, and open source adoption. She is actively involved with the GESSI and inSSIDE research groups at UPC, which focus on integrated software, services, information, and data engineering. These groups maintain strong industry connections and have produced significant research in empirical software engineering, reference architectures, and quality assessment methodologies. Her recent work shows increasing collaboration with researchers working at the intersection of software engineering and artificial intelligence.

• Statistical Modeling
• Biostatistics
• Biomedicine
• +۷ مورد دیگر

Dae-Jin Lee is an Assistant Professor at IE University’s School of Science and Technology, specializing in statistical modeling and data science. Previously, he served as a Research Line Leader at the Basque Centre for Applied Mathematics (BCAM) and coordinated the Knowledge Transfer Unit in Data Science/AI. His academic background includes a Ph.D. in Mathematical Engineering (2010) from Universidad Carlos III de Madrid and postdoctoral research at CSIRO (Australia). His research focuses on statistical methods for complex data, including penalized splines, tensor product smooths, and applications in biomedicine, epidemiology, environmental science, and sports analytics. He has led multidisciplinary projects funded by public and industry grants, collaborating globally with experts across fields like engineering, medicine, and biology. Key research themes include predictive modeling for health outcomes (e.g., SARS-CoV-2 pneumonia severity), sports injury prevention, and AI in healthcare. His work integrates machine learning with traditional statistical techniques, addressing real-world challenges like pedestrian dynamics simulations and automated medical diagnostics. He is actively involved in scientific organizations, including the Spanish Biostatistics Society and the Statistical Modelling Society. His recent publications highlight innovations in growth curve modeling, AI ethics, and spatiotemporal data analysis, reflecting his commitment to advancing both theoretical and applied statistics.

• Fluid Dynamics
• Turbulence
• Heat Transfer
• +۶ مورد دیگر

Andrea Ianiro is a Full Professor in the Aerospace Engineering Department at Universidad Carlos III de Madrid (UC3M), where he leads research in fluid dynamics, turbulence, and heat transfer. His work bridges experimental techniques and machine learning applications for flow analysis and control. He serves as Associate Editor of the International Journal of Heat and Mass Transfer (2025-2028) and directs the EFM Lab (Experimental Fluid Mechanics Laboratory) at UC3M. Professor Ianiro's research focuses on turbulence characterization, boundary layer flows, and the application of machine learning to fluid mechanics problems. His work spans experimental techniques including Particle Image Velocimetry (PIV), infrared thermography, and advanced data processing methods. Recent research emphasizes data-driven approaches for flow field reconstruction, turbulence control, and heat transfer optimization in wall-bounded flows. His projects often combine theoretical, experimental, and computational approaches to address complex fluid mechanics challenges. The analysis of his recent publications reveals a strong trend toward integrating machine learning with traditional fluid mechanics. His work increasingly focuses on using deep learning techniques (particularly CNNs and GANs) for flow field prediction from limited measurements, developing meshless computational methods for flow analysis, and applying optimization techniques (including genetic algorithms) to heat transfer enhancement. His research maintains a strong experimental foundation while embracing data-driven approaches to tackle turbulence modeling challenges. Associate Editor of the International Journal of Heat and Mass Transfer (2025-2028) Professor Ianiro leads multiple significant research projects including SPANDRELS (SParse AND paRsimonious Event-based fLow Sensing, 2025-2030), HumanIC (Human-Centric Indoor Climate for Healthcare Facilities, 2024-2027), and EXCALIBUR (Extraction of machine learning strategies for turbulent flow control, 2023-2026). His work has attracted funding from the European Commission, Spanish National Research Agency, and industry partners including Airbus. He has supervised numerous theses on topics including AI-based sensing of turbulent flows, convective heat transfer control, and turbulent boundary layers. At UC3M, Professor Ianiro directs the Experimental Fluid Mechanics Laboratory (EFM Lab), which focuses on advanced measurement techniques for fluid flow and heat transfer characterization. The lab specializes in PIV/PTV techniques, infrared thermography, and the development of novel experimental approaches for turbulence research. Current research directions include machine learning applications for flow field reconstruction, plasma-based flow control, and heat transfer optimization in complex flow configurations.

Elsa Prada Nuñezمشاهده پروفایل

پژوهشگر

• Condensed Matter Theory
• Quantum Materials
• Topological Insulators
• +۱۴ مورد دیگر

Elsa Prada Nuñez is a Senior Researcher at the Institute of Materials Science of Madrid (ICMM) under the Spanish National Research Council (CSIC) . She leads the Quantum Dynamics of Materials (QUDYMA) group and currently serves as Head of the Theory Department. Her academic career spans multiple institutions, including the Universidad Autónoma de Madrid (UAM), Karlsruhe University, and Lancaster University, with a focus on condensed matter theory and quantum materials. PhD in Physics from UAM (2006) Tenured Scientist at ICMM-CSIC (2020-2025) Senior Researcher at ICMM-CSIC (2025-present) Her research explores quantum phenomena in low-dimensional materials and nanostructures, particularly topological insulators, Majorana zero modes in hybrid nanowires, graphene and 2D crystals, disorder effects, magnetotransport, spintronics, quantum pumping, straintronics, and exciton dynamics. She has directed over 20 students across PhD, Master's, and undergraduate levels, including notable projects on full-shell hybrid nanowires and twisted bilayer graphene. Recent publications highlight advancements in Josephson junctions, Majorana detection, and topological superconductivity in full-shell nanowires. Awards include the Young Female Scientist 2021 from the Royal Academy of Sciences of Spain and Mastercard, and the 2022 Certamen Universitario 'Arquímedes' First Award as a tutor. She has secured significant grants from the Spanish government and European collaborations for projects on quantum materials and topological superconductivity. Principal Investigator for €139,150 Spanish government grant (PID2021-125343NB-I00) Lead on €5,000 ICMM-CSIC grant (2020-2021) Participant in €3.48M EU AndQC project (2019-2023)

Yuan Zhongمشاهده پروفایل

دانشیار

• Applied Probability
• Stochastic Systems
• Operations Management
• +۷ مورد دیگر

Yuan Zhong is an Associate Professor of Operations Management at the University of Chicago Booth School of Business . He previously held positions as an Assistant Professor at Columbia University’s Department of Industrial Engineering and Operations Research and was a Postdoctoral Scholar at UC Berkeley’s Computer Science Department. Education: PhD in Operations Research, MIT (2012) MA in Mathematics, Caltech (2008) BA in Mathematics, University of Cambridge (2006) His research focuses on applied probability and stochastic system design , with applications in cloud computing , supply chain management , and e-commerce logistics . Recent work explores multi-period production systems and dynamic resource allocation in data centers and healthcare operations . Recent publications analyze cloud value chains , sparse graph design for delivery networks, and process flexibility in manufacturing. He has contributed to journals like Operations Research , Annals of Applied Probability , and Stochastic Systems . Scientific Awards: 2012 Kenneth C. Sevcik Outstanding Student Paper Award Best Student Paper Award at ACM Sigmetrics (2012) He teaches courses in business process fundamentals and queueing theory , with a future schedule including Operations Management: Business Process Fundamentals (2025–2026). No explicit student advising list was provided.

• Cloud Computing
• Green Computing
• High-Performance Computing
• +۷ مورد دیگر

Jordi Guitart Fernández is a Professor at the Department of Computer Architecture, Barcelona School of Informatics (FIB), Universitat Politècnica de Catalunya (UPC). He is also affiliated with the Barcelona Supercomputing Center (BSC-CNS), a leading national supercomputing facility. He leads the CROMAI research group, focusing on Computing Resources Orchestration and Management for AI. His work bridges high-performance computing, cloud systems, and artificial intelligence. Research Interests: Cloud Computing and Edge Computing Green and Energy-Efficient Computing Containerization and Virtualization for HPC Resource Orchestration and Management Autonomic and Self-Adaptive Systems Machine Learning Workflow Management AI-Driven System Optimization His recent publications reveal a strong focus on intelligent management of computing resources across cloud, edge, and HPC environments using machine learning and agent-based frameworks. He investigates performance, efficiency, and reliability in containerized AI and HPC workloads, particularly within Kubernetes and distributed infrastructures. His work increasingly integrates human-in-the-loop and trustworthiness aspects into AI systems. Scientific Awards: CLOUD Conference 2025 Best Paper Award VISIGRAPP 2025 Best Student Paper Award Premi Extraordinari de Doctorat 2025 - Àmbit d'Enginyeria de les TIC Test of Time Award Honorable Mention (e-Energy) Reconeixement als Mèrits Docents d'Especial Qualitat Top reviewers for Polytechnic University of Catalonia (Computer Science) - September 2017 Advising and Grants: He has advised doctoral students, including Peini Liu. He leads and participates in numerous competitive R+D+i projects, such as CROMAI and DALEST, funded by national and European programs like HORIZON 2020 and the Spanish State Research Plans. His work is supported by grants focused on knowledge generation and industrial leadership in computing technologies. Labs and Teams: He is the leader of the CROMAI - Computing Resources Orchestration and Management for AI research group at UPC. He also collaborates closely with the Barcelona Supercomputing Center (BSC-CNS), contributing to large-scale computing initiatives and strategic research agendas in Europe.

Agustín Zaballos Diegoمشاهده پروفایل

استادیار

• Smart Grids
• Internet of Things (IoT)
• Sensor Networks
• +۳ مورد دیگر

Agustín Zaballos Diego is an Assistant Professor in the Department of Computer Engineering at University Ramon Llull (URL), Barcelona, Spain, since 1999. He serves as Research Coordinator in the Department of Engineering at La Salle Campus Barcelona and leads the R&D Networking and Security Area since 2002. His academic background includes a PhD in Data Networks and Internet Technologies (2012), an International MBA (2014), and an M.S. in Electronic Engineering (2000). University: University Ramon Llull (URL) Department: Department of Computer Engineering Research Group: GRITS Research Focus: Real-time QoS-aware routing protocols in Smart Grids, Ubiquitous Sensor Networks, and IoT communications. His work bridges telecommunications, computer science, and energy systems through projects like OPERA (FP6), INTEGRIS (FP7), and FINESCE (FP7). Publication Trends: Recent articles highlight advancements in HF communications for Antarctic research, hybrid genetic algorithms for traffic engineering, IPv6 testing, and Industry 4.0-related networking solutions. Keywords span Smart Grids, IoT, Sensor Networks, and QoS optimization. Collaborative Projects: Key initiatives include the Antarctica Project , ATHIKA (ICT in healthcare), ENVISERA (environmental sensor networks), HOTSUP (online teaching innovation), PLANET4 (AI/ML in industry), and XIoT (IoT scalability challenges).

• Internet of Things
• Transport Protocol
• Cybersecurity
• +۸ مورد دیگر

Alan Briones Delgado is a researcher at the La Salle School of Engineering , Universitat Ramon Llull , with a focus on Internet of Things , Cybersecurity , and Transport Protocols . His work spans projects funded by the European Commission and national grants, including EXCEL4HOUSING4.0 , WeB-Nimbus , and NG-SOC , addressing challenges in cloud computing education, ecological monitoring, and security operations. His research integrates Artificial Intelligence and Wireless Sensor Networks for sustainable solutions. Key research areas include Quality of Service in heterogeneous networks, Environmental Conservation via IoT, and Teaching and Learning strategies for Big Data. Projects like EcoSentinel and BTL-COP highlight his commitment to Environmental Monitoring and Community Policing applications. His collaborations extend to institutions in the UK , Albania , and Western Balkans . Contact: alan.briones@salle.url.edu

Felix Gomez Marmolمشاهده پروفایل

دانشیار

• Cybersecurity
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Felix Gomez Marmol is an Associate Professor at the University of Murcia's Faculty of Informatics, Department of Information and Communication Engineering. His research focuses on cybersecurity, artificial intelligence, network security, and IoT security. He holds a PhD in Computer Science from the University of Murcia (2010), supervised by Dr. Gregorio Martínez Pérez. Key research interests include adaptive intrusion detection systems, dark web analysis, and AI-driven cybersecurity frameworks. He leads the Intelligent Systems and Telematics research group and previously contributed to the Sistemas Inteligentes group. His work emphasizes practical applications such as the SCORPION Cyber Range platform for cybersecurity training and gamification. Recent projects involve detecting hate networks on social media, optimizing malware defense using transfer learning, and developing SIEM systems for IoT environments. His contributions span technical papers on cybersecurity education, ethical hacking fundamentals, and blockchain-based security solutions. Prof. Gomez Marmol has collaborated on initiatives like the COBRA framework for simulating advanced persistent threats (APTs) and the COnVIDa dashboard for pandemic-related data analysis. His research bridges theoretical advancements with real-world cybersecurity challenges.

Alejandro Sánchez Graciaمشاهده پروفایل

دانشیار

• Molecular Evolutionary Genetics
• Population Genomics
• Comparative Genomics
• +۳ مورد دیگر

Alejandro Sánchez Gracia is an Associate Professor at the Universitat de Barcelona's Faculty of Biology, affiliated with the Department of Genetics, Microbiology and Statistics. He leads the Molecular Evolutionary Genetics research group and directs the advanced course in 'Phylogenomics and Population Genomics: Inference and Applications.' Education: Llicenciat in Biology (Universitat de Barcelona, 1998), PhD in Biology (Universitat de Barcelona, 2006) Research Focus: Molecular mechanisms of chemosensory gene evolution in arthropods, development of bioinformatics tools for evolutionary and population genomics, and population genomics of adaptation in Drosophila. His work bridges computational methods with evolutionary biology, emphasizing genomic approaches to study adaptation. Key projects include analysis of chemoreceptor gene families across Panarthropoda, genomic studies of Canary Island endemic species, and development of tools like BITACORA for gene family annotation. He has contributed to major genomic resources such as DnaSP 6 and participated in initiatives like the Earth BioGenome Project. Active in collaborative networks like the European Drosophila Population Genomics Consortium and AdaptNET (Adaptive Genomics Network). Grants and Projects: 2021-2024: PID2020-113168GB-I00 (Ministry of Science, Spain) - Poligenic adaptation in Drosophila 2020-2021: Catalan blind scorpion genome project (Institut d'Estudis Catalans) Labs/Teams: Heads the Molecular Evolutionary Genetics group, collaborating on projects involving spider genomics, chemosensory evolution, and population-level adaptation studies.

Wouter Lueksمشاهده پروفایل

استاد

• Applied Cryptography
• Anonymous Communication
• Privacy-Preserving Systems
• +۳ مورد دیگر

Wouter Lueks is a faculty member at the CISPA Helmholtz Center for Information Security in Saarbrücken, Germany. His research focuses on designing secure, practical, and privacy-friendly systems using applied cryptography, anonymous communication, and systems engineering. He leads a lab and actively mentors PhD and PostDoc researchers. Education: PhD in Computer Science (Radboud University, Netherlands), advised by Jaap-Henk Hoepman and Bart Jacobs. Postdoctoral Researcher at EPFL, Switzerland (SPRING Lab). Research Interests: Privacy-preserving systems for humanitarian aid and public health. Cryptography in decentralized networks and anonymous communication. Secure protocols for identity management and voting systems. Key Publications: Recent work includes privacy-preserving digital wallets for aid distribution (IEEE S&P 2025), biometric deduplication systems (IEEE S&P 2024), and decentralized proximity tracing protocols (Commun. ACM 2022). His research emphasizes practical applications of zero-knowledge proofs and attribute-based credentials. Awards: Distinguished Paper Award at IEEE S&P 2023. Runner-up Casper Bowden PET Award 2021 and CNIL-Inria Privacy Award 2021. Advising & Grants: Supervises PhD/PostDoc researchers and collaborates on projects funded by EU and industry grants. Active in open-source contributions, including the zksk library and Lightnion anonymous communication tool. Labs/Teams: Principal investigator at CISPA, collaborates with the SPRING Lab (EPFL) and leads interdisciplinary teams in privacy-enhancing technologies.

Marta Casanellasمشاهده پروفایل

استاد

• Algebraic Geometry
• Computational Biology
• Phylogenetics
• +۴ مورد دیگر

Marta Casanellas is a full professor in the Department of Mathematics at the Polytechnic University of Catalonia (UPC) and a researcher at the Centre de Recerca Matemàtica. She teaches at the Faculty of Mathematics and Statistics, ETSEIB, and FIB. She earned her PhD in mathematics from the University of Barcelona under RM Miró-Roig, focusing on algebraic geometry and liaison theory. After completing a postdoc at UC Berkeley with a Fulbright Scholarship, she shifted her research to applications of algebraic geometry in computational biology, particularly phylogenetics. Her educational background includes a PhD from the University of Barcelona (2002), followed by a postdoctoral fellowship at UC Berkeley (2002-2003) supported by a Fulbright Scholarship. She obtained a prestigious Ramón y Cajal contract at UPC in 2003, which marked her transition to interdisciplinary research at the intersection of mathematics and biology. Casanellas' research focuses on applying algebraic and geometric techniques to phylogenetics, with particular emphasis on evolutionary models, phylogenetic invariants, and computational methods for genomic data analysis. Her work bridges pure mathematics (particularly algebraic geometry) with biological applications, developing mathematical frameworks to reconstruct evolutionary histories and understand genomic relationships. She has published extensively in both mathematics journals like Advances in Mathematics and biology journals like Molecular Biology and Evolution. Her recent publications demonstrate a consistent focus on developing algebraic methods for phylogenetic analysis, with increasing attention to heterogeneous evolutionary processes across lineages, time-reversible models, and computational implementations of theoretical results. The trend shows progression from theoretical foundations in algebraic geometry toward increasingly sophisticated and applicable computational methods for biological data. Fulbright Scholarship for postdoctoral research at UC Berkeley Ramón y Cajal contract (2003) Casanellas has supervised PhD students including A. Kedzierska (co-supervised with R. Guigó of the CRG). She has served as principal investigator for three competitive Spanish government projects involving fifteen researchers each. She has held significant academic leadership roles including Deputy Director of Research of the Department of Mathematics at UPC (2015-2018), head of studies for the Degree in Data Science and Engineering at UPC (2018-2022), and currently coordinates UPC's PhD in Bioinformatics program and Bachelor's Degree in Bioinformatics. She leads the BIO-GEOMAP research group focused on applying mathematical techniques to biological problems.

• Autonomous Vehicles
• Intelligent Transportation Systems
• Robotics
• +۷ مورد دیگر

Miguel Ángel Sotelo Vázquez is a full Professor at the University of Alcalá, leading the INVETT Research Group (Intelligent Vehicles and Traffic Technologies). He holds the Department of Automatic Control and specializes in autonomous systems, particularly in path planning, sensor fusion, and human-vehicle interaction. His research integrates machine learning, robotics, and control theory to address challenges in intelligent transportation systems. He earned his Ph.D. in 2001 with a thesis on autonomous vehicle navigation in partially known environments. His work emphasizes real-world deployment, explainable AI, and safety-critical systems. Recent projects focus on lane change prediction, pedestrian behavior modeling, and cybersecurity for autonomous systems. Key contributions include neuro-symbolic frameworks for decision-making, real-time multi-physics field reconstruction, and cross-cultural studies of pedestrian interactions. He collaborates internationally on urban mobility resilience and hydrogen refueling infrastructure. Research Highlights : Development of knowledge graph-based prediction architectures Experimental validation of human-vehicle interaction in VR environments Creation of the SCOUT trajectory prediction framework

• Cybersecurity
• Internet of Things (IoT)
• Post-Quantum Cryptography
• +۵ مورد دیگر

Florina Almenares Mendoza is an Associate Professor at the Telematics Engineering Department of Carlos III University of Madrid , where she also serves as the Director of the University Master's Degree in Cybersecurity. Her research focuses on addressing security challenges in emerging technologies such as IoT, post-quantum cryptography, and privacy-preserving systems. Email: florina.almenares@uc3m.es Contact: 916246234 Location: 4.0.F06 - Quevedo Towers (Leganés) Research Interests Florina's work spans cybersecurity , Internet of Things (IoT) , and post-quantum cryptography , with a focus on scalable authentication, quantum-resistant protocols, and privacy. She explores machine learning applications for security, federated identity management , and smart grid security frameworks. Recent Publications Her recent research includes papers on DNSSEC soft delegation, hybrid quantum security for TLS/IPsec, PUF-based authentication in IoT, and blockchain-enabled auditability. These studies emphasize IoT security , quantum-resistant algorithms , and privacy-enhancing technologies .

Gemma Boledaمشاهده پروفایل

استاد پژوهشی

• Computational Linguistics
• Linguistic Theory
• Semantics
• +۳ مورد دیگر

Gemma Boleda is an ICREA Research Professor at Universitat Pompeu Fabra in Barcelona, Spain, where she co-directs the Computational Linguistics and Linguistic Theory (COLT) research group. Her research focuses on understanding how humans convey meaning through language, investigating the formal properties that support communication, and exploring how languages are shaped by cognitive and communicative factors. Her primary interests include lexical semantics, cross-linguistic variation, and the integration of linguistic theory with computational methods. She employs interdisciplinary approaches combining linguistics, artificial intelligence, and cognitive science, utilizing large-scale data analysis to study universal patterns and variations across languages. Boleda's publications demonstrate a consistent focus on computational semantics, lexical variation, and language evolution. Her recent work explores the intersection of symbolic and neural approaches to language processing, lexical creativity across development and evolution, and computational models of semantic phenomena like colexification and polysemy. She teaches Computational Semantics in the Master's in Theoretical and Applied Linguistics program and has secured significant research funding including ERC Starting Grants. Her work has contributed valuable linguistic resources such as the ManyNames dataset and Database of Catalan Adjectives.