جست‌وجوی استاد و پژوهشگر

Simo Alamiمشاهده پروفایل

مربی

• Deep Learning
• Reinforcement Learning
• Inverse Reinforcement Learning
• +۴ مورد دیگر

Simo Alami is a Ph.D. candidate and Tutor at Ecole Polytechnique, affiliated with the LIX computer science laboratory under the supervision of Professor Jesse Read. He teaches tutorials for the Advanced Machine Learning and Autonomous Agents course (Computer Science, Ingénieur 3A/Master1) since 2020, focusing on practical implementations of machine learning algorithms and autonomous systems. His academic background includes undergraduate and graduate studies in Mathematics and Computer Science at Université Pierre et Marie Curie and Ecole CentraleSupélec. Ph.D. Candidate, Ecole Polytechnique (2020-Present) Master's Studies, Mathematics and Computer Science, Université Pierre et Marie Curie and Ecole CentraleSupélec Alami's research centers on developing algorithms that learn from experience through self-learned metrics, with core expertise in Deep Learning, Inverse Reinforcement Learning, and Metric Learning. His work targets robotic applications where agents must perform novel tasks by understanding logical concepts, while also extending to energy management systems through non-invasive load monitoring. He explores how meta-learning frameworks can enable transferable reward structures across domains. His publication record reveals a strong trajectory in distributional reinforcement learning and inverse reinforcement learning using generative models, with significant contributions to metric learning for clustering and energy disaggregation. The consistent focus on transferable methodologies across robotics and smart grid applications demonstrates his interdisciplinary approach to solving real-world problems through advanced machine learning techniques. Scientific recognition includes: Nvidia Grant awarded in 2022 for research on Meta-Inverse Reinforcement Learning 3rd Prize at Hi Paris Hackathon (2021) for a reinforcement learning-based smart grid energy management solution While not supervising graduate students as a Ph.D. candidate, Alami has secured competitive external funding including the Nvidia research grant. His industry collaboration with Accenta during a visiting researcher position resulted in ECML 2022 publications on non-invasive load monitoring, highlighting his ability to bridge academic research with practical engineering applications. As an active member of the LIX laboratory at Ecole Polytechnique, Alami participates in cutting-edge computer science research while maintaining external collaborations. His visiting researcher position at Accenta demonstrates engagement with industry partners, and his organization of the IRT SystemX Electromobilité et territoires webinar in 2021 reflects leadership in knowledge dissemination within the energy and mobility research community.

Luis Antonio Belanche Muñozمشاهده پروفایل

استاد

• Machine Learning
• Kernel Methods
• Neural Networks

Luis Antonio Belanche Muñoz is a Professor at the Department of Computer Science , Faculty of Informatics of Barcelona (FIB) , Universitat Politècnica de Catalunya (UPC) . He is affiliated with research groups SOCO - Soft Computing and IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Group . His career spans over 25 years, with 216 documented activities. His research focuses on Machine Learning , Kernel Methods , and Neural Networks . He has pioneered techniques in feature selection, similarity measures, and hybrid models connecting deep learning with kernel methods. His work applies to diverse domains including finance, microbiology, cancer diagnostics, and environmental engineering. Recent publications highlight trends in kernel matrix analysis using entropy, microbiome data integration , and drug resistance prediction in HIV. Earlier work includes knowledge-based systems for wastewater treatment diagnostics and educational technologies for MOOC environments. He has collaborated with 75+ researchers across UPC's research network, contributing to projects funded under Spain's State Research Plans and Catalonia's RIS3CAT strategy. His 2011 thesis on Feature selection in brain tumor MRS data demonstrates interdisciplinary applications.

Martha Ivon Cárdenas Domínguezمشاهده پروفایل

مدرس ارشد

• Intelligent Data Analysis
• Machine Learning
• Personalized Medicine
• +۳ مورد دیگر

Dr. Martha Ivon Cárdenas Domínguez is a Senior Lecturer at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Computer Science. She is an active member of the IDEAI-UPC - Intelligent Data sciEnce and Artificial Intelligence Research Group, as well as the SOCO (Soft Computing) research group. Education: BSc in Mathematics PhD in Artificial Intelligence (UPC) Master's in Artificial Intelligence Her research focuses on applying computational intelligence and machine learning techniques to biomedical data analysis, particularly for pharmacoproteomic applications involving G protein-coupled receptors. She specializes in kernel-based methods and data visualization techniques for sequence analysis and classification tasks. Recent publications demonstrate her expertise in manifold learning, subtype discrimination of GPCRs, and phylogenetic tree integration with visualization techniques. Her work addresses challenges in classification errors, mislabeling, and sequence transformation for complex biomedical datasets. Dr. Cárdenas employs advanced visualization strategies to explore metabotropic glutamate receptors and analyze protein sequence overlaps through manifold-based approaches. Her research bridges computational methods with biomedical applications, particularly in personalized medicine contexts. She actively contributes to competitive R&D+i projects and participates in international conferences. Her professional activities include 5 conference presentations, 2 book chapters, and 2 journal articles focusing on data science applications in bioinformatics. Dr. Cárdenas utilizes computational intelligence for analyzing receptor sequences and has developed innovative approaches for visualizing complex biological data structures. Her work has implications for drug discovery and personalized treatment development through enhanced understanding of receptor classification.

• Machine Learning
• Computer Vision
• Robotics
• +۵ مورد دیگر

Roberto Javier López Sastre is an Associate Professor of Signal Theory and Communications at the University of Alcalá. He holds a Ph.D. from the same institution (2010), focusing on 'Visual vocabularies for category-level object recognition' under Dr. Saturnino Maldonado Bascón's supervision. His research spans machine learning, computer vision, robotics, and astrophysics. Key areas include Bayesian neural networks for stellar dating, semantic navigation in robotics, and AI-driven medical assistive technologies. Affiliation: Department of Signal Theory and Communications, University of Alcalá Research Group: GRAM (Multisensorial Recognition and Analysis Group) His work interfaces computational methods with real-world applications, such as assistive robotics for neurodevelopmental disorder patients and deep learning models for astrophysical parameter estimation. Recent contributions include semantic segmentation-driven navigation systems and Bayesian approaches to black hole solutions. Publications emphasize interdisciplinary applications of AI, including live video processing, continual learning frameworks, and physics-informed neural networks. Ongoing research explores the intersection of robotics, healthcare, and astrophysics through collaborative projects. López Sastre's GRAM group focuses on multisensory data analysis for recognition and navigation challenges. His technical expertise spans signal processing, probabilistic modeling, and embedded AI systems.

• Bayesian Statistics
• Survival Analysis
• Biostatistics
• +۲ مورد دیگر

Elena Lazaro Hervas is a Part-Time Lecturer at the Universitat de València, affiliated with the Faculty of Mathematics and the Department of Statistics and Operations Research. Her research focuses on Bayesian statistical methods applied to survival analysis and biometric studies. Education: PhD in Statistics (2018, Universitat de València) She contributes to the Valencia Bayesian Research Group (VABAR) and has expertise in probabilistic modeling and computational statistics.

David Garrido Romeroمشاهده پروفایل

استاد

• Maritime History
• Archival Science
• Historiography
• +۳ مورد دیگر

David Garrido Romero is a Professor of Historiographic Sciences and Techniques at the University of Cádiz , actively engaged in maritime history and archival research. As a PhD candidate at CEIMAR (Campus of International Excellence for the Sea) and holder of two master's degrees – one in Maritime Heritage, Archaeology, and History (University of Cádiz, Extraordinary Master's Award ) and another in Documents, Books, Archives, and Libraries (University of Seville) – his academic foundation is robust. His work bridges maritime history, notarial documentation, and digital humanities. Research interests span 18th-19th century maritime history from notarial/documentary perspectives, with specific focus on: Maritime notarial institutions Underwater cultural heritage Historical manuscript digitization Global communication nodes in colonial contexts Archival metadata systems His recent publications highlight maritime legal frameworks, AI applications in archival work, and transatlantic cultural connections. He has participated in critical conferences at international venues (2016-2024) and received recognition for his work on Cádiz' maritime heritage. The Caravel Project (2018-2019) demonstrates his innovative approach to combining maritime archaeology with artificial intelligence. Key scientific contributions include: Developing probabilistic indexing methods for historical documents Digitizing 3200+ notarial maritime records Establishing archival metadata standards for maritime heritage Analyzing Bourbon dynasty reforms through notarial sources His work creates bridges between archival science, maritime archaeology, and digital humanities, ensuring historical sources remain accessible for modern research.

Anna De Mier Vinueمشاهده پروفایل

دانشیار

• Combinatorics
• Graph Theory
• Matroid Theory
• +۳ مورد دیگر

Anna De Mier Vinue is an Associate Professor at the Department of Mathematics, Universitat Politècnica de Catalunya (UPC), affiliated with the Facultat d'Informàtica de Barcelona (FIB). She leads research in combinatorics, graph theory, and matroid theory as part of the UPC's GAPCOMB research group (Geometric, Algebraic and Probabilistic Combinatorics). Her work focuses on structural combinatorics, polynomial invariants, and discrete geometry. Education: Holds a PhD in Applied Mathematics from UPC. Research Interests: Combinatorial enumeration, graph polynomials (Tutte, U-polynomials), matroid representations, non-crossing structures, and algorithmic combinatorics. Her contributions bridge algebraic methods with geometric and probabilistic approaches. Publications: Over 77 works including articles in Discrete Mathematics, European Journal of Combinatorics, and SIAM Journal on Discrete Mathematics. Recent research explores marked graphs, Tutte polynomial evaluations, and lattice approximations in clutter theory. Active in international projects like COCOA and R+D+I initiatives. Grants & Collaborations: Co-leads projects on extremal combinatorics, geometric algorithms, and mathematical education. Collaborates with researchers from BarcelonaTech and international institutions. Involved in initiatives addressing gender equality in STEM education through statistical analysis. Labs/Teams: Core member of the UPC's GAPCOMB group, contributing to interdisciplinary projects at the Institut de Matemàtiques de la UPC-BarcelonaTech. Supervises research in combinatorial geometry and algebraic structures.

Víctor López Domínguezمشاهده پروفایل

استادیار

• Spintronics
• Magnetic materials
• Electrical transport
• +۵ مورد دیگر

Víctor López Domínguez is an Assistant Professor and Principal Investigator at the Institute of Advanced Materials (INAM) of Jaume I University in Castelló, Spain, where he leads the Spintronics for Advanced Devices Lab (SPINAD Lab). His research focuses on developing next-generation spintronic devices for computing and sensing applications. His academic background includes: PhD in Nanoscience and Nanotechnology (2014) from University of Barcelona Physics Degree (2009) from University of Barcelona López Domínguez's research centers on electrical transport in magnetic materials, magnetization dynamics, and voltage-controlled spintronic devices. His work bridges fundamental physics with practical applications in neuromorphic computing, probabilistic systems, and nanoscale sensors. Key focus areas include antiferromagnetic spintronics, skyrmion manipulation, and energy-efficient computing paradigms that leverage spin-orbit torque and voltage control mechanisms. His 15 most recent publications reveal a strong emphasis on antiferromagnetic memory devices, voltage-controlled magnetism, and neuromorphic applications. The research spans from fundamental material studies to device integration, with significant contributions to silicon-compatible spintronic memory, probabilistic computing hardware, and magnetomechanical sensors. His scientific recognition includes: CIDEGENT grant (2022) from Generalitat of Valencia López Domínguez secured the CIDEGENT grant to establish his research group at INAM, supported by Jaume I University and INAM. His lab trains undergraduate, master's, and PhD students in experimental spintronics while collaborating with international clean rooms and industry partners. Current projects focus on implementing novel computing paradigms using spintronic devices. The SPINAD Lab maintains comprehensive facilities for material fabrication, device characterization, and nanofabrication through Spanish clean room networks. The group collaborates extensively with Northwestern University (where López Domínguez previously worked) and participates in international research consortia focused on next-generation computing technologies.

FRANCISCO JAVIER GARCIA POLOمشاهده پروفایل

استاد

• Artificial Intelligence
• Reinforcement Learning
• Robotics
• +۴ مورد دیگر

Francisco Javier Garcia Polo is a Professor at the University of Santiago de Compostela (USC) , affiliated with the Department of Electronics and Computing within the Higher Polytechnic School of Engineering . His research focuses on Reinforcement Learning (RL) , particularly in areas such as safe decision-making, adversarial attack detection, and policy transfer across tasks. He holds a PhD from Universidad Carlos III de Madrid (2013), where his thesis explored safe RL in continuous state-action spaces. Key research interests include enhancing RL robustness against adversarial attacks, federated learning applications in robotics, and applying RL to financial systems like automated market makers. He is part of the GSI Group (Intelligent Systems Group) , contributing to projects involving social assistive robotics and multi-modal transportation planning tools like TIMIPLAN. His work bridges theoretical advancements with practical domains such as healthcare robotics, cybersecurity, and economic modeling. Publications highlight innovations in policy defense mechanisms, similarity metrics between Markov Decision Processes, and frameworks for evaluating assistive robots. Despite his prolific output, he has not publicly shared research papers on Academia.edu. Collaborations span interdisciplinary topics, reflecting a commitment to both foundational AI research and real-world applications.

• Computational Mechanics
• Biomechanics
• Railway Systems
• +۵ مورد دیگر

Dr. Jesús R. Jiménez-Octavio is an Associate Professor in the Department of Mechanical Engineering at the School of Engineering (ICAI) of Comillas Pontifical University. He specializes in computational mechanics, biomechanics, road safety, and dentistry, with a focus on finite element analysis and computational fluid dynamics. As Academic Deputy Director at ICAI, he bridges academic leadership with multidisciplinary research. PhD in Industrial Engineering (2009), Comillas Pontifical University BSc in Industrial Engineering (2004), Comillas Pontifical University Research Interests : His work spans biomedical engineering (computational biomechanics, dental tissue characterization), railway systems (catenary-pantograph dynamics, wind load modeling), and automotive safety (seatbelt design, e-scooter injury analysis). He integrates numerical methods with experimental validation. Publication Trends : Recent articles emphasize biomechanics (vertebral injury modeling, dental stress analysis), railway engineering (dynamic cable systems), and safety simulation (impact scenarios). Cross-disciplinary themes include pandemic mobility analysis and AI in transportation safety. Scientific Awards : Honorary Distinction for Best Doctoral Thesis in Engineering (2010) Talgo Award for Technological Innovation (2010) 3rd National Sika Award for Adhesion Technology (2004) Multiple Erasmus and Marie Curie Fellowships Grants and Projects : Leads research on e-scooter safety , dental implant biomechanics , and high-speed railway dynamics . Collaborates with institutions like Mapfre CESVIMAP, European Rail Agency, and Mercedes-Benz Technology Group. Labs and Teams : Co-founder of the MOBIOS Lab (Mobility, Biomechanics, and Health Research), integrating AI, urban mobility, and injury prevention studies.

• Biomechanics
• Injury prevention
• Automotive safety
• +۲ مورد دیگر

Dr. Francisco José López Valdés is an Associate Professor in the Department of Mechanical Engineering at the ICAI School of Engineering, Universidad Pontificia Comillas. He joined the faculty in 2017 and is an Associate Member of the Institute for Research in Technology (IIT). His research focuses on injury biomechanics, road traffic safety, and pediatric impact biomechanics. Education: Bachelor's degree in Mechanical Engineering, University of Valladolid (2002) PhD in Biomedical Engineering from the University of Virginia (2007), focusing on pediatric impact biomechanics Research Interests: Specializes in injury prevention, automotive safety, and biomechanical testing. His work includes crash test methodologies, cadaver testing ethics, and the mechanical properties of biological tissues. He leads projects on e-scooter rider safety, seatbelt systems, and elderly occupant protection. Articles Trends: Recent studies emphasize cervical spine mechanics, additive manufacturing for crash energy absorption, and real-world crash analysis. His work bridges computational models (e.g., PIPER HBM) with experimental validations to improve safety standards. Awards: Received the 2019 Elaine Wodzin Young Achiever Award and the 2018 Best Paper Prize at the AAAM conference. Advising & Grants: Supervised 6 PhD theses and led projects like the SENIORS EU initiative. Collaborates with industry (e.g., Autoliv, MAPFRE) and agencies (MCIN/AEI) on injury mitigation and safety technology. Labs & Teams: Leads the MOBIOS Lab, a European hub for injury biomechanics research. Active in interdisciplinary teams studying automated vehicle seating configurations and sustainable mobility safety.

David Poza Garcíaمشاهده پروفایل

دانشیار

• Additive Manufacturing
• Project Management
• Combinatorial Auctions
• +۱ مورد دیگر

David Poza García is an Associate Professor at the University of Valladolid’s Department of Business Organisation and Market Research. He holds affiliations with INSISOC (GIR UVa, GREX251, UIC086) and professional organizations including ESSA, ADINGOR, and AEIPRO. His certifications include IPMA-D Project Management accreditation. Research focuses on optimization in industrial systems, spanning additive manufacturing, project scheduling, combinatorial auctions, and risk modeling. Key themes include algorithmic efficiency, stochastic analysis, and sustainable operations. Publications emphasize computational methods for industrial challenges, with recent trends in simulation-based scheduling, additive manufacturing economics, and uncertainty management in project frameworks. No advising roles, grants, or lab affiliations are detailed in available texts.

Mark Steelمشاهده پروفایل

استاد

• Bayesian Statistics
• Econometrics
• Distribution Theory
• +۷ مورد دیگر

Professor Mark Steel is a faculty member at the University of Warwick , serving as Professor of Statistics since 2003. He previously held a Chair in Economics at the University of Edinburgh (1998-2000) and a Chair of Statistics at the University of Kent (2000-2003). He has also served as Head of the Statistics Department at Warwick (2014-2018) and as Editor-in-Chief of Bayesian Analysis (2022-2025). Education: Ph.D. in Quantitative Economics from Université Catholique de Louvain (1987) Steel's research focuses on Bayesian econometrics and statistics , with interests in distribution theory, model averaging, spatial statistics, nonparametric inference, survival analysis, and stochastic volatility. His work bridges theoretical advancements with applications in macroeconomics (growth theory) , microeconomics (stochastic frontier models) , and finance (stochastic volatility) . Recent publications highlight his contributions to Bayesian computation , copula-based classification , and spatiotemporal modeling . His editorial roles include leadership in Bayesian Analysis and Journal of Productivity Analysis . Scientific Awards: Fellow of the Journal of Econometrics Steel co-leads the Centre for Research in Statistical Methodology (CRiSM) at Warwick and has secured grants such as the EPSRC GR/T17908/01 for flexible distributional modeling in panel data. His collaborations span institutions in the UK, Spain, Italy, and the Netherlands, with co-authors like Roberto Casarin and Jairo Fúquene.

• Optical Networking
• Cybersecurity
• Fault-Tolerant Computing
• +۳ مورد دیگر

Alfonso Alejandro Sanchez Macian Perez serves as an Associate Professor in the Telematics Engineering Department at Carlos III University of Madrid, specializing in cutting-edge telecommunications and cybersecurity research. His work spans optical networking, fault-tolerant systems, and space applications, with significant contributions to 6G infrastructure development and privacy-preserving data structures. His research focuses on optical networking innovations for next-generation communications, including space-division multiplexing and multi-band migration techniques critical for 6G deployment. In cybersecurity , he investigates vulnerabilities in probabilistic data structures like Bloom filters and KMV sketches, developing countermeasures against privacy attacks. His space systems research addresses radiation-hardened memory architectures and FPGA reliability for spacecraft applications, with emphasis on error correction and fault tolerance. As principal investigator for major projects including FUN4DATE Redes (2023-2026), Agile uLtra Low EnerGy secuRe netwOrks (2023-2026), and PROTEUS-6G (2024-2026), he leads EU and nationally funded initiatives advancing optical transport networks and sustainable high-capacity infrastructure. His publication record shows consistent high-impact output across IEEE Transactions and optical networking journals, with growing emphasis on 6G-enabling technologies since 2021. His laboratory work centers on the Telematics Engineering Research Group at UC3M, collaborating with Telefónica Innovation Digital and European Commission agencies on photonic integrated circuits and non-terrestrial networks. Current efforts focus on programmable optical transport for 6G services and self-managed sustainable optical networks through the SEASON project.

• High-energy particle phenomenology
• Quantum computing for scattering amplitudes
• Loop-tree duality
• +۳ مورد دیگر

Germán Rodrigo is a tenured Research Professor at the Instituto de Física Corpuscular (IFIC) , a joint centre of the Spanish National Research Council (CSIC) and the University of Valencia . After earning his PhD in 2003 under Arcadi Santamaria, he held post-doctoral positions at KIT Karlsruhe and CERN before returning to Valencia in 2008. He currently leads the quantum–phenomenology group within the theoretical physics department. His research straddles high-energy collider phenomenology and quantum computing. Rodrigo is internationally recognised for turning multi-loop Feynman integrals into causal, loop-tree-dual forms and for implementing the resulting algorithms on real quantum hardware. Key achievements include the first quantum calculation of loop integrals, quantum jet clustering at the LHC, and quantum amplitude estimation with error mitigation. Recent work (2022-2025) focuses on: Quantum integration of decay rates and fragmentation functions Graph-based quantum algorithms for causal multi-loop configurations Adaptive importance sampling on quantum annealers and gate-based devices Factorisation-breaking studies in triple-collinear splitting with massive partons He advises three doctoral students and is PI on a national Spanish grant supporting the group’s quantum-technologies programme. No personal e-mail is publicly listed; contact is handled through the IFIC secretariat.