جستجوی استاد راهنمای دانشگاهی

Xavier Serra is a Full Professor at the Department of Engineering at Universitat Pompeu Fabra (UPF), Barcelona. He is the founder and director of the Music Technology Group (MTG), and leads the UPF-BMAT Chair on AI and Music. He also coordinates the Master in Sound and Music Computing and serves as President of the Phonos Foundation. His research focuses on audio signal processing, sound and music computing, and computational musicology, emphasizing open science and open innovation. Education: BSc in Biology, University of Barcelona (1981) Master in Music, Florida State University (1983) PhD in Computer Music, Stanford University (1989) Research Interests: Audio Signal Processing Data-Driven and Knowledge-Driven Methodologies Music Information Retrieval Cultural Music Analysis (e.g., Carnatic/Turkish/Andalusian Music) Music Education Technology Notable Projects: CompMusic (ERC Advanced Grant, 2010-2017): Multicultural computational music analysis Open datasets: Freesound, Saraga, FSD50K Technologies: Reactable, Vocaloid, Essentia API Recent Trends in Articles: Focus on AI-driven audio processing (neural fingerprints, generative models), cross-cultural music analysis, and explainable music difficulty estimation. Awards: ERC Advanced Grant (2010) for CompMusic Project. Labs/Teams: Director of MTG, Phonos Foundation, and UPF-BMAT Chair. Active in open-source projects and international collaborations.

• Audio Signal Processing
• Sound and Music Computing
• Music Information Retrieval
• +۵ مورد دیگر

Prof. Raimon Jané Campos is a leading figure in biomedical signal processing at the Universitat Politècnica de Catalunya (UPC) and Universitat de Barcelona (UB). As co-director of UPC's Biomedical Signal and System Group (CREB) and coordinator of the Biomedical Engineering PhD Programme, he bridges engineering and clinical applications. His work focuses on respiratory and sleep disorder diagnostics, with significant contributions to COPD and sleep apnea monitoring through wearable devices and machine learning. PhD in Biomedical Engineering (UPC, 1989) Visiting researcher at Université de Nice-Sophia Antipolis Vice-president of Spanish Society of Biomedical Engineering Research spans respiratory mechanics , sleep-disordered breathing , acoustic biomarkers , bioimpedance , and machine learning in biomedical contexts . His 2025 work on microcalorimetric pathogen classification and 2024 spiking neural networks for apnea detection demonstrate cutting-edge integration of computational methods with physiological monitoring. Articles from 2017-2024 reveal consistent focus on non-invasive diagnostics , cardiorespiratory synchronization , and smartphone-based health solutions . Awarded the Barcelona City Technology Research Award (2005) and serving on the International Advisory Board for Physiological Measurement since 2010, his career combines academic leadership with real-world clinical translation through IBEC's technology transfer initiatives.

• Biomedical Signal Processing
• Respiratory Monitoring
• Sleep Disorders
• +۴ 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)

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

Antonio Salvador Pena Gimenez is a full-time researcher at the Universidade de Vigo , affiliated with the School of Telecommunications Engineering and the Department of Signal Theory and Communications . He holds a PhD from the Polytechnic University of Madrid (1995) for his work on Psychoacoustic modeling techniques applied to very high quality audio coding , supervised by Dr. Luis Alfonso Hernández Gómez. Education: PhD in Signal Theory and Communications (Polytechnic University of Madrid, 1995) University Degree in Full-Time Mode His research spans signal processing , biomedical engineering , and audio signal analysis , with a focus on medical applications (e.g., ECG processing) and music information retrieval (e.g., beat tracking, onset detection). He has contributed to non-invasive vital sign monitoring and data compression techniques in audio and biomedical contexts. The 15 most recent articles (prioritized by year) highlight his work in polyphonic music analysis , rhythmic structure modeling , and medical signal compression . Key trends include machine learning for audio processing , biomedical signal analysis , and algorithm development for telemedicine . He has collaborated with institutions including Instituto Politécnico de Setúbal , Instituto de Telecomunicações , and University of Cambridge . His work has been cited 567 times, with an h-index of 9. He is involved in underwater acoustic databases (e.g., ShipsEar) and smartphone-based telecare systems , indicating ongoing work in sensor networks and mobile health applications .

• Signal Processing
• Biomedical Engineering
• Audio Signal Processing
• +۳ مورد دیگر

David Santos Dominguez is a Doctoral Research Personnel in GROUP I at the University of Vigo, affiliated with the School of Telecommunications Engineering and the Department of Signal Theory and Communications. His work focuses on underwater acoustics, marine noise pollution, and environmental monitoring. Education: PhD in Signal Theory and Communications (University of Vigo, 2020) Email: dsantos@gts.uvigo.es His research explores underwater noise mapping methodologies, ship noise impacts on marine organisms, and hydrophone signal processing. Recent work analyzes dredger noise propagation and marine vessel acoustic databases, with interdisciplinary implications for Marine Biology , Environmental Engineering , and Signal Processing . Publications show consistent focus on Shallow Water Acoustics , Hydroacoustics , and Marine Environmental Assessment , often combining experimental measurements with computational modeling. Despite no listed awards, his collaborations span marine conservation and engineering disciplines.

• Underwater Acoustics
• Marine Noise Pollution
• Signal Processing
• +۴ مورد دیگر

Francisco Javier Oliver Bernal is a Lecturer at the University of Deusto in Bilbao, Spain, within the Faculty of Education and Sport and the Department of Physical Activity and Sports Sciences. He teaches across Computer Engineering, Physical Activity and Sports Sciences, and Primary Education bachelor's programs, as well as the Master's in Secondary Education. He earned his Doctor of Medicine and Surgery from the University of the Basque Country. His research spans Human-Computer Interaction, Educational Technology, and Science Education, with a strong emphasis on accessibility for visually impaired users. He has developed tools for e-learning, digital resource centers, and innovative teaching methodologies in computer science and natural sciences, aiming to enhance educational experiences through technology. His scholarly output, spanning from the 1990s to 2023, demonstrates a consistent focus on technology-enhanced learning, evolving from early work in 3D interfaces and computer graphics to recent applications in health, music, and interdisciplinary educational contexts. Key trends include the integration of accessibility features, the development of domain-specific educational tools (e.g., for biology and astronomy), and responses to contemporary challenges like the COVID-19 pandemic. He has supervised multiple theses on digital accessibility and cooperative systems, though student names were not listed. Details on research grants were not provided in the available text. As a member of the eVida research group (officially recognized by the Basque Government), he contributes to projects advancing accessible educational technologies, including the ACCE project for audiovisual accessibility and READIS digital resource centers for visually impaired users.

• Human-Computer Interaction
• Educational Technology
• Computer Science Education
• +۳ مورد دیگر

Antonio Calomarde Palomino is an Associate Professor at the Department of Electronic Engineering, Polytechnic University of Catalonia (UPC), located at the Higher Technical School of Industrial Engineering of Barcelona. He holds a B.S. in Telecommunications Engineering (UPC, 1986), an M.S. in Electronic Engineering (Universitat Autònoma de Barcelona, 1993), and a Ph.D. in Electronic Engineering (UPC, 2007) with honors. His research focuses on low-power/high-performance digital circuits and soft-error resilient designs, addressing challenges in semiconductor technology and radiation-hardened electronics. Key research areas include FinFET-based memory cells, RRAM modeling, and radiation mitigation strategies for advanced nanoelectronics. He contributes to the High Performance Integrated Circuits and Systems Design (HIPICS) Group, advancing circuit design methodologies and educational initiatives such as integrating autonomous vehicle systems into undergraduate curricula. His work bridges theoretical advancements with practical applications in automotive electronics and embedded systems. Publications span topics from memristor-based associative memory to approximation techniques in object detection systems, reflecting a balance between fundamental research and applied engineering. His recent work emphasizes variability-aware design and energy-efficient architectures, as seen in 2023-2024 studies on RRAM models and automotive case studies. Calomarde actively organizes academic events like the 2022 ETS conference and develops educational materials for digital electronics and audiovisual systems courses. His contributions to both technical research and pedagogical innovation solidify his role as a key figure in electronic engineering education and innovation.

• Low Power Digital Circuits
• Soft Error Resilient Circuits
• Integrated Circuit Design
• +۴ مورد دیگر

Adrian Hilton is a Professor of AI and Computer Vision at the University of Surrey, UK. He serves as the Founding Director of the Surrey Institute for People-Centred AI and Director of the Centre for Vision, Speech and Signal Processing. His research focuses on advanced fields such as 4D Vision, Computer Graphics, and AI-driven Digital Doubles. He holds prestigious fellowships including Fellow of the Royal Academy of Engineering, IET Fellow, and IAPR Fellow. His work spans interdisciplinary areas like Virtual/Augmented Reality, Light Fields, and Audio-Visual Signal Processing. No specific grants, students, or recent publications are detailed in the provided text, but his leadership roles highlight significant contributions to AI and computer vision research.

• Computer Vision
• Machine Learning
• 4D Vision
• +۹ مورد دیگر

Manuel Rosa Zurera is a Full Professor at the Universidad de Alcalá, specializing in Signal Theory and Communications. He leads the AES3 research group focused on Acoustic and Electromagnetic Smart Sensor Networks and Signal Processing. His research emphasizes machine learning applications in audio analysis, biomedical signal processing, and passive radar systems. Dr. Rosa holds a PhD from Universidad de Alcalá (1999), supervised by Francisco López Ferreras. Research Interests : Dr. Rosa’s work spans acoustic signal localization, UAV detection, emotion recognition via speech analysis, and evolutionary studies of hominin auditory systems. His innovations include robust detection algorithms for passive radar, energy-efficient anger detection systems, and age/gender classification from speech using neural networks. He has pioneered acoustic sensor networks for urban security and biomedical diagnostics. Key Contributions : Over 150 peer-reviewed articles since 1999 demonstrate his expertise in signal processing for aerospace flutter analysis, real-time violence detection in smart cities, and 3D reconstruction of Neanderthal auditory capacities. His work bridges theoretical signal processing with practical applications in healthcare, surveillance, and evolutionary anthropology. Labs/Teams : Directs the AES3 group and collaborates on EU-funded projects like DVB-T radar systems and acoustic drone detection initiatives. Active in designing microphone arrays for hearing aids and wireless sensor networks.

• Signal Processing
• Machine Learning
• Acoustic Engineering
• +۵ مورد دیگر

Auxiliadora Sarmiento Vega is a full professor at the University of Seville 's School of Engineering within the Department of Signal Theory and Communications . With over two decades of research experience, her work bridges audio signal processing and biomedical applications, focusing on blind source separation, entropy-based methods, and machine learning for healthcare diagnostics. Research Pillars : Audio source separation, biomedical signal/image analysis, and virtual reality integration Key Projects : ACACIA (Signal Analysis), NEUBIAS (Bioimage Analysts Network), and multiple NIH-funded biomedical imaging initiatives Academic Contributions span 15+ years, with groundbreaking work in: Alpha-Beta divergence clustering algorithms EEG processing for motor imagery BCI systems Automated breast cancer grading from histological images Glaucoma and diabetic retinopathy diagnostics via retinal image analysis Virtual reality platforms for emotion analysis research She actively collaborates with institutions like the IEEE Women in Engineering (Spanish section secretary) and NEUBIAS network , while mentoring through outreach programs like g4g Day that empower young women in STEM.

• Audio Source Separation
• Biomedical Signal Processing
• Machine Learning
• +۵ مورد دیگر

Roberto Rodriguez-Echeverria is an Associate Professor at the Computer Languages and Systems Department of the Universidad de Extremadura (Spain). He leads the Applied Informatic Technology Institute and co-founded MetrikaMedia, a SaaS company for multimedia content measurement. His research focuses on software engineering, model-driven engineering, machine learning, and legacy system modernization. Education: Bachelor and Master in Computer Science (2000), Universidad de Extremadura Master on Education and IT (2012), Universitat Oberta de Catalunya PhD in Computer Science (2014), Universidad de Extremadura Research interests include data-driven software development, medical image segmentation using SAM models, and educational technology applications like chatbot performance analysis in exams. He explores reproducible data science workflows and hybrid recommendation systems for media. Recent work highlights include advancing loss function analysis for COVID-19 lung scans and developing cost-efficient medical image segmentation techniques leveraging SAM's zero-shot capabilities. He also studies the impact of AI tools like ChatGPT on academic assessment methods. His contributions span over 50 publications since 2004, with recent focus on smart city applications, cloud cost estimation, and cooperative social process modeling. Rodriguez-Echeverria's work bridges theoretical computer science with practical industry solutions through his lab's applied research initiatives. Labs/Teams: Applied Informatic Technology Institute (Director) i3 Lab (Affiliated)

• Software Engineering
• Model-Driven Engineering
• Machine Learning
• +۵ مورد دیگر

Juan D. Gutiérrez is an Assistant Professor in the Department of Computer Languages and Systems at Universidade de Santiago de Compostela. His research focuses on applying Artificial Intelligence to diverse domains, particularly optimizing foundation models for specialized tasks and advancing medical image segmentation techniques. He holds a PhD in Modeling and Experimentation in Science and Technology (2022) from Universidad de Extremadura, following bachelor's and master's degrees in Computer Science (2010-2016). Bachelor in Computer Science, Universidad de Extremadura (2010) Master in Computer Science, Universidad de Extremadura (2013) Master's in Secondary Education with Computer Science Specialization, Universidad de Extremadura (2016) PhD in Modeling and Experimentation in Science and Technology, Universidad de Extremadura (2022) His work emphasizes low-cost AI optimizations and reproducible data science practices. Notable contributions include leveraging SAM models for medical image segmentation and rethinking audio classification using EnCodec's latent space. He has authored over 20 computer science books and translated 10 technical works into Spanish. Recent research trends highlight AI-driven healthcare solutions, loss function analysis in medical imaging, and frameworks for reproducible data analysis. His JENUI 2023 Best Paper Award recognized advancements in SAM-based segmentation techniques. Recipient of JENUI 2023 Best Paper Award Teaching responsibilities include courses like 'Technological Tools for Business' and 'Digital Technologies for Cultural Management.' Active in academic advising and curriculum development, he emphasizes hands-on learning through collaborative projects. Current initiatives explore model-driven reproducibility standards and hybrid recommender systems for media content.

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +۴ مورد دیگر

Dr. Sergi Jordà is a Senior Researcher and Associate Professor at the Music Technology Group of Universitat Pompeu Fabra (UPF) in Barcelona. He obtained his B.S. in Fundamental Physics (1986) and PhD in Computer Science and Digital Communication (2005) from UPF. He leads the Music & Advanced Interaction (MAIn) team and teaches courses in Computer Music, Audio Signal Processing, Human-Computer Interaction (HCI), and Interactive Media. In 2011, he joined the tenure-track faculty at UPF. Research Interests Jordà's research focuses on the intersection of Human-Computer Interaction (HCI) and tangible musical interfaces , including applications in education, collaborative music creation, and brain-computer interfaces . His work explores how tabletop interfaces and visual feedback can enhance intuitive instrument design and real-time performance. He is best known for co-inventing the Reactable , a tangible tabletop musical instrument that gained global recognition after being used by Icelandic artist Björk in her 2007-08 world tour. Scientific Awards Prix Ars Electronica Golden Nica (2008) MIDEM Hottest Music Biz Start-Up Award (2008) Yellow Pencil, D&AD Design Awards (2008) Rolling Stone Magazine's Hot Instrument of the Year (2007) Premi Ciutat de Barcelona (1999, 2007) Möbius International Award (2001) Innova Business Ideas Contest (2008) Projects and Grants He has participated in over 30 international scientific committees, including chairing TEI'13 (Tangible, Embedded and Embodied Interaction Conference) . Jordà has secured funding from the European Commission and Spanish government for six research projects, two as Principal Investigator (IP). In 2009, he co-founded the spin-off company Reactable Systems , which launched Reactable Mobile for iOS devices in 2010.

• Human-Computer Interaction
• Tangible Interfaces
• Musical Interaction
• +۵ مورد دیگر

Yolanda Castillo Escario is a researcher at the Institute for Bioengineering of Catalonia , specializing in the Biomedical Signal Processing and Interpretation group. Her work focuses on leveraging smartphone sensors and machine learning to assess sleep disorders, trunk function in spinal cord injury patients, and respiratory diagnostics through cough acoustics. Key research areas: Sleep-disordered breathing, Spinal cord injury rehabilitation, Smartphone-based health monitoring Recent publications highlight her contributions to deep learning for apnea detection , accelerometry for sleep position analysis , and acoustic profiling of respiratory diseases . Her interdisciplinary approach bridges biomedical engineering, neuroscience, and mobile health technologies. As part of IBEC's collaborative initiatives, she works with hospitals and industry partners to translate research into practical applications. Her projects include clinical trials for spinal cord injury rehabilitation and epidemiological studies on respiratory disease patterns.

• Biomedical Signal Processing
• Sleep Disorders
• Spinal Cord Injury
• +۳ مورد دیگر

Roberto Gil Pita is a Professor at the University of Alcalá (Spain), affiliated with the Department of Signal Theory and Communications. He leads the AES3 research group focusing on acoustic and electromagnetic smart sensor networks and signal processing applications. His doctoral work (2006) centered on radar target classification using statistical and AI methods under the supervision of Dr. Manuel Rosa Zurera. His research spans signal processing, machine learning, and their applications in aerospace, biomedical systems, and smart cities. Key areas include UAV detection, emotion recognition from speech, and acoustic localization using microphone arrays. His academic background includes a doctorate from the University of Alcalá and extensive contributions to wireless acoustic sensor networks, hearing aid signal processing, and bioimpedance spectroscopy. He has developed energy-efficient algorithms for real-time audio analysis, acoustic violence detection systems, and robust methods for speech enhancement in noisy environments. His work bridges theoretical signal processing with practical engineering solutions for defense, healthcare, and urban monitoring. Research interests extend to aeroelastic flutter analysis in aviation, wearable biomedical sensors for stress assessment, and data-driven approaches for sound environment classification. He has pioneered the use of deep learning in flutter testing and acoustic event classification, contributing to datasets like REALISED for benchmarking machine learning models. Notable projects include acoustic localization of drones using microphone arrays, real-time emotion detection systems, and collaborative research in smart healthcare technologies. His work emphasizes computational efficiency and energy conservation, particularly for embedded systems and battery-operated devices.

• Signal Processing
• Acoustic Sensor Networks
• Machine Learning
• +۳ مورد دیگر