جست‌وجوی استاد و پژوهشگر

Andrew Markhamمشاهده پروفایل

استاد

• Sensors and Sensor Networks
• Signal Processing
• Machine Learning
• +۶ مورد دیگر

Andrew Markham is a Professor of Computer Science at the University of Oxford , affiliated with Kellogg College . He leads a research group focusing on Cyber Physical Systems (CPS) , specializing in sensors, signal processing, and machine learning to enable machines to better perceive the physical world. His work emphasizes cross-disciplinary collaboration, notably in wildlife tracking and indoor positioning systems. He has held roles as a Postdoctoral Fellow (2008-2012), Associate Professor (2013), and Full Professor (2021). Education : PhD in Electrical Engineering (University of Cape Town, 2008), BSc (Hons) in Electrical Engineering (2004). Research Interests : Tracking and localization in GPS-denied environments (e.g., underground, indoors), magneto-inductive systems, physics-informed machine learning, and data-driven approaches for noisy sensor data. His projects include wildlife monitoring via wireless sensor networks and mmWave radar for human motion capture. Key Projects : CARACAL acoustic monitoring system, mmPoint dense human tracking, and RandLA-Net for large-scale point cloud segmentation. His work spans robotics, environmental sensing, and biomedical applications. Advising & Grants : Supervises over 30 students and collaborates with industrial partners. Research teams include Cyber Physical Systems, Autonomous Ubiquitous Sensing, and Wildlife Monitoring initiatives. Labs/Teams : Leads the CPS research group, focusing on sensor networks, inertial navigation, and multimodal fusion systems. Collaborates with zoology and earth science disciplines on applied projects.

Shinji Watanabeمشاهده پروفایل

دانشیار

• Automatic Speech Recognition
• Speech Enhancement
• Spoken Language Understanding
• +۳ مورد دیگر

Shinji Watanabe is an Associate Professor at Carnegie Mellon University's Language Technologies Institute and a Courtesy Professor in the Electrical and Computer Engineering department. He holds a Ph.D. (Dr. Eng.) from Waseda University, Japan, and has held research roles at NTT Communication Science Laboratories, Mitsubishi Electric Research Laboratories (MERL), and Johns Hopkins University. His research focuses on automatic speech recognition, speech enhancement, and machine learning for speech processing. Watanabe has published over 300 peer-reviewed papers and received the Best Paper Award at IEEE ASRU 2019. His work emphasizes robust speech processing in challenging environments, multilingual models, and neural audio codecs. He leads the ESPnet toolkit development for end-to-end speech processing systems and contributes to technical committees like IEEE SLTC and APSIPA SLA. Recent research trends include streaming speech systems, universal speech enhancement (URGENT challenges), and fusion of discrete speech units with self-supervised representations. He explores scalable speech foundation models through benchmarks like ML-SUPERB 2.0 and investigates cross-modal audio-visual processing in challenges like MISP 2025. Education : B.S., M.S., Ph.D. (Waseda University) Affiliations : CMU Language Technologies Institute, CMU ECE, Former roles at MERL and Johns Hopkins Key Projects : ESPnet, OpenWhisper-Style Models, URGENT Challenge Frameworks

Mark Bockoمشاهده پروفایل

استاد

• Audio and Acoustic Signal Processing
• Computer Audition
• Sensors and Transducers
• +۳ مورد دیگر

Mark Bocko is a Distinguished Professor of Electrical and Computer Engineering at the University of Rochester, affiliated with the Hajim School of Engineering & Applied Sciences. He holds roles as Director of the Center for Emerging and Innovative Sciences (CEIS) and Director of Audio & Music Engineering. He earned his PhD in Physics from the University of Rochester in 1984, focusing on gravitational wave detectors. His research spans audio signal processing, sensors, superconductivity, and quantum computing. Notable contributions include flat-panel loudspeaker development, non-contact ECG sensors, and quantum coherence studies in Josephson junctions. Research interests include audio and acoustic signal processing, computer audition, and sensor technologies. His work integrates interdisciplinary approaches, combining electrical engineering, physics, and computer science. Awards include the 2012 Goergen Award for Teaching and Mercer Brugler Distinguished Teaching Professor (2008–2011). Recent publications address modal crossover networks for loudspeakers, vibrational touch sensing, and room impulse response modeling. He has advised PhD students on topics like spatial audio rendering and musical vibrato analysis. His labs focus on advancing audio engineering and smart sensor systems through collaborative industry partnerships.

• Digital Music
• Human-Machine Interaction
• Electroacoustic Composition
• +۳ مورد دیگر

Dominic Thibault is an Assistant Professor at the Faculty of Music, Université de Montréal . His research-creation explores human-machine interaction in musical contexts, focusing on embodied cognition through electroacoustic compositions, audiovisual performances, and musical software development. Co-director, Laboratoire Formes·Ondes Active member, CIRMMT (Centre for Interdisciplinary Research in Music Media and Technology) Research axis leader, Expanded Musical Practice (CIRMMT) Member, Québecor Millénium entrepreneurship committee Scientific committee member, ACFAS

Jesper Rindom Jensenمشاهده پروفایل

دانشیار

• Audio Signal Processing
• Artificial Intelligence
• Speech Enhancement
• +۱۲ مورد دیگر

Jesper Rindom Jensen is an Associate Professor in the Department of Electronic Systems at Aalborg University, Denmark, under the Technical Faculty of IT and Design. He is the Head of the Audio Analysis Lab, a leading research group in audio signal processing, since 2023. His work bridges theoretical signal processing and practical applications in artificial intelligence and audio systems. Full Name: Jesper Rindom Jensen Institution: Aalborg University School: The Technical Faculty of IT and Design Department: Department of Electronic Systems Research Lab: Audio Analysis Lab Email: jrj@es.aau.dk Office: Fredrik Bajers Vej 7B, B5-206, 9220 Aalborg Øst, Denmark Education: M.Sc. in Electronic Systems, Aalborg University (cum laude, 2009) Ph.D. in Signal Processing, Aalborg University (2012) Research Interests: Jesper Rindom Jensen's research centers on audio signal processing, with a strong emphasis on artificial intelligence, speech enhancement, noise reduction, beamforming, and multichannel systems. His work applies to diverse domains including robot and drone audition, spatial audio, and active noise control. He develops novel filtering techniques, including variable span linear filters and harmonic beamformers, to improve speech quality and intelligibility in noisy and reverberant environments. Publication Trends: His recent publications (2023–2025) show a strong trend toward integrating deep learning with classical signal processing, particularly in direction-of-arrival estimation, underwater acoustics, and robust multichannel systems. There is a clear focus on real-world applications, including sound zone control, active noise control, and limited-data scenarios using knowledge distillation. His work consistently emphasizes robustness, efficiency, and practical deployment. Scientific Awards and Recognition: AAU Talent for emerging research leaders Recipient of a competitive postdoc grant from the Danish Independent Research Council Advising and Grants: Jesper has supervised multiple PhD and master’s students, including Nørholm, Karimian-Azari, Zhang, and Wang. He has led significant research projects such as 'Sound Processing for Robots and Drones' (2018–2020) and participated in others related to joint audio-visual tracking and speech enhancement. His research has been supported by national funding bodies, reflecting its innovation and impact. Labs and Teams: He is a founding and core member of the Audio Analysis Lab at Aalborg University, which focuses on cutting-edge audio signal processing and AI-driven solutions. The lab fosters interdisciplinary collaboration and has produced numerous publications, datasets, and real-world applications. Jensen’s leadership since 2023 underscores his pivotal role in shaping the lab’s research direction.

Thomas Hermannمشاهده پروفایل

پژوهشگر

• Auditory Data Science
• Interactive Sonification
• Smart Environments
• +۵ مورد دیگر

Dr. rer. nat. Thomas Hermann is a faculty member at Bielefeld University's Faculty of Engineering, leading the Ambient Intelligence Group and coordinating the Computer Science program. He specializes in sonification, auditory data science, and smart environments. Head of Ambient Intelligence Working Group Computer Science Program Coordinator Member of multiple academic advisory boards His research focuses on interactive sonification for biomedical applications, quantum systems, and smart environments. Key projects include ECG sonification for cardiac diagnosis, real-time auditory feedback in swimming, and sonic interfaces for AR cooperation. Recent publications span 2025 with Python-based sonification tools ( pya AGen ), quantum system sonification, and ST-elevation myocardial infarction monitoring. He contributes to open-access supplementary materials and interdisciplinary workshops. As a researcher , Hermann develops practical sonification frameworks like Panson for facial behavior analysis, CardioScope for portable ECG monitoring, and Base Cube One for smart environments. His work bridges academic research with industry applications.

Lin Wangمشاهده پروفایل

مدرس

• Machine Learning
• Audio-Visual Signal Processing
• Robotic Perception
• +۳ مورد دیگر

Dr. Lin Wang is a Lecturer in Applied Data Science and Signal Processing at Queen Mary University of London (QMUL), affiliated with the School of Electronic Engineering and Computer Science. He leads the Machine Listening Lab and is a member of the Centre for Multimodal AI, Centre for Intelligent Sensing (CIS), and Institute of Coding (IoC). His research focuses on audio-visual signal processing, robotic perception, and machine learning, with applications in healthcare, drone-based sensing, and human activity recognition. Dr. Wang holds a PhD from Dalian University of Technology and has held postdoctoral positions at QMUL, the University of Sussex, and the Alexander von Humboldt Foundation in Germany. Education and Roles: PhD in Signal Processing, Dalian University of Technology (2010) Postdoc at Queen Mary University of London (2014–2017) Postdoc at University of Sussex (2017–2018) Alexander von Humboldt Fellow at University of Oldenburg (2011–2013) Fellow of the Higher Education Academy (UK) Research Interests: Audio-visual signal processing for drones and wearable devices Machine listening and robotic perception Machine learning for healthcare and environmental monitoring Human activity recognition using multimodal sensors Awards and Grants: Early Career Champion on AI&Data, UK Acoustics Network Outstanding Article Award, Frontiers in Computer Science (2022) EPSRC grant: Bioacoustic Monitoring Using Drones (£46,821, 2022–2023) Innovate UK grant: Music Source Separation (£48,144, 2024–2025) Teaching and Students: Dr. Wang teaches Applied Statistics , Website Design and Authoring , and Machine Learning for Visual Data Analysis . He supervises PhD students including Ashish Alex (speech separation), Michael Clayton (drone audition), and Dmitrii Mukhutdinov (audio-visual processing). Labs and Teams: He co-leads the Machine Listening Lab and is part of the Centre for Multimodal AI, focusing on interdisciplinary projects in robotics, acoustics, and AI.

Annie Mahtaniمشاهده پروفایل

استاد

• Electroacoustic Music
• Acousmatic Composition
• Multichannel Audio
• +۶ مورد دیگر

Professor Annie Mahtani is a Professor of Electroacoustic Composition and Practice at the University of Birmingham's Department of Music. She holds a BMus (Hons), MA, MPhil, and PhD from the University of Birmingham and Birmingham City University. Her work focuses on electroacoustic music, acousmatic composition, multichannel audio, spatialisation, and field recordings, with significant contributions to site-specific installations and cross-disciplinary collaborations. She co-directs the SOUNDkitchen collective and serves on key boards such as the British ElectroAcoustic Network (BEAN) and the British Section of ISCM. Her research explores the sonic identity of environmental sounds, large-scale multichannel composition, and ambisonic audio techniques. As a performer with BEAST (Birmingham Electroacoustic Sound Theatre), she develops live acousmatic performances and soundwalks. Recent projects include Becoming Tree (an immersive audio retelling of a literary work) and Minimum Monument , performed at Birmingham Hippodrome. She actively collaborates with dance and theatre companies like Rosie Kay Dance Company. Professor Mahtani teaches undergraduate and postgraduate modules in electroacoustic composition and is involved in admissions and curriculum leadership. Her works have been performed globally in festivals like Klang! Électroacoustique and Sound + Environment, showcasing her innovative contributions to contemporary music and sound art.

Henrik von Colerمشاهده پروفایل

استادیار

• Music Technology
• Spatial Audio Systems
• Live Electronics
• +۳ مورد دیگر

Henrik von Coler is an Assistant Professor at Georgia Institute of Technology's School of Music within the College of Design. His work bridges engineering, electronic music, and empirical research, focusing on spatial audio systems, live electronics, and human-computer interaction in musical contexts. He joined Georgia Tech in 2023 after serving as director of the TU Studio for Electronic Music at Technische Universität Berlin from 2015 to 2023, where he founded the Electronic Orchestra Charlottenburg (EOC) to explore live electronic ensembles in multichannel environments. His research emphasizes the integration of sound, space, and HCI to enhance compositional and performative expressiveness. Notable projects include immersive audio installations, virtual instrument design, and AI-assisted composition. Coler has performed globally on immersive audio systems and curated international concerts. His technical contributions span spatial sound synthesis algorithms, networked music systems, and real-time signal processing tools. Key areas of exploration include volumetric music performances in metaverse environments, hybrid spatial interaction via ARCube, and statistical models for spectral synthesis. He has developed open-source systems like Orchestra (for metaverse performances) and SPRAWL (for ensemble interaction). Coler’s work often combines empirical research with artistic practice, aiming to redefine the boundaries of live electronic music through technological innovation. His academic output spans over 30 peer-reviewed articles since 2011, with recent focus on metaverse applications, AI-human collaboration, and immersive audio design. While no formal awards are listed, his leadership roles and project outcomes highlight significant contributions to music technology and spatial audio engineering.

Fernando Lopez-Lezcanoمشاهده پروفایل

مدرس

• Computer Music
• Spatial Audio
• 3D Sound Diffusion
• +۶ مورد دیگر

Fernando Lopez-Lezcano is a Lecturer at Stanford University's Center for Computer Research in Music and Acoustics (CCRMA) where he has been working since 1993. His work combines music composition, electronic engineering, and programming with a focus on spatial audio and sound diffusion technologies. He was the Edgar Varese Guest Professor at TU Berlin during the Summer of 2008 and is the 2014 winner of Stanford's Marsh O'Neill Award for Exceptional and Enduring Support of Stanford University's Research Enterprise. Lopez-Lezcano's research interests center on computer music, spatial audio technologies, and sound diffusion systems. He has pioneered work in High Order Ambisonics (HOA), developing novel decoders and reverberation architectures for immersive sound environments. His work on the SpHEAR Project has created innovative 3D-printed soundfield microphone arrays, while his development of the GRAIL (Giant Radial Array for Immersive Listening) has revolutionized concert speaker arrays for HDLAs (High Density Loudspeaker Arrays). He has also created numerous open-source tools and software environments for spatial sound composition and diffusion. His recent creative output demonstrates a consistent exploration of 3D sound spatialization, modular synthesis, and interdisciplinary collaborations. Across his compositions, he frequently integrates custom-built hardware like his modular synthesizers (including the famous 'El Dinosaurio' built in 1980-81) with sophisticated software environments written in SuperCollider. His work often bridges acoustic and electronic sound sources, creating rich spatial experiences that explore the relationship between technology and artistic expression. Among his notable achievements is the 2014 Marsh O'Neill Award, recognizing his exceptional support of Stanford's research enterprise. This prestigious award was inspired by Marsh O'Neill, Associate Director of the W.W. Hansen Laboratories, and honors outstanding staff members who support faculty research activities. Lopez-Lezcano has mentored numerous students in the development of musical instruments and performance systems, most notably the 'Ensemble AnaLocos' (Analógicos Locos or 'Crazy Analogs') which created the 'Noise Toaster' synthesizers. He has also developed important infrastructure for CCRMA including 'Planet CCRMA,' a collection of open-source audio software for Linux. His teaching includes the 'Sound in Space' course (Music 222), which covers historical background, techniques, and theory on the use of space in music composition and diffusion. He directs the CCRMA Stage concerts and has been instrumental in developing CCRMA's spatial audio infrastructure, including the GRAIL system used in Bing Concert Hall. His work with the SpHEAR Project has advanced 3D sound recording techniques, while his collaborations with performers like Michiko Theurer (violin) and Chris Chafe (celletto) have produced innovative interdisciplinary performances.

Swati Chandnaمشاهده پروفایل

مدرس ارشد

• Statistics
• Data Science
• Network Theory
• +۳ مورد دیگر

Dr. Swati Chandna is a Senior Lecturer at the School of Computing and Mathematical Sciences, Birkbeck, University of London. She holds an honorary position as an Honorary Lecturer in Statistics at University College London (UCL) from January 2023 to January 2026. She earned her PhD in Statistics from Imperial College London in 2013. Her research focuses on statistical modeling, network analysis, and bioinformatics, with notable contributions to stochastic networks, single-cell genomic data analysis, and complex-valued signal processing. Teaching responsibilities include modules such as Bayesian Methods, Analysing Data, Statistical Analysis, and Project Applied Statistics. She serves as Admissions Tutor for Graduate Certificate and Diploma in Statistics for Data Science and as School Ethics Lead at Birkbeck. Her work bridges theoretical statistics with practical applications in genomics, environmental modeling, and biomedical research. Dr. Chandna’s recent research explores topics like covariate-driven network estimation, stochastic modeling of genomic data, and bootstrap techniques in source separation. Her publications reflect interdisciplinary collaboration across statistics, computer science, and life sciences.

Neil Leonardمشاهده پروفایل

استاد

• Sound Art
• Experimental Music
• Multimedia Performance
• +۷ مورد دیگر

Neil Leonard is a Professor at Berklee College of Music and the founding Artistic Director of the Berklee Interdisciplinary Arts Institute. He is affiliated with the Department of Electronic Production and Design (EPD) within the College of Arts and Sciences. His artistic and academic work bridges music, technology, and interdisciplinary collaboration. Ph.D. or equivalent terminal degree in composition or sound art (inferred from academic rank and output) Extensive international residency and fellowship experience Leonard's research and artistic practice centers on sound art, electroacoustic composition, and multimedia performance . He explores immersive multichannel audio, live electronics, and collaborations with visual artists, dancers, and filmmakers. His work investigates the resonance of cultural memory, urban soundscapes, and historical acoustics. He integrates technology and philosophy, often drawing from astronomy, Plato, and intercultural exchange. His recent works, including Matanzas Sound Map (Tate Modern, 2025), Sonance for the Precession , and For Kounellis , reflect a trend toward site-specific, durational sound installations that merge scientific concepts with poetic expression. These pieces utilize field recordings, algorithmic processing, and spatial audio to create immersive environments. His scientific and artistic honors include: Fulbright Specialist Award (2016) Distinguished Faculty Award, Berklee (2011) International CubaDisco Award (2015) Rauschenberg Residency (2016) Sacatar Institute Fellow (2023) MIT Art, Culture, and Technology affiliate U.S. State Department Fulbright Specialist Roster (2013–present) Leonard is deeply committed to mentoring students, particularly in refining portfolios and developing lifelong learning strategies. He emphasizes time management as a compositional skill and encourages adaptability in the evolving music industry. He has led major collaborative projects such as The Berklee Sessions with Robin Rimbaud (Scanner) and has performed with renowned artists including Vijay Iyer, Rudresh Mahanthappa, and Los Muñequitos de Matanzas. He co-founded and leads the Berklee Interdisciplinary Arts Institute , fostering cross-departmental collaborations and innovative performance practices. His work continues to be exhibited globally, from Documenta and Venice Biennale to Mass MoCA and the Peabody Essex Museum.

• Signal Processing
• Machine Learning
• Audio Engineering
• +۷ مورد دیگر

Archontis Politis is an Assistant Professor in the Department of Computing Sciences at Tampere University's Faculty of Information Technology and Communication Sciences. His research focuses on signal processing, machine learning, and their applications in audio engineering, particularly in spatial audio, sound source separation, and parametric audio coding. He explores topics such as Ambisonics, reverberation control, and neural network-based approaches for audio processing. His work emphasizes spatial audio reproduction, including six degrees of freedom (6DOF) rendering, microphone array processing, and efficient compression techniques for higher-order Ambisonics. He also investigates sound event localization and detection, leveraging machine learning for real-world acoustic scenarios. His contributions span theoretical advancements in spherical harmonics and practical implementations of spatial audio systems. Recent research highlights include developing datasets for music source separation, improving synthetic-to-real generalization in classical music, and creating neural encoding models for irregular microphone arrays. His methodologies often integrate deep learning with traditional signal processing to address challenges in multi-speaker environments and dynamic acoustic scenes.

Ryo Ikeshiroمشاهده پروفایل

استادیار

• Sound Art
• Sonification
• Computational Creativity
• +۳ مورد دیگر

Ryo Ikeshiro is an Assistant Professor at the School of Creative Media, City University of Hong Kong, and co-director of the spatial audio art/research unit SoundLab. His work bridges sound art, computational creativity, and cultural studies through immersive installations, algorithmic audio-visual systems, and sonification techniques. PhD in Creative Practice (Goldsmiths, University of London) MPhil in Music (University of Cambridge) BMus (King's College London) Ikeshiro's research interrogates the materiality of sound through: Multichannel Ambisonics and directional audio Neural network-driven temporal dislocation Sonification of climate data and historical soundscapes Machine learning for artistic interpretation Interplay of identity and technology East Asian ideophonic traditions His 2010-2024 publications and installations reveal cross-disciplinary engagement with: Fractal mathematics in audiovisual art Algorithmic composition systems Interactive installation technologies Sonic cartography Historical memory in sound Collaborative research frameworks SoundLab, which he co-directs, develops spatial audio research at the intersection of: Technical innovation Cultural representation Experimental pedagogy Public engagement International artistic exchange Practice-based research

Herbert Buchnerمشاهده پروفایل

پژوهشگر

• Digital Signal Processing
• Acoustics
• Speech Recognition
• +۹ مورد دیگر

Herbert Buchner is a researcher affiliated with the University of Cambridge in the Information Engineering Division , focusing on Machine Learning for Signal Processing and Human-Machine Interfaces . Research Interests : Acoustic scene analysis, biomedical interfaces, haptic systems, wave-domain adaptive filtering, and sensor networks. Applications : Speech recognition, wavefield synthesis, active noise control, and full-duplex communication systems. His work explores TRINICON (a framework for broadband adaptive MIMO filtering), blind source separation, and wave-domain filtering, emphasizing theoretical rigor and real-time implementation. Key Awards : Best Paper Award at ITG Conference on Speech Communication (2008) Best Student Paper Award at IEEE Intl. Workshop on Acoustic Echo and Noise Control (2001) Publications highlight 15 recent articles in areas like: Wave-Domain Adaptive Filtering Blind Source Separation for Convolutive Mixtures Robust Extended Multidelay Filters Multichannel Acoustic Echo Cancellation Active Room Compensation Biomedical Signal Processing