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Jordan CheerView profile

Professor

• Active Noise Control
• Active Vibration Control
• Smart Structures for Noise and Vibration Control
• +3 more

Professor Jordan Cheer holds a Royal Academy of Engineering Research Chair in Smart Acoustic Control Technologies at the University of Southampton's Institute of Sound and Vibration Research (ISVR). His research focuses on active control of noise and vibration, including smart structures and metamaterials. He is an Associate Editor for Journal of the Acoustical Society of America and Subject Editor for Journal of Sound and Vibration . Education: BMus (Tonmeister) in Music and Sound Recording, University of Surrey (2008) MSc in Sound and Vibration, ISVR, University of Southampton (2009) PhD in Active Control of Automobile Cabin Acoustics, ISVR, University of Southampton (2012) Research Interests: Active Noise/Vibration Control, Smart Structures, Acoustic Black Holes, and Metamaterials. Current projects include the BAE Systems-funded Smart Acoustic Control Technologies Chair and the IN-NOVA MSCA Doctoral Network. Recent Work Trends: Publications emphasize neural network controllers, head-tracking systems, and metamaterial applications. Patents focus on vibration damping and acoustic control devices. Awards: Royal Academy of Engineering Research Chair (2024) Grants & Labs: Leads projects funded by EPSRC, MOD, and industry partners. Collaborates with teams like the Southampton Marine and Maritime Institute and the Centre for Defence and Security Research.

Sean AndersonView profile

Senior Lecturer

• Bioinspired Robotics
• Adaptive and Optimal Control
• System Identification
• +3 more

Dr Sean Anderson is a Senior Lecturer at the Department of Automatic Control and Systems Engineering , University of Sheffield , with over 15 years of experience in interdisciplinary research spanning robotics, control systems, and computational biology. He earned his MEng and PhD from the University of Sheffield, focusing on control systems and chemical engineering. Education: MEng in Control Systems Engineering, University of Sheffield (2001) PhD in Chemical and Process Engineering, University of Sheffield (2005) Research Interests include: Bioinspired robotics Adaptive and optimal control in biological systems Nonlinear system identification Computational neuroscience Acoustic and visual sensor fusion for localization His recent publications highlight innovations in robotic localization in hazardous environments, interpretable deep learning for control systems, acoustic sensing technologies, and data-driven modeling of complex systems. Key projects involve autonomous navigation in pipe networks, turbulence modeling, and biomedical signal processing. Grants and Funding: He has secured major grants from EU H2020 (£4M), EU FP7 (£2.9M), and EPSRC (£5.7M), focusing on bioinspired control algorithms, robotic safety, and infrastructure assessment. Teaching: He leads the ACS61011 Deep Learning module, emphasizing practical applications in robotics and signal processing.

Jon BarkerView profile

Professor

• Noise-Robust Speech Processing
• Machine Listening
• Computational Modeling of Human Hearing
• +4 more

Professor Jon Barker is a faculty member at the University of Sheffield , where he holds a Personal Chair in the School of Computer Science . He leads the Speech and Hearing (SpandH) research group and co-founded the CHiME international workshop series on robust speech recognition. Education : PhD in Computer Science (University of Sheffield, 1999); BA in Electrical and Information Sciences (Cambridge University). Research Focus : His work bridges machine listening and human auditory perception , with key contributions to noise-robust speech recognition , speech intelligibility prediction , and hearing aid signal processing for speech and music. Recent projects include the Clarity Challenges and Cadenza Challenges , large-scale machine learning initiatives to improve accessibility for hearing-impaired users. Publication Trends : Recent articles emphasize machine learning for hearing aid optimization , dysarthric speech recognition , audio-visual integration , and music demixing algorithms . Collaborations span speech processing, psychoacoustics, and biomedical engineering. Scientific Awards : EURASIP Best Paper Award (2009) ISCA Best Paper Award (2008) Grants and Leadership : He has secured major EPSRC grants including EnhanceMusic (2022-2026) and Challenges to Revolutionise Hearing Device Processing (2019-2025). He co-led the TAPAS Marie Curie Training Network (2017-2022) and led projects like AV-COGHEAR (2015-2018) and CHiME (2009-2012). Labs and Teams : Barker collaborates closely with the Speech and Hearing Research Group and contributes to international initiatives like the CHiME Workshop . His lab develops open datasets such as the Clarity Speech Corpus and Audio-Visual Lombard Corpus .

Bruce WigginsView profile

Associate Professor

• Audio Engineering
• 3D Audio
• Ambisonics
• +5 more

Bruce Wiggins is an Associate Professor in Audio Engineering at the College of Science and Engineering. His research focuses on spatial audio technologies, including Ambisonics, binaural auralization, and 3D audio systems. Notable projects include the GASP guitar system and WHAM webcam-based head-tracked audio solutions. He has contributed to advancements in microphone array calibration, speaker array modeling, and virtual reality audio integration. His work bridges theory with practical applications in music technology and acoustic engineering. Education: PhD in Audio Engineering (2004). Research Interests: Ambisonics, spatial audio capture and reproduction, 3D audio for virtual reality, binaural rendering, and innovative musical instrument design. His work emphasizes practical implementations such as the GASP guitar system and calibration tools for low-cost microphone arrays. Article Trends: Recent publications address virtual stereo microphone techniques (2024), dynamic electrical systems (2024), and browser-based 3D audio (2023). Earlier work explores head-tracking algorithms (2016–2020) and acoustic modeling for domestic environments (2017). Grants/Advising: No explicit grants listed. Advising details unavailable but has collaborated with numerous researchers on projects like WHAM and GASP. Labs/Teams: Active in interdisciplinary teams developing spatial audio tools and instruments, including collaborations on virtual reality auralization and ambisonic guitar systems.

Philip JacksonView profile

Professor

• Machine Audition
• Audio-Visual Machine Learning
• Spatial Audio
• +9 more

Philip Jackson is a Professor in Machine Audition at the University of Surrey's Centre for Vision, Speech and Signal Processing (CVSSP) within the School of Computer Science and Electronic Engineering. His research focuses on audio-visual machine learning, spatial audio technologies, object-based media production, and responsible AI applications. He has over 200 publications and an h-index of 30, contributing to projects like Nephthys, BALTHASAR, and SAVEE. He served as an associate editor for Computer Speech and Language and reviewer for major journals like IEEE/ACM Transactions on Audio, Speech and Language Processing. Key research interests include sound localization, audio-visual tracking, reverberation modeling, and ethical implications of AI in media. His work spans datasets such as Tragic Talkers, SurrRoom, and ForecasterFlexOBM, advancing immersive audio-visual systems and personalized media experiences. Notable projects include spatial audio reproduction for VR, parametric room acoustics, and citizen council research on algorithmic transparency. He has advised over 20 PhD/Master’s students and collaborates with industry on applications like the Catalan Pavilion's Venice Biennale installation. His grants include UK postdoctoral fellowships and leadership in EU-funded initiatives like UDRC2 and QESTRAL.

Jiahong ZhaoView profile

Lecturer

• Signal Processing
• Acoustics
• Spatial Audio
• +2 more

Dr Jiahong Zhao is a Lecturer in Acoustics at the University of Southampton. His research focuses on signal processing and audio technologies. Research interests include microphone array signal processing, spatial audio, machine learning, and computer vision. Current supervisor for PhD student Yaoxiang Yu in Engineering and Environment. Contact: Jiahong.Zhao@soton.ac.uk

Rob WorleyView profile

Research Fellow

• Robotics
• Autonomous Systems
• Sensor Networks
• +3 more

Dr. Rob Worley is a Research Fellow at the University of Sheffield’s School of Electrical and Electronic Engineering since 2022, following his PhD studies initiated in 2018. His research focuses on robot navigation and localization within buried pipe networks, with a particular emphasis on acoustic and visual sensing technologies. He leads the Pipebot Patrol project, advancing autonomous inspection systems for water and sewer infrastructure. His work integrates state estimation, artificial intelligence, and robotics to address challenges in feature-sparse underground environments. Worley’s research interests span robot localization algorithms, SLAM (Simultaneous Localization and Mapping), and sensor fusion, with applications to cylindrical pipe networks. His projects leverage cylindrical regularity and hybrid metric-topological models to enhance navigation accuracy. Notable contributions include acoustic echo localization using microphone arrays and visual SLAM techniques for sewer networks. He has published extensively on topics like error detection in particle filters and condition monitoring in underground pipes. Advising and grants: While no specific advisees are listed, his projects likely involve collaborative research teams. He has contributed to the Pipebots initiative since its inception, focusing on localization and sensing advancements. Labs/Teams: Active member of the University of Sheffield’s robotics research group, contributing to the development of autonomous inspection technologies for infrastructure maintenance.

• Computer Vision
• Robotics
• 3D Vision
• +4 more

Sangyun Shin is a Researcher in the Department of Computer Science at the University of Oxford, supervised by Professors Niki Trigoni and Andrew Markham. His work focuses on advancing object localization systems for robotics through 3D vision technologies. He specializes in integrating multimodal sensing (e.g., RGB-D cameras, acoustic arrays) to enhance robotic perception in challenging environments. His research interests include 3D motion capture for wildlife, domain-adaptive 3D detection, and self-supervised learning for nighttime vision. He has explored applications ranging from long-range wildlife tracking to autonomous drone navigation using reinforcement learning. Recent efforts emphasize sensor fusion and neural network architectures tailored for dynamic environments. Key technical contributions include the SoundLoc3D system for 3D sound localization and the WildPose framework for wildlife motion capture. His publications span topics like acoustic neural warping fields (SPEAR), spherical point cloud segmentation, and LiDAR-based object detection for urban driving. Shin's work bridges theoretical advancements in machine learning with practical robotics applications, addressing challenges such as cross-domain adaptation and low-resource sensor setups. His research has implications for autonomous systems, environmental monitoring, and human-drone interaction interfaces.

• Acoustic Signal Processing
• Speech Enhancement
• Microphone Array Processing
• +6 more

Dr Alastair Moore is a Researcher in the Dyson School of Design Engineering at Imperial College London, affiliated with the Speech and Audio Processing Laboratory. He holds a PhD from Imperial College and has industrial experience in consumer electronics. His research focuses on microphone array signal processing, speech enhancement in reverberant environments, and applications in augmented reality, hearing aids, and robot audition. Education: MEng in Electronic Engineering with Music Technology Systems (1st class) from University of York (2005); PhD in Binaural Hearing funded by France Telecom R&D (2012). Research Interests: He specializes in speech enhancement algorithms for wearable devices, binaural hearing systems, room acoustics modeling, and acoustic SLAM. His work includes developing virtual reality tools for hearing aid evaluation and room identification techniques for forensic applications. Funding: His projects are supported by EPSRC, EU FP7, Google, Reality Labs Research, and the UK Home Office. Notable grants include EPSRC EP/M026698/1: Environment-aware speech enhancement EPSRC EP/S035842/1: Binaural hearing aids with VR evaluation EU FP7/2007-2013: Robot audition using spherical microphone arrays Google: Speech dereverberation for VoIP UK Home Office: Audio forensics via room geometry inference Labs: Active member of the Speech and Audio Processing group led by Prof. Mike Brookes and Prof. Patrick A. Naylor.

Dale JohnsonView profile

Research Fellow

• Psychoacoustics
• Software Development
• Virtual Room Acoustics
• +4 more

Dale Johnson is a Research Fellow in the Department of Computer Science at the School of Computing and Engineering , University of Huddersfield. He is affiliated with the Centre for Audio and Psychoacoustic Engineering , focusing on psychoacoustics and 3D audio technology development. Research Fellow, Department of Computer Science (2025) Member, Centre for Audio and Psychoacoustic Engineering Active in open-access audio research and software tool creation His research spans Binaural Audio , Microphone Array Optimization , and Acoustic Modeling . Publications highlight expertise in Convolutional Neural Networks for spatial audio discrimination and Impulse Response Analysis for immersive environments. He contributes to datasets like 3D Microphone Array Comparison and collaborates on international acoustic projects. Recent work (2020-2022) demonstrates a focus on improving 3D Audio Perception through Virtual Room Acoustics simulations and calibration methods. Keywords include Transfer Functions , Crosstalk Reduction , and Digital Signal Processing .

Hyunkook LeeView profile

Professor

• Psychoacoustics
• Spatial Audio
• Virtual Reality
• +5 more

Hyunkook Lee is a Professor of Audio and Psychoacoustic Engineering at the University of Huddersfield , where he directs the Applied Psychoacoustics Lab (APL) and the Centre for Audio and Psychoacoustic Engineering . He joined the university in 2010 and has pioneered research in 3D audio, spatial recording, and psychoacoustic applications in virtual reality. Education: PhD in Psychoacoustics (University of Surrey, 2006) Industry Experience: Senior Research Engineer at LG Electronics Research Interests include: Psychoacoustics : Perception of height in 3D audio and interchannel crosstalk. Spatial Audio : Development of microphone arrays, panning, and upmixing techniques. Virtual Reality : Bridging XR and audio engineering for immersive experiences. Music Technology : Applications in commercial rap production and surround sound. Scientific Awards : 5 US-granted patents h-index of 14 (Scopus) Advising & Grants : Actively supervises PhD students and participates in industry-funded projects with Samsung, Volvo, and MagicBeans. His research includes a £326k grant for 3D sound in the 'Audience of the Future'.

• Acoustic Signal Processing
• Speech Processing
• Robot Audition
• +5 more

Professor Patrick Naylor is a faculty member in the Department of Electrical and Electronic Engineering at Imperial College London's Faculty of Engineering. His research focuses on acoustic signal processing, speech processing, and audio technology, with a particular emphasis on spatial audio, robot audition, and applications in human-robot interaction. His work spans theoretical advancements like polynomial eigenvalue decomposition (PEVD) and practical innovations in audio security, data augmentation, and assistive technologies for hearing aids. He leads the Speech and Audio Processing research group, affiliated with Imperial's Robotics Forum, Artificial Intelligence Network, and Natural and Machine Hearing initiatives. His research addresses challenges in multi-channel speech compression, secure audio transmission, and adaptive systems for dynamic acoustic environments. Notable projects include developing neural network-based methods for sound source localization and enhancing speech recognition for post-stroke aphasia patients. Prof. Naylor's work intersects electrical engineering, machine learning, and cognitive sciences. He has pioneered techniques for binaural speech enhancement using deep learning and contributed to standards in acoustic environment profiling. His lab's research is showcased at www.ee.ic.ac.uk/sap . His publications emphasize audio security (e.g., watermarking, privacy-preserving processing) and ambient cooperative intelligence systems. Current trends focus on explainable AI for acoustic neural embeddings and scalable microphone array processing for smart environments. His research frequently addresses real-world applications in healthcare, robotics, and telecommunications. Prof. Naylor collaborates across disciplines, integrating signal processing with robotics and clinical needs. His lab explores both foundational algorithms and deployable systems, reflecting Imperial's engineering ethos of bridging theory and practice.

• Room Acoustics Modeling
• Multichannel Audio
• Microphone Beamforming
• +5 more

Enzo De Sena is a Professor and Director of the Institute of Sound Recording (IoSR) at the University of Surrey. He holds a PhD in Electronic Engineering from King’s College London (2013) and has held postdoctoral and visiting researcher positions at institutions such as KU Leuven, Stanford University, and Aalborg University. His research focuses on room acoustics, multichannel audio systems, and spatial audio technologies, with contributions to binaural modeling, diffraction perception, and immersive audio workflows. He is a Senior Member of the IEEE and serves on editorial boards for top journals like IEEE/ACM Transactions on Audio, Speech, and Language Processing. Key research interests include: Room acoustics modeling via feedback delay networks Diffraction modeling for virtual reality environments Immersive music production workflows Perceptual evaluation of spatial audio technologies Notable achievements include the EPSRC New Investigator Award and best paper awards at WASPAA-21 and AVAR-22. His work has been showcased at venues like the National Gallery and Bell Labs. Current projects explore the intersection of machine learning with acoustics and the perceptual aspects of virtual acoustic environments. His recent publications (2023–2025) emphasize scalable acoustic modeling techniques, neural network-based diffraction approximation, and the psychological dimensions of spatial audio perception. The IoSR lab under his leadership is a hub for cutting-edge research in audio engineering and immersive technologies.

• Computer Graphics
• Machine Vision
• Artificial Intelligence
• +5 more

Dr Farshad Einabadi is a Senior Research Engineer at the Centre for Vision, Speech and Signal Processing (CVSSP) , University of Surrey, and contributes to the CoSTAR National Laboratory . His work focuses on neural rendering, real-time systems, and media personalization within the intersection of computer graphics, machine vision, and AI. Research interests include lighting/illumination applications (acquisition, modeling, rendering), virtual production tools, and industrial sensor calibration. He leads projects in next-gen UK screen technologies infrastructure (UKRI AHRC CoSTAR) and has contributed to EPSRC AI4ME and EU FP7 Dreamspace initiatives. Publications emphasize datasets like ForecasterFlexOBM (multi-view audio-visual) and 3DVHshadow , advancing human avatar rendering and cast shadow generation. He teaches AI Bootcamp for the UKRI CDT in Digital Media Inclusion and reviews for Eurographics and top-tier conferences. Industry experience includes software engineering for real-time augmented reality systems. Collaborates in labs/teams at CVSSP and CoSTAR, advancing projects in virtual production and immersive media technologies.

Qusai Al-HamdanView profile

Lecturer

• Gas Turbine Engineering
• Power Generation Systems
• Thermodynamics
• +3 more

Qusai Al-Hamdan is a Lecturer in Aeronautical Engineering at the School of Engineering, University of the Highlands and Islands. He holds a PhD in Gas Turbine Engines from the University of Hertfordshire and a BSc in Mechanical Engineering from Mu’tah University, Jordan. His research focuses on advanced gas turbine technologies, including component design, thermal efficiency optimization, and data acquisition systems for propulsion systems. Notable projects include developing a computerized static firing test cell for missile rocket engines, upgrading Mirage F1 turbojet engine test cells with real-time data systems, and designing microturbine components for high-output power generation. Al-Hamdan's work integrates mechanical engineering principles with aerospace applications, emphasizing practical solutions for energy systems and propulsion. His technical contributions span turbine component matching, compressor design, and acoustic noise mitigation in aerospace components. He teaches courses on aircraft propulsion systems, hydraulic systems, and project engineering, reflecting his expertise in both theoretical and applied aspects of aeronautical engineering.