Find Academic Supervisors

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.

• Acoustic Signal Processing
• Blind Source Separation
• Digital Signal Processing
• +6 more

Shoji Makino is a Professor at Waseda University's Graduate School of Information, Production and Systems. He has held academic and research positions at institutions such as the University of Tsukuba and NTT Communication Science Laboratories. His work spans acoustic signal processing, blind source separation, and adaptive filtering. Education: Ph.D., Tohoku University (1993.03) Mechanical Engineering, Tohoku University Graduate School of Engineering (1979.04–1981.03) Engineering, Tohoku University Faculty of Engineering (1975.04–1979.03) Research Interests: His research focuses on acoustic signal processing for speech and audio, including blind source separation (BSS) , beamforming , and adaptive filtering . He pioneered methods for solving permutation alignment in frequency-domain BSS and developed geometrically constrained ICA techniques. Scientific Awards: Hoko Award (2018.10, Hattori Hokokai Foundation) Outstanding Contribution Award of the Institute of Electronics, Information, and Communication Engineers (2018.06) IEEE Signal Processing Society Best Paper Award (2014.01) IEEE Fellow (2004.01) IEICE Achievement Award (1997.05) Committee Memberships: He has served as Chair of the IEEE CAS Society's Blind Signal Processing TC, General Chair of IEEE WASPAA2007, and Associate Editor of IEEE Trans. SAP. He is actively involved in EURASIP, APSIPA, and the Acoustical Society of Japan.

Navarun GuptaView profile

Professor

• Signal Processing
• Audio Signal Processing
• Bio Signal Processing
• +2 more

Navarun Gupta is a Professor and Chair of the Department of Electrical Engineering within the School of Engineering at the University of Bridgeport's College of Engineering, Business & Education. He holds a Ph.D. in Electrical Engineering from Florida International University (2003), complemented by an M.S. in Physics from Georgia State University (1992) and an M.S. in Electrical Engineering from Mercer University (1998). His educational credentials include: Ph.D., Electrical Engineering, Florida International University, 2003 M.S., Physics, Georgia State University, 1992 M.S., Electrical Engineering, Mercer University, 1998 Dr. Gupta's research centers on signal processing with specialized applications in audio and bio signals . His work spans: Digital Signal Processing for mobile and biomedical applications Pattern Recognition in biosignals (e.g., meditation impact on brain activity) Audio Spatialization and 3D sound modeling using anthropometric data Millimeter-wave propagation for 5G networks Biomedical case studies on electrical burns and respiratory flow dynamics Neuroscience applications in problem-solving and concentration His publication trends (2018-2020) emphasize biomedical signal classification, cloud security protocols, and wireless propagation modeling, demonstrating cross-disciplinary impact in healthcare and communications. Earlier works (2000-2016) established foundational contributions in audio spatialization, brain signal analysis, and biomedical engineering case reports. No scientific awards are documented in his current profile. Dr. Gupta has secured significant research funding including: National Science Foundation grant ($192,347, 2014) as Co-PI for teacher fellowship programs in urban schools United Illuminating Company grant ($11,020, 2018) as Co-PI for energy loss analysis Department of Education grant (2014) as Co-PI for aerospace/hydrospace curriculum development ENGAGE mini-grant ($2,000, 2013) as PI for engineering education initiatives As Department Chair, he leads interdisciplinary collaborations in biomedical signal processing and wireless communications, with research directly impacting healthcare monitoring systems, audio engineering, and electrical safety standards through industry partnerships.

Pierrick LottonView profile

Research Professor

• Electroacoustics
• Thermoacoustics
• Audio Transducers
• +4 more

Pierrick Lotton serves as a CNRS Research Director at Le Mans University's Institute of Acoustics (LAUM), a joint research unit between CNRS and the university. He leads critical work within LAUM's Transducers team, focusing on fundamental and applied research in electroacoustics and thermoacoustics. His institutional affiliation places him at France's premier acoustics research laboratory, which maintains extensive facilities for acoustic measurements, ultrasonic experimentation, and transducer development across multiple specialized domains including materials science, opto-acoustics, and bioacoustics. Lotton's research program centers on two interconnected pillars: electroacoustics and thermoacoustics. His electroacoustic investigations pioneer advanced modeling, development, and characterization of audio transducers with particular emphasis on nonlinear behaviors in loudspeakers and electric guitar pickups. Simultaneously, his thermoacoustic research explores acoustic refrigeration systems, complex couplings between acoustic and thermal energy fields, and transient nonlinear phenomena. This dual focus enables innovative cross-pollination between audio engineering and thermal physics, driving advancements in both fundamental understanding and practical applications of acoustic energy conversion. Analysis of his 2019-2024 publications reveals a consistent trajectory in transducer physics, particularly MEMS-based piezoelectric speakers, voice coil dynamics in magnetic environments, and digital acoustic projection systems. His work demonstrates exceptional methodological diversity spanning analytical modeling, experimental validation, and educational innovation. Notable contributions include the ASKNOWN project's open-access acoustics courseware and breakthroughs in understanding transducer nonlinearities for both consumer audio and specialized applications like fish sound localization. No major scientific awards were documented in the available institutional materials, though his sustained publication record in high-impact journals and presentations at European Acoustics Association forums indicate significant peer recognition. His collaborative research network spans France, Germany, Italy, and the Czech Republic, reflecting strong international engagement. Lotton's academic supervision activities aren't explicitly detailed, but his educational initiatives like the ASKNOWN project demonstrate commitment to pedagogy. His research is supported through LAUM's institutional framework and collaborative projects including European initiatives and ANR-funded programs. Current work appears concentrated on advancing MEMS transducer technology, refining thermoacoustic cooling systems, and developing next-generation educational resources for acoustics. As a core contributor to LAUM's Transducers team, Lotton operates within one of Europe's leading acoustics laboratories. His current projects align with LAUM's strategic focus on transducer innovation and thermoacoustic applications, positioning him at the forefront of both theoretical acoustics research and practical engineering solutions. The laboratory's comprehensive infrastructure supports his work from fundamental wave propagation studies to applied device development.

Josh ReissView profile

Professor

• Audio Engineering
• Signal Processing
• Music Production
• +4 more

Josh Reiss is a Professor of Audio Engineering at Queen Mary University of London (QMUL), part of the School of Electronic Engineering and Computer Science . He holds additional roles including President-Elect and Fellow of the Audio Engineering Society (AES), and Visiting Professor at Birmingham City University. His research focuses on audio signal processing, procedural audio, and intelligent music production. He earned degrees including BSc in Physics, BSc in Mathematics, and a PhD. Research & Awards : Reiss has published over 200 papers, authored books like Intelligent Music Production , and received awards such as the AES Board of Governors Award (2009, 2010) and Best JAES Paper 2016. His work spans sound synthesis, dynamic range compression, and live audio systems. Teaching & Industry : Teaches modules like Artificial Intelligence and Sound Design. Co-founded startups LandR (AI mixing), Tonz, and Nemisindo. Leads the Centre for Digital Music at QMUL, advancing research in audio technology. Labs & Teams : Active in the Centre for Digital Music, collaborating on projects like the Open Multitrack Testbed and semantic audio evaluation tools.

Johan PauwelsView profile

Lecturer

• Audio Signal Processing
• Music Information Retrieval
• Machine Learning for Audio
• +3 more

Dr. Johan Pauwels is a Lecturer in Audio Signal Processing at Queen Mary University of London's School of Electronic Engineering and Computer Science, where he is affiliated with the Centre for Digital Music and the Centre for Multimodal AI. His educational background includes: Master of Science in Electrical/Electronics Engineering from KU Leuven (2006) Master of Science in Artificial Intelligence from KU Leuven (2007) PhD from Ghent University (2016) on automatic harmony recognition from audio Johan's research focuses on making machines understand audio to the level of a trained professional. His work combines machine learning, signal processing, data science, and music theory to develop tools for musicians, listeners, and music learners. He has been working on narrowing the gap between academic research and user-centric applications, web-based music services, and the personalization of spatial and immersive audio. His specific interests include machine learning for audio, audio signal processing, music information retrieval, and binaural audio. His recent publications show a strong focus on music representation learning, with particular attention to limited data scenarios, multimodal approaches, and spatial audio processing. His work bridges theoretical music concepts with practical machine learning applications, especially in chord recognition, beat detection, and instrument recognition. He has made significant contributions to HRTF (Head-Related Transfer Function) research and development of tools for spatial audio processing. Dr. Pauwels is actively involved in research funding, with current grants including the AIM CDT Internship with Sofilab (2025), AIM CDT Studentship - Stem (2024), and AIM CDT Internship with stem.tech (2024). He currently supervises multiple PhD students, primarily through the UKRI Doctoral School in AI and Music, with research topics spanning intelligent audio editing, neural drum synthesis, source separation, graph neural networks for music recommendation, and more. In addition to PhD supervision, he typically guides 8-10 undergraduate and 8-10 master's students through their final year projects. His teaching responsibilities include ECS7013P Deep Learning for Audio and Music (MSc/PhD level) and ECS411U Signals and Information (first-year undergraduate).

Kartic SubrView profile

Senior Lecturer

• Computer Graphics
• Monte Carlo Rendering
• Physics-based Simulation
• +13 more

Kartic Subr is a Senior Lecturer (equivalent to Associate Professor) in the School of Informatics at the University of Edinburgh, where he conducts research at the intersection of computer graphics, machine learning, and robotics. He is affiliated with the Institute of Perception, Action and Behaviour and leads an active research group in physics-aware simulation and AI for scientific discovery. His research interests span Computer Graphics , Monte Carlo Rendering , Physics-based Simulation , Machine Learning , Robotics , and Computational Biology . He has made significant contributions to rendering theory, light transport analysis, BRDF modeling, and simulation of fluids and fractures. Recently, his group has applied deep learning to protein design, achieving notable success in international competitions. The recent publications reflect a strong trend toward interdisciplinary research, combining computer graphics with AI and biology. Key themes include explainable AI for physics-aware interfaces (e.g., CueTip), neural rendering (NeRF), protein design with CNNs, and reward learning in robotics. His group regularly publishes in top venues such as SIGGRAPH, NeurIPS, and IEEE RA-L. Royal Society University Research Fellowship (2014–2024) Lead, GCRF Impact Accelerator (2019) Lead, EPSRC First Grant (2017) Royal Society Challenge Grant (2016) Royal Society Newton International Fellow (2010) Marie-Curie Visitor (2006) Best Paper Honorable Mention, I3D 2012 Best Paper, I3D 2011 Kartic Subr actively supervises PhD students and postdocs, including Leonardo Castorina, Zhiyuan Zhang, and Kevin Denamganaï. Former students have gone on to positions at DeepMind, University of Edinburgh, and industry. He has secured multiple grants, including from the Royal Society and EPSRC. His research group collaborates across disciplines, particularly with biological sciences on protein design. He leads projects on approximate physics for robotics, protein design via deep learning, and interactive rendering systems. The group has developed frameworks like TIMED for de novo protein design and tools for explainable physics-aware assistants.

David LindlbauerView profile

Assistant Professor

• Human-Computer Interaction
• Augmented Reality
• Virtual Reality
• +6 more

David Lindlbauer is an Assistant Professor at the Human-Computer Interaction Institute (HCII) of Carnegie Mellon University . He leads the Augmented Perception Lab and co-directs the CMU Extended Reality Technology Center . His research focuses on enhancing human perception and interaction with digital information through novel Augmented Reality and Virtual Reality technologies. Research Interests : Computational interaction techniques Adaptive user interfaces Spatial audio and haptic feedback Dynamic interface element placement Environmental context awareness Noticeability prediction models Scientific Recognition : Best Paper Honorable Mention at ACM CHI 2024 Best Paper Award at ACM ISS 2023 ETH Zurich Postdoctoral Fellowship Multiple best paper recognitions at ACM UIST and IEEE VR Professional Engagement : Subcommittee Chair for CHI 2025 Workshops Co-Chair for UIST 2023 Doctoral Symposium Chair for ISS 2023 Regular reviewer for top venues like CHI, UIST, SIGGRAPH, and IEEE VR Education : PhD from TU Berlin Postdoctoral Researcher at ETH Zurich

Luis Velez QuinteroView profile

Assistant Professor

• Data Science
• Extended Reality (XR)
• Machine Learning
• +4 more

Luis Velez Quintero is an Assistant Professor at Stockholm University within the Department of Computer and Systems Sciences (DSV) . He is affiliated with the Data Science Research Group and the Stockholm Technology & Interaction Research (STIR) group, focusing on Human–Computer Interaction. His research spans adaptive immersive systems, affective computing, and physiological signal analysis in extended reality (XR) environments. Education & Background : Holds a PhD in Computer and Systems Sciences from Stockholm University (2023), MSc in Health Informatics from Karolinska Institutet (2019), and BSc in Electronics Engineering from the National University of Colombia (2015). He has led the startup PortalSense since 2018, developing VR solutions for real estate visualization. Research Interests : Combines data science and ML with XR technologies to create context-aware systems for healthcare, education, and professional training. Key themes include: Adaptive VR/AR systems using real-time physiological and behavioral signals Biosignal integration for personalized user experiences Immersive technologies for cognitive assessment and skill development Publications : Over 20 peer-reviewed articles, including work on affective databases (AVDOS-VR), biosignal frameworks (Excite-O-Meter), and XR applications in cybersecurity education. Recent efforts explore third-person locomotion in VR and early-stage Alzheimer’s detection via spatial navigation tasks. Awards & Grants : Wallenberg Foundation Grant (2023-2025): Analyzing non-verbal communication in psychotherapy Swedish Institute Scholarship (2017-2019): Fully funded Master’s and PhD studies Seed funding for PortalSense from Fondo Emprender SENA Colombia (2022-2023) Advising & Projects : Lead researcher in projects like AVDOS-VR and CS:NO . Co-designed the Excite-O-Meter open-source plugin for real-time physiological analysis in VR. Active in industry collaborations for scalable health interventions and immersive training systems. Labs & Teams : Collaborates with multidisciplinary teams at STIR and DSV, advancing human-centered AI and adaptive XR technologies.

Dominique BechmannView profile

Professor

• Computer Graphics
• Geometric Modeling
• 3-D Interaction in Virtual Reality
• +3 more

Dominique Bechmann is a **Professor of Computer Science** at the University of Strasbourg, affiliated with the **Department of Computer Science** within the **Sciences Collegium**. He is also a researcher at the **ICube Lab** (UMR 7357 CNRS-University of Strasbourg). His academic career spans over three decades, including roles as Head of the IGG Computer Graphics and Geometry research group (1997–2022) and Head of the National Research Group GdR IG-RV (2014–2021). He holds a Habilitation (1995) and PhD (1989) from the University of Strasbourg, with postdoctoral research at IBM's Thomas Watson Research Center (1989–1990). His research focuses on **Computer Graphics**, **Geometric Modeling**, and **Virtual Reality**, with key contributions in free-form deformation, 3D modeling of anatomical structures, and interaction techniques in immersive environments. He has led projects like the ICT-Asian initiative on Virtual Reality (2004–2007) and organized conferences such as AFRV 2012 and AFIG-EG France 2005. His teaching spans undergraduate and graduate levels in algorithms, computer graphics, and computational geometry. Bechmann has held numerous leadership roles, including Head of the Computer Science Department (1997–2000), Vice-Head of LSIIT Lab (2009–2012), and member of the National Commission of Universities (CNU) section 27 (2007–2011). His work bridges theoretical computer graphics with practical applications in medicine, architecture, and collaborative systems.

Jonas BraaschView profile

Professor

• Acoustic Virtual Reality
• Binaural Hearing
• Auditory Modeling
• +3 more

Jonas Braasch is a Professor at Rensselaer Polytechnic Institute's School of Architecture and Associate Director for Research at the Experimental Media and Performing Arts Center (EMPAC). He teaches in the Graduate Program in Architectural Acoustics and leads research on collaborative virtual reality, binaural hearing, auditory modeling, and sensory substitution devices. His work has been funded by NSF, NSERC, and European agencies, and he holds dual PhDs in Electrical Engineering/Information Science and Musicology. His research integrates acoustic virtual reality systems, immersive museum soundscapes, telematic music, and assistive instrument design. Recent publications focus on networked immersive environments, spatial audio techniques, museum acoustics classification, and innovations in wind instrument design for accessibility. Publications emphasize the application of deep learning to acoustic prediction and multisensory integration.

Philip NelsonView profile

Professor

• Acoustic Signal Processing
• Array Signal Processing
• Spatial Audio
• +1 more

Philip Nelson is Professor of Acoustics at the University of Southampton and former CEO of the Engineering and Physical Sciences Research Council. A Fellow of the Royal Academy of Engineering, his research advances acoustic signal processing and spatial audio. Recent work applies neural networks to acoustic classification and develops methods for personalized sound field reconstruction. His industrial collaborations include Samsung, Huawei, and Qualcomm. Honors include a CBE for contributions to UK engineering science.

Sascha SporsView profile

Professor

• Spatial Audio Processing
• Signal Processing
• Medical Signal Processing
• +4 more

Sascha Spors is a Professor at the Chair of Signal Theory and Digital Signal Processing within the Institute of Communications Engineering at the University of Rostock. His work spans spatial audio processing, medical signal processing, and data-driven methodologies. Chair of the AES Technical Committee on Spatial Audio Ombudsperson at the University of Rostock Research focuses on spatial sound capture/synthesis, perception of synthetic sound fields, and biomedical applications like implant monitoring via electrical impedance tomography. He contributes to open science initiatives and research data management frameworks. Key collaborations include memberships in the IEEE Signal Processing Society, Deutsche Gesellschaft für Akustik (DEGA), and Audio Engineering Society (AES).

Stefan Albert WirlerView profile

Researcher

• Spatial Audio
• Psychoacoustics
• Speech Enhancement
• +3 more

Stefan Albert Wirler serves as a Researcher in the Department of Information and Communications Engineering at Aalto University, actively contributing to the Communication Acoustics research group specializing in Spatial Sound and Psychoacoustics. His work bridges theoretical audio signal processing with practical applications in spatial audio systems. Primary research areas include Spatial Audio, Psychoacoustics, and Speech Enhancement, with specific focus on microphone array processing, spatial post-filtering techniques, and machine learning applications for auralization. His investigations address critical challenges in virtual reality audio reproduction and headphone acoustics through innovative signal processing approaches. Analysis of his 2020-2024 publications reveals consistent advancements in spatial post-filter design, particularly through non-linear combinations and coherence-based methods for speech enhancement. His work demonstrates growing integration of machine learning with traditional signal processing, notably in rigid sphere scattering modeling and DIY headphone modifications for improved acoustic transparency. Wirler operates within Aalto University's Communication Acoustics research ecosystem, collaborating extensively with senior researchers like Ville Pulkki on projects spanning spatial audio rendering, psychoacoustic validation, and real-time audio processing systems.

Amalia de GötzenView profile

Associate Professor

• Service Design
• Systemic Design
• Open Data
• +7 more

Amalia de Götzen is an Associate Professor at Aalborg University's Department of Architecture, Design and Media Technology, part of The Technical Faculty of IT and Design. Her work focuses on Systemic Design, Service Design, and Open Data initiatives, with a particular emphasis on participatory approaches and sustainability. She leads projects like CREATIVE DRIVERS FOR SUSTAINABLE LIVING HERITAGE LANDSCAPES and BC4ECO (Blockchain for Environmental Education), exploring interdisciplinary solutions for societal challenges. Her research interests include systemic design principles, cross-cultural collaboration through digital platforms, and ethical frameworks for data-driven design. Notable contributions include the DiversityOne multi-country smartphone sensor dataset and work on Theory of Change methodologies in urban regeneration projects. She has been awarded for innovative contributions to mobile sensing and 3D user interface design. Prof. de Götzen actively engages in public sector design, developing tools like the Stakeholder Map to enhance citizen-centric service design. Her projects often bridge academia and industry through collaborative ecosystems, emphasizing open licensing and IP awareness (e.g., ZOOOM project). Key Projects: Co-Design 4 Transitions (CD4T) - Climate Transition Strategies (2024-2027) Blockchain for Environmental Education (BC4ECO) - Disruptive Technology Pedagogy (2022-2025) CREATIVE DRIVERS - Heritage Landscapes and Sustainable Living (2023-2026) Awards: 2023: Mood Inference Model Prize for cross-cultural data analysis 2015: 3D User Interface Design Excellence Award Her work frequently addresses global challenges through design thinking, such as circular economy practices and digital citizenship frameworks. Current research explores temporal dimensions in urban planning and ethical AI integration in diversity-aware platforms.