Sound & Music Computing Professors and Supervisors | ApplySharif

جست‌وجوی استاد و پژوهشگر

استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشی‌تان را پیدا کنید و با او ارتباط بگیرید.

نمایش ۱۶-۳۰ از ۱٬۲۶۹ استاد راهنما

اطلاعات این پروفایل‌ها از صفحات عمومی دانشگاه‌ها جمع‌آوری شده و ممکن است به‌روز نباشد.

Michael S. Hornمشاهده پروفایل

استاد

Northwestern UniversityUnited States

Michael S. Horn is a Professor of Learning Sciences and Computer Science at Northwestern University, serving as Program Coordinator for Learning Sciences. He holds a PhD in Computer Science from Tufts University and a ScB in Computer Science from Brown University. His research focuses on the intersection of human-computer interaction and learning, emphasizing the use of emerging technologies in museums, classrooms, and informal settings. Notable projects include multi-touch tabletops in natural history museums, tangible programming languages for early education, and the TIDAL Lab’s innovative exhibits like Build-a-Tree and DeepTree. Education background includes: PhD in Computer Science (Tufts University, 2009) MS in Computer Science (Tufts University, 2006) ScB in Computer Science (Brown University, 1997) Research interests span tangible interaction design, computational literacy, and museum-based learning. He has led projects such as the ‘Energy Monsters’ board game and the TunePad music-coding platform. His work integrates technology with pedagogical practices to foster collaborative and exploratory learning environments. Active collaborations include the Computer History Museum and the California Academy of Sciences. Advising contributions include mentoring doctoral students like Dr. Mmachi Obiorah and Pei-Yi. His lab, TIDAL, explores interactive technologies for education, with grants from NSF and industry partnerships. Recent articles highlight innovations in computational thinking integration, music-coding hybrid practices, and AI-driven qualitative analysis.

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Adam Finkelsteinمشاهده پروفایل

استاد

Princeton UniversityUnited States

Adam Finkelstein is a Professor in the Department of Computer Science at Princeton University, where he has been a faculty member since 1997. He holds a PhD and Master's in Computer Science from the University of Washington and a dual degree in Physics and Computer Science from Swarthmore College. Finkelstein is renowned for his interdisciplinary work at the intersection of computer graphics, audio processing, and machine learning, and he co-organized the Art of Science exhibition at Princeton. Education: PhD, Computer Science, University of Washington MS, Computer Science, University of Washington BA, Physics and Computer Science, Swarthmore College His research spans audio processing (e.g., speech enhancement, voice conversion, audio metrics), computer graphics (e.g., line drawing algorithms, stylized rendering, image manipulation), and machine learning (e.g., self-supervised learning, differentiable programming). His work often bridges technical and creative domains, exemplified by collaborations at Pixar and Adobe Creative Technologies Lab. Recent publications highlight advancements in audio super-resolution and voice conversion using deep learning frameworks, as well as stylized line rendering for animated 3D models. His contributions to perceptual audio metrics and shader optimization further underscore his impact on human-centric computational systems. Scientific Awards: NSF CAREER Award Alfred P. Sloan Fellowship Fellow of the Association for Computing Machinery (ACM) Finkelstein has secured foundational grants for his research and actively mentors students, though no specific advisees are listed. He also explores collaborative tools for internet music performance, reflecting his broader interest in distributed systems and user interfaces.

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Golan Levinمشاهده پروفایل

استاد

Carnegie Mellon UniversityQatar

Golan Levin is Professor of Electronic Art at Carnegie Mellon University's School of Art, with courtesy appointments in the School of Design, School of Architecture, School of Computer Science, and Entertainment Technology Center. From 2009 to 2022, he served as Director and Co-Director of CMU's Frank-Ratchye STUDIO for Creative Inquiry, a laboratory dedicated to supporting atypical, anti-disciplinary research at the intersection of arts, science, technology, and culture. Levin's research spans interactive art, digital fabrication, information visualization, and generative design. He explores the critical potential of visualization, generative computation for expressive form, and how abstraction connects to realities beyond language. His practice engages interactive gestural robotics, nonverbal interaction aesthetics, and tactical applications of personal digital fabrication through responsive artifacts and media provocations that highlight human-machine relationships. His publications reveal consistent innovation in real-time audiovisual systems, interactive fabrication interfaces, and pedagogic tools for artists. Key trends include slit-scan video techniques, tangible augmented-reality performance, and noise-based visualizations, demonstrating his commitment to expanding human action vocabulary through digital media while bridging artistic expression with computational systems. Levin's work has received significant recognition: Permanent collection inclusion at Museum of Modern Art (MoMA) Whitney Biennial exhibition "50 Designers Shaping the Future" by Fast Company (2012) Competitive grants from National Endowment for the Arts, National Endowment for the Humanities, Creative Capital, and Rockefeller MAP Fund As an educator, Levin teaches "studio courses in computer science" on interactive art, experimental capture, and generative design, emphasizing computation as a medium for critical inquiry. His research funding from major cultural institutions supports interdisciplinary exploration at the arts-technology nexus. The Frank-Ratchye STUDIO for Creative Inquiry, which he directed for 13 years, remains a vital hub for anti-disciplinary collaboration, continuing his legacy of fostering creative agency through technology-infused artistic practice.

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Mathias Funkمشاهده پروفایل

دانشیار

Eindhoven University of TechnologyNetherlands

Mathias Funk is an Associate Professor in the Industrial Design department at Eindhoven University of Technology (TU/e), leading the Things Ecology lab. His research focuses on designing with data and systems behavior, particularly in IoT and medical technology contexts. He co-founded UXsuite GmbH and developed the OOCSI communication framework. With a PhD in Electrical Engineering from TU/e (2011), Funk has held academic roles since 2013, including postdoctoral positions in Electrical Engineering and Industrial Design. He teaches courses like 'Data-enabled design' and supervises projects on AI, data foundry, and OOCSI applications. His work bridges engineering and design, addressing sustainability and human values through systemic design approaches. Education: PhD in Electrical Engineering, TU/e (2011) Computer Science background from RWTH Aachen Postdoc at TU/e's Electrical Engineering and Industrial Design departments Research Interests: Data-driven design methodologies, IoT systems, medical technology innovation, sustainable design practices, and interactive systems for musical expression. Recent work emphasizes telemonitoring efficacy in heart failure care and federated learning applications. Awards: Best Paper Award (2014) Honorable Mention (2021) Grants/Projects: Leading initiatives like MEDICAID (medtech solutions), ACACIA (interpretable AI), and Data-Driven Servitizing in Professional Printing. Active in clinical workflow prototyping and cardiovascular disease detection projects. Lab Activities: Manages the Things Ecology lab, focusing on systemic design challenges in smart ecosystems. Collaborates internationally through spin-offs and visiting lectureships.

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Mark Bockoمشاهده پروفایل

استاد

University of RochesterUnited States

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.

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Gary Scavoneمشاهده پروفایل

استاد

McGill UniversityCanada

Dr. Gary Scavone is a Professor and Department Chair in the Music department at McGill University's Schulich School of Music. He holds a PhD in Computer-Based Music Theory & Acoustics and MS in Electrical Engineering from Stanford University, alongside degrees from Syracuse University in Music and Electrical Engineering. His research focuses on music technology, including acoustic modeling, sound synthesis, and instrument design. He directs the Computational Acoustic Modeling Laboratory (CAML), which explores advanced techniques for simulating musical instruments and developing software tools. As a saxophonist, he specializes in contemporary concert music performance. Research interests include physically-based sound synthesis, wind instrument acoustics, and digital waveguide modeling. He has contributed to studies on brass and woodwind impedance measurements, violin soundpost dynamics, and free-reed instrument modeling. His work bridges engineering and artistry, with applications in music pedagogy, instrument design optimization, and virtual acoustic replication. Key contributions include open-source projects for wind instrument modeling and the development of tools for automated timbre assessment. His research often combines experimental methods with computational simulations, addressing challenges in both theoretical and applied music acoustics. Current projects focus on deep learning for friction modeling, impedance measurement systems, and cross-cultural instrument analysis.

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Mikael B. Skovمشاهده پروفایل

استاد

Aalborg UniversityDenmark

Mikael B. Skov is a Vice Dean and Professor at the Technical Faculty of IT and Design of Aalborg University , Denmark. His research spans human-AI interaction, robotics, and user experience, with a focus on trust signaling in clinical AI, swarm robotics, and sound zones for domestic environments. Role: Vice Dean for Research Department: Computer Science Research Interests: Skov investigates how humans interact with AI and robots in healthcare and domestic settings, emphasizing trust calibration, alert design, and acoustic comfort. His work includes developing frameworks for UX maturity in robotics organizations and studying long-term adoption of sound zone systems. Recent Projects: As principal/co-investigator, he leads the HERD project on human-AI collaboration in robot swarms (2021–2025) and supervises Data og Bæredygtig Mad (2020–2023), an HCI perspective on sustainable food systems. Publications: His 2024 work includes studies on AI explanations in clinical training, music applications with intermittent interactions, and multi-robot supervision. Earlier projects (2001–2020) focused on mobile device usability, UX practices, and context-aware computing.

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Maarten Hornikxمشاهده پروفایل

استاد

Eindhoven University of TechnologyNetherlands

Building Acoustics
Computational Sound Propagation Modeling
Mixed Reality Sound Reproduction
+۴ مورد دیگر

Maarten Hornikx is a Full Professor in Building Acoustics at the Department of the Built Environment , Eindhoven University of Technology. He serves as Vice-Dean of the department, leads the Building Acoustics Chair of Unit Building Physics and Services (BPS), and coordinates the Science of Sound and Music course series since 2013. His research focuses on computational modeling of sound propagation in built environments, with applications in mixed reality platforms and numerical analysis of outdoor/indoor propagation effects like vegetation and meteorological influences. Education : PhD in Applied Acoustics (Chalmers University of Technology, 2009); MSc in Architecture, Building and Planning (2004) Hornikx promotes open research software in acoustics and has received multiple grants, including Marie Curie Individual and Career Integration Grants. His recent publications explore AI-driven diffusion equation modeling, acoustic absorber optimization, and advanced numerical methods like the discontinuous Galerkin technique. He has held international leadership roles, including chairing the Computational Acoustics Technical Committee of the European Acoustics Association and serving as Associate Editor for Acta Acustica . Scientific Awards : Marie Curie Fellowship (2009-2011); Marie Curie Career Integration Grant (2012); 4TU.Built Environment Center Scientific Director (2020-2021); eScience Center Fellow (2022) As a research leader, Hornikx guided the H2020-ITN Acoutect project and conducted sabbaticals at Aalto University, Stockholm University (2018), and Politecnico Torino (2022). His group emphasizes computational acoustics and open-source tools to enhance reproducibility and collaboration.

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Richard M. Sternمشاهده پروفایل

استاد

Carnegie Mellon UniversityQatar

Richard M. Stern is a Professor of Electrical and Computer Engineering at Carnegie Mellon University (CMU), holding courtesy appointments in the Language Technologies Institute and Department of Computer Science, and serving as an Artist Lecturer in the School of Music since 2007. His interdisciplinary work bridges engineering and music technology through the School of Music's programs. Education: Ph.D. in Electrical Engineering from Massachusetts Institute of Technology (MIT), 1976 Professor Stern's research spans sound, speech, hearing, and music, with core emphases on robust speech processing in variable acoustic environments, music information retrieval, automated accompaniment, and foundational contributions to binaural perception theory. His work integrates psychoacoustic principles with machine learning to address challenges in speech recognition and human-robot interaction. Recent publications (2022-2025) reveal intensified focus on deep learning for speech enhancement in reverberant/noisy conditions, human-robot interaction scenarios, and music tagging—highlighting innovations in beamforming, source separation, and temporal modulation modeling. Awards and Honors: Fellow of the IEEE Fellow of the Acoustical Society of America Fellow of the International Speech Communication Association (ISCA) ISCA Distinguished Lecturer Allen Newell Award for Research Excellence (1992) Lutron Award for Teaching Excellence (2018) Professor Stern has advised numerous graduate students in speech and audio research, though specific names are unlisted in source materials. His grant portfolio includes significant National Science Foundation and industry-funded projects in speech technology, with leadership roles in initiatives like Interspeech 2006. He actively collaborates with CMU's Language Technologies Institute and Music and Technology program. He maintains strong ties to CMU's interdisciplinary ecosystem through the Language Technologies Institute and School of Music's Music and Technology program, contributing to research that merges acoustic engineering with musical applications.

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Alec Wrightمشاهده پروفایل

پژوهشگر ارشد

University of EdinburghUnited Kingdom

Alec Wright is a Chancellor’s Fellow in Audio Machine Learning at the University of Edinburgh, affiliated with the Edinburgh College of Art and the Music department. He focuses on applying machine learning to musical audio signal processing and synthesis, particularly through neural network-based audio effects modeling. Education: Doctor of Science (DSc) in Neural Modelling of Audio Effects, Aalto University (2023) Master of Science (MSc) in Acoustics and Music Technology, University of Edinburgh (2018) Master of Engineering (MEng) in Mechanical Engineering, University of Manchester (2014) His research explores neural network architectures for real-time audio processing, guitar amplifier emulation, and diffusion-based distortion restoration. Key methodologies include Recurrent Neural Networks (RNNs), neural ordinary differential equations, and synthetic data generation for foundation models. Recent publications highlight sample rate conversion techniques, interpolation filters, and nonlinear distortion modeling. These works span domains like signal processing, computational audio, and physical modeling synthesis. Scientific Awards: Chancellor’s Fellow, University of Edinburgh As an active researcher, he collaborates internationally and contributes to frameworks like Open-Amp for audio effect modeling. No formal student advising details are currently available.

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Bryan Pardoمشاهده پروفایل

استاد

Northwestern UniversityUnited States

Bryan Pardo is a Professor of Computer Science at Northwestern University and head of the Interactive Audio Lab. He co-directs the Northwestern Center for Human Computer Interaction + Design and chairs the Computer Science Diversity Committee. He teaches courses in Deep Learning, Machine Learning, Generative Modeling, and Digital Music Instrument Design. PhD in Computer Science and Engineering, University of Michigan MMus in Jazz and Improvisation, University of Michigan MS in Computer Science, Ohio State University BMus in Jazz Composition, Ohio State University His research focuses on machine understanding and manipulation of sound, particularly in music and speech domains. Key areas include Machine Learning (e.g., automated gradient clipping), Signal Processing (e.g., Multi-scale Common-fate Transform), and Human Computer Interaction. Applications involve inclusive audio interfaces, audio search engines, source separation, natural language-controlled audio effects, privacy-preserving adversarial attacks on voice recognition, and music co-creation tools. Recent publications highlight advancements in neural watermarking (MaskMark), masked acoustic modeling (VampNet), and real-time adversarial privacy systems for speech. His lab's work has been applied in Adobe's AI-powered audio editor and Lexie B2 hearing aids. Scientific Awards: $1.8 million NSF Future of Work award $440K NSF grant for accessible music programming $200K Toyota grant $100K Sony grant TorchCrepe pitch tracker: 20 million+ downloads Bryan Pardo advises PhD student Max Morrison and collaborates with researchers like Patrick O'Reilly, Zeyu Jin, and Prem Seetharaman. His lab develops technologies for blind and visually impaired audio creators, including HaptEQ and Eyes-free tools.

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Edwin van der Heideمشاهده پروفایل

مدرس

Leiden UniversityNetherlands

Edwin van der Heide is a part-time Lecturer and researcher at Leiden University, affiliated with the Leiden Institute of Advanced Computer Science (LIACS) and the Academy for Creative and Performing Arts (ACPA). His work bridges sound, space, and interaction through installations, performances, and environments. Key roles include: Co-head of ArtScience Interfaculty (Royal Conservatoire & Royal Academy of Art, The Hague) until 2016 Edgard Varèse Guest Professor at TU Berlin (2009) Invited artist at Le Fresnoy (France) and HKB Bern University of the Arts (2019) Research Interests: Spatial sound composition, audience interaction, interdisciplinary art, and the intersection of technology with auditory perception. Notable projects include Whispering Wind (permanent installation at Leiden University) and Spiral of Time (MACBA, Barcelona). Recent Articles & Exhibitions (2023–2024): Focus on large-scale installations like Pneumatic Sound Field and Spiral of Time , emphasizing public engagement and spatial acoustics. Awards: Witteveen+Bos Art+Technology Award (2009), Best Paper Award for BAI (摆) (2018). Grants & Labs: Collaborations with institutions like NCCA (Russia), MAXXI (Italy), and involvement in projects like Evolving Spark Network (global sound art initiatives).

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Panpan Yangمشاهده پروفایل

مدرس

SOAS University of LondonUnited Kingdom

Panpan Yang is a Lecturer in Arts and Visual Cultures of Modern China at the School of Arts, SOAS University of London. She joined SOAS in 2021 after completing her joint PhD at the University of Chicago under the direction of Wu Hung, Tom Gunning, W. J. T. Mitchell, Judith Zeitlin, and Dana Polan. Her interdisciplinary work bridges art history, screen studies, East Asian studies, and digital humanities, with a focus on innovative methodologies in art historical writing. Dr. Yang earned a dual BA from Peking University, double majoring in art and philosophy, followed by an MA from Tisch School of the Arts at NYU, and a PhD from the University of Chicago. During her undergraduate studies, she served as president of the Society of Dream of the Red Chamber Studies, which informed her secondary academic interest in Redology and the visual material world of the novel Hong lou meng. Panpan Yang's research explores how minor discourses can deterritorialize the terrains of both art history and screen studies. Her work demonstrates a multimethodological approach attentive to archival research, material practices, close visual analysis, computer-aided vision, and cross-cultural theorization. She is particularly interested in Chinese animation history, calligraphic imagination in contemporary art, and the intersections between traditional Chinese art forms and new media. Her publications reveal a consistent focus on Chinese visual culture across multiple media forms, with particular attention to animation, film, and calligraphy. Yang's work demonstrates how traditional Chinese art forms engage with contemporary digital media, creating new hybrid forms that challenge disciplinary boundaries. Her research shows a trajectory from historical analysis of Chinese animation to contemporary explorations of calligraphy in digital contexts, revealing the ongoing relevance of traditional Chinese aesthetics in modern media. Dr. Yang has received several prestigious awards for her scholarly and creative work: China's National Young Screenwriter Award Domitor Essay Award Dean's Distinguished Dissertation Award Nomination Honourable Mention from the Association for Chinese Animation Studies As a Principal Investigator, Dr. Yang leads the AHRC-funded research project "Stroke by Stroke: Calligraphic imagination in contemporary Chinese art and emergent media" (2023-25) with Shane McCausland. She was also a collaborating partner on the NEH-funded "Media Ecology Project." Her research has received additional support from the Getty Foundation and the Sino-British Fellowship Trust. At SOAS, she works closely with faculty and graduate students interested in Chinese arts and cultures, art theory, cinematic arts, and digital art history. Dr. Yang is currently developing innovative research at the intersection of traditional Chinese calligraphy and contemporary digital media through her AHRC-funded project. This work explores how calligraphic imagination manifests in contemporary art and emergent media contexts, creating new pathways for understanding Chinese cultural heritage in the digital age.

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Cecilia Mascoloمشاهده پروفایل

استاد

University of CambridgeUnited Kingdom

Cecilia Mascolo is a Professor of Mobile Systems at the University of Cambridge , specifically in the Department of Computer Science and Technology . She co-directs the Centre for Mobile, Wearable System and Augmented Intelligence and is a Fellow of Jesus College, Cambridge . Her research focuses on mobile systems , machine learning for mobile health , and earable technology . She has been awarded prestigious grants such as the ERC Advanced Research Grant (2019-2025) and the EPSRC Open Research Fellowship (2025-2030). Currently on sabbatical at Harvard University , her work bridges systems and machine learning for health applications. Education: PhD in Computer Science from the University of Bologna, Italy. Previous Affiliation: Faculty at University College London before 2008. Her research spans mobile and wearable systems for health and behavior monitoring, focusing on on-device machine learning , uncertainty-aware models , and audio-based diagnostics . Key areas include federated learning , edge computing , and respiratory disease progression analysis via wearables. She explores earable technology for physiological monitoring, gait analysis, and even toothbrushing tracking using in-ear sensors. Her recent publications highlight advancements in earable-based health monitoring , including heart rate estimation , respiratory rate detection , and ECG analysis using machine learning. She emphasizes longitudinal health data from consumer devices, advocating for scalable diagnostics beyond traditional clinical standards. Scientific Awards: ERC Advanced Research Grant EPSRC Open Research Fellowship Best Paper Award - IEEE Percom 10-Year Impact Award - ACM Ubicomp Computer Laboratory Ring Hall of Fame Best Paper Award Student: Andrea Ferlini - ACM SIGMOBILE Doctoral Dissertation Runner-up She leads the Mobile Systems Research Laboratory , mentoring a team of 15 researchers (postdocs and PhD students), and has graduated over 25 PhD students. Her teaching includes Mobile Health courses at the University of Cambridge, and she serves as Director of Studies for Computer Science at Jesus College.

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David Lindlbauerمشاهده پروفایل

استادیار

Carnegie Mellon UniversityQatar

David Lindlbauer is an Assistant Professor at Carnegie Mellon University's Human-Computer Interaction Institute (HCII), where he leads the Augmented Perception Lab and co-directs the CMU Extended Reality Technology Center. His research focuses on advancing Mixed Reality (MR) and Extended Reality (XR) interfaces through computational interaction methods that optimize spatial, temporal, and multimodal feedback.

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