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.
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.
David De Roure is Professor of e-Research at the University of Oxford and Academic Director of both the Digital Scholarship initiative and the Laboratory for AI Security Research. He is also an Honorary Research Professor at the Royal Northern College of Music (RNCM), where he serves as Technical Director of the Centre for Practice & Research in Science & Music (PRiSM). His work bridges computer science, digital humanities, cybersecurity, and music through his distinctive interdisciplinary approach. De Roure received his PhD in 1990 supervised by David W Barron and Peter Henderson, with research in Lisp and distributed systems. Prior to joining Oxford in 2010, he was Professor of Computer Science at the University of Southampton and Director of the Centre for Pervasive Computing in the Environment. His career spans multiple institutions and research domains, reflecting his commitment to interdisciplinary work. De Roure's research focuses on new methods of digital scholarship, innovation in knowledge infrastructure, cybersecurity, and computational approaches to music. His work uniquely combines humanities (digital musicology), social sciences (social machines and web science), engineering (Internet of Things), and computer science (distributed systems, AI). A key theme is empowering human creativity through technology rather than replacing humans with AI. He emphasizes co-creation between humans and machines, particularly in music composition where he explores how algorithms can generate fragments for human assembly. His recent publications reveal a strong focus on AI security in IoT systems, digital scholarship methods, and the intersection of music with computational approaches. There's a clear trajectory from foundational work in social machines and web science toward current applications in cybersecurity and music-AI co-creation. His publications consistently bridge technical domains with humanistic inquiry, demonstrating his commitment to interdisciplinary scholarship that addresses real-world challenges. Fellow of the British Computer Society (FBCS) Fellow of the Institute of Mathematics and its Applications (FIMA) Fellow of the Royal Society of Arts (FRSA) Chartered IT Professional (CITP) Turing Fellow at The Alan Turing Institute (2018-2024) De Roure has co-founded three major interdisciplinary initiatives: PETRAS National Centre of Excellence for IoT Systems Cybersecurity (the world's largest socio-technical research center focused on IoT security), the Software Sustainability Institute (dedicated to improving research software), and PRiSM at RNCM. He was Director of the Oxford e-Research Centre from 2012-17 and has led numerous research projects including SOCIAM (The Theory and Practice of Social Machines), FAST (Fusing Audio and Semantic Technologies), and Transforming Musicology. The Laboratory for AI Security Research, which he directs, took its first PhD students in 2024. At Oxford, De Roure chairs the Digital Research Cluster at Wolfson College and oversees the Laboratory for AI Security Research. The PRiSM team at RNCM has produced numerous musical works and performances, including six premieres in New York in 2024. He has been involved in designing gesture recognition software used in many performances and has collaborated on public engagement projects including the Science Together project which released a Hip Hop album. His current work includes exploring Chladni Plates for new musical instrument design and developing algorithmically enhanced instruments.
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
Prithvi Ravi Kantan is a full-time Researcher at Aalborg University's Department of Architecture, Design and Media Technology within The Technical Faculty of IT and Design. His work focuses on developing sound-based and multimodal feedback systems for motor rehabilitation, integrating principles from music technology and biomedical engineering. Education: PhD in Embodied Sonification Design (2021-2023) M.Sc. in Sound and Music Computing (2018-2020) B.E. in Electronics and Telecommunications (2009-2013) Research interests include real-time auditory feedback systems for neurological rehabilitation, user-centered design of clinical technologies, and the application of generative music in data sonification. He actively contributes to projects like HearWalk (2023-2027), exploring sound-facilitated motor learning in cerebral palsy patients. Notable achievements include winning the Danish Sound Day Research Pitch Battle (2023) and receiving the Best Student Paper Award at ICAD 2024. His work aligns with UN SDG 3 (Good Health) and SDG 4 (Quality Education). Teaching responsibilities include coordinating bachelor and master-level courses in PBL-based learning, emphasizing interdisciplinary approaches. He has supervised multiple student projects and contributed to over 39 publications since 2013.
Sanjeev Dewan is a Professor of Information Systems and Associate Dean of Masters Programs at the Paul Merage School of Business, University of California, Irvine. He also serves as Faculty Director of the Master of Science in Business Analytics program. Prior to joining UCI in 2001, he held faculty positions at the University of Washington and George Mason University. PhD, University of Rochester MS, University of Rochester Bachelor of Technology, Indian Institute of Technology, Delhi His research focuses on the economics of digital platforms , social and mobile analytics , and the valuation of technology investments . He investigates how information technology creates business value, impacts consumer behavior, and influences firm performance. His work spans electronic markets, Web 2.0 technologies, IT productivity, and the digital divide. The most recent publications reveal a strong emphasis on empirical analysis of digital platforms , including studies on gender bias in open source communities, quality certification in the sharing economy (e.g., Airbnb), personalized ranking in app stores, and mobile health applications. His research frequently uses large-scale datasets to examine behavioral patterns, market dynamics, and the economic implications of IT innovations. Faculty Service Award for 2023-24, UCI Paul Merage School of Business Best Paper Award, INFORMS 2019 e-Business Cluster Faculty Service Award for 2016-17, UCI Paul Merage School of Business Best Paper Award, INFORMS Conference on Information Systems and Technology (2009) INFORMS Service Award (2009) INFORMS Certificate of Appreciation (2008) Beta Gamma Sigma Honor Society (1991) University of Rochester Fellowship (1985–1990) Sanjeev Dewan has advised numerous PhD students who have secured faculty positions at leading institutions such as the University of Wisconsin-Madison, HKUST, Penn State, and the University of Hong Kong. His editorial service includes senior editor roles at Information Systems Research and associate editor at Management Science . He has also chaired tracks at ICIS and served as program co-chair for PACIS. There is no indication of external grant funding in the provided text, but his sustained publication record and leadership roles suggest significant research activity and institutional support. He is actively involved in academic leadership and research dissemination, contributing to major conferences and editorial boards. His work bridges theory and practice, particularly in digital platform ecosystems and analytics-driven decision-making.
Samuel W.K. Wong is an Associate Professor in the Department of Statistics and Actuarial Science at the University of Waterloo. He holds a Ph.D. in Statistics from Harvard University (2013) under Prof. Samuel Kou. His research focuses on statistical methodology for complex data science challenges in protein structure modeling, dynamic systems inference, and reliability engineering of wood-based products. He has held academic positions at the University of Florida (2013–2018) and has been at Waterloo since 2018. His research interests include Bayesian computation, statistical inference for dynamic systems, and spatial-temporal data analysis. Notable contributions include the development of manifold-constrained Gaussian processes (MAGI package) and sequential Monte Carlo methods for protein folding studies. He has advised over 15 graduate students and researchers, many of whom are now in academic or industry roles worldwide. Wong has received teaching distinctions at Harvard and holds awards including the Nash Medal (2008) for academic excellence. His work bridges computational statistics with applications in bioinformatics, structural engineering, and environmental science. He has published extensively in top-tier journals like Journal of Computational and Graphical Statistics and Biometrics , and collaborates with wood scientists to improve real-time lumber quality assessment using laser imaging data. His teaching portfolio includes courses on probability theory, statistical inference, and spatial data analysis at both undergraduate and graduate levels. Beyond academia, he maintains an active passion for classical piano performance, having performed recitals combining music with his statistical research interests.
Joseph P. Romano is a distinguished Professor of Statistics and Economics at Stanford University, where he has been on the faculty since 1986. He holds joint appointments in both the Department of Statistics and the Department of Economics, reflecting his interdisciplinary research that bridges statistical theory with economic applications. Romano has established himself as a leading scholar in mathematical statistics with significant contributions to econometrics, climate science, and multiple testing methodologies. Ph.D. in Statistics, University of California, Berkeley (1986) M.S. in Statistics, University of California, Berkeley (1983) A.B. in Statistics, Princeton University (1982), Summa Cum Laude Romano's research focuses on the theoretical foundations and practical applications of statistical methods, particularly in nonparametric statistics, bootstrap and resampling techniques, and multiple testing procedures. His work addresses the challenges of analyzing massive datasets with complex structures, such as those found in biotechnology, clinical trials, and econometrics. He has developed universal statistical tools applicable across diverse fields including climate science, genetics, finance, and education. His recent work emphasizes methods for multiple testing and multivariate inference driven by the availability of massive datasets, where he tackles issues like unknown dependence structures, heterogeneity, and high dimensionality. Analysis of Romano's recent publications reveals a consistent focus on developing robust statistical methodologies for complex data structures. His work spans theoretical advances in U-statistics with growing dimensions, practical applications in seroprevalence studies, and innovative approaches to ranking inference across various domains. The interdisciplinary nature of his research is evident in publications spanning economics journals, statistics journals, and even behavioral science preprints, demonstrating the broad applicability of his methodological contributions. 2021 LGBTQ+ Scientist of the Year, Out to Innovate Fellow, International Association of Applied Econometrics (2020) Fellow, Institute of Mathematical Statistics Presidential Young Investigator Award, National Science Foundation The Canadian Journal of Statistics Award Romano has mentored dozens of doctoral students throughout his career at Stanford, serving as dissertation advisor, co-advisor, and committee member for numerous PhD candidates in Statistics. His research has been consistently supported by National Science Foundation grants, including recent funding for computer-intensive inference with applications to social sciences (2020-2023) and randomization inference for contemporary statistical problems (2013-2016). He has served in various administrative roles at Stanford including Associate Chairman and Chair of Committee on Faculty Affairs. Beyond his academic pursuits, Romano is actively involved in the 500 Queer Scientists visibility campaign and maintains a balanced life with passions in music (having performed at Carnegie Hall), competitive tennis (ranked nationally in his age group), cooking, and architecture.
Christos Gatzidis serves as Executive Dean of Bournemouth University's Faculty of Science and Technology since October 2023, overseeing six departments including Computing and Informatics, Creative Technology, and Psychology. Previously Deputy Dean (2021-2023) and Head of Creative Technology Department (2016-2021), he was appointed Professor in Creative Technology in November 2019. The Faculty leads five REF Units of Assessment and secures funding from AHRC, NIHR, and Innovate UK for research spanning digital healthcare, gaming technologies, and cultural heritage applications. His educational qualifications include: PhD in Information Science, City University London (2010) PG Cert in Research Degree Supervision, Bournemouth University (2010) MA in Computer Animation, Teesside University (2003) BSc (Hons) in Computer Studies (Visualisation), University of Derby (2002) Professor Gatzidis specializes in computer graphics with research spanning virtual reality, serious games, and digital healthcare applications. His work bridges technical innovation and practical implementation, particularly in mindfulness prototypes for healthcare and stroke rehabilitation systems. Current projects focus on the multidisciplinary application of gaming technologies in medical contexts, emphasizing user experience and therapeutic outcomes through collaborations with industry partners. His publication record (2014-2025) demonstrates evolving expertise from foundational computer graphics research in terrain generation and deformation to applied work in healthcare, cultural heritage, and music education. Key trends include virtual reality for therapeutic mindfulness, usability studies in mobile gaming, and digital cultural presentation techniques, reflecting a trajectory toward socially impactful technological solutions with strong industry translation. No scientific awards are documented in the provided information. He has supervised PhD students and secured competitive research funding, including two Innovate UK Knowledge Transfer Partnerships. His principal investigator role in a virtual reality mindfulness prototype project exemplifies his approach to translating academic research into practical industry solutions, with current focus on expanding knowledge exchange activities to support the University's civic engagement mission. As Executive Dean, he leads faculty-wide research strategy across six departments, fostering interdisciplinary collaborations particularly in digital healthcare and cultural heritage. His personal research integrates computer graphics expertise with clinical applications through partnerships with healthcare providers and technology companies, driving innovation in therapeutic VR systems and educational gaming platforms.
Andy McLennan is a Professor in the School of Economics at the University of Queensland since 2007, following roles at the University of Minnesota (1987–2005) and the University of Sydney. His research focuses on mathematical economics and game theory, with contributions to computational game theory, fixed point theory, and algebraic geometry. Notable collaborations include work with Richard McKelvey on the Gambit software package for game analysis. Education: B.A. in Mathematics from the University of Chicago (undergraduate), PhD in Economics from Princeton University (1982). Prior faculty positions included the University of Toronto and Cornell University. Research Interests: Explores intersections between pure mathematics and economics, including applications of topology (Vietoris-Begle theorem), differential geometry (Morse-Sard theorem), and computational complexity in markets. Recent work includes the 'Index +1 Principle' for equilibrium stability and fixed point index theory. Software & Tools: Co-developed Gambit , a widely used open-source toolkit for analyzing finite games. Authored technical software for solving systems of equations and 3D visualization tools for academic use. Books: Authored Advanced Fixed Point Theory for Economics (Springer, 2018), The Algebra of Coherent Algebraic Sheaves , and The Nature and Origins of Modern Mathematics . Personal: Lives in Brisbane with his partner Shino Takayama (also an economist) and their son Sean. Enjoys Japanese language, classical music, and strategic games like Go and chess.
Josh McDermott is a Professor in the Department of Brain and Cognitive Sciences at MIT and an Associate Investigator at the McGovern Institute. He holds roles as Associate Department Head and Principal Investigator of the Laboratory for Computational Audition. His work bridges psychology, neuroscience, and engineering to study auditory perception, with a focus on sound interpretation, hearing impairment treatments, and machine hearing systems. Education includes a B.A. from Harvard (summa cum laude), an MPhil from University College London, and a PhD from MIT. Postdoctoral training included NYU and the University of Minnesota. Research interests encompass computational principles of sound perception, natural sound statistics, music cognition, and machine hearing. Key areas include sound localization, auditory scene analysis, and the role of generative models in perception. Recent publications highlight advancements in auditory neural networks, cross-cultural music perception, and noise schema processing. Awards include the Troland Research Award, BCS Excellence in Advising, and NSF CAREER Award. Advising includes over 20 graduate students and postdocs, with notable contributions to auditory neuroscience and machine learning. Major grants support projects on auditory models and sensory systems. The lab develops tools like cochleagram generation and headphone screening software. The Laboratory for Computational Audition operates at MIT, focusing on biological and computational approaches to hearing. Collaborations span engineering, psychology, and neuroscience to advance understanding of auditory processing.
Christopher Rundle is a Professor of Translation at the University of Bologna, Department of Interpreting and Translation , and a Honorary Research Fellow at the University of Manchester, Centre for Translation and Intercultural Studies . His career spans over 30 years in academic and research roles focused on translation history under totalitarian regimes, audiovisual translation, and interdisciplinary methodology. PhD, MA, and BA in Translation Studies Co-founder of the History and Translation Network Co-editor of the Routledge Research on Translation and Interpreting History book series Research interests include translation history in Fascist Italy and European Communism , theory of translation historiography , and subtitling practices . His publications explore censorship, ideological influence, and cultural exchange. Notable projects include the Subtitle Project and SDH Project on subtitling standards. Key publications: Publishing Translations in Fascist Italy (2010), The Routledge Handbook of Translation History (2021), and The Routledge Handbook of Translation and Methodology (2022) Editorial roles: inTRAlinea , Chronotopos , and ri.tra journal His scientific awards include an Honorary Research Fellowship at the University of Manchester. He also explores dialect and music through collaborations like the Chris Rundle Band and the album Pianura Blues .
Dr. Robert Lieck is an Assistant Professor in the Department of Computer Science at Durham University. His research focuses on interdisciplinary applications of machine learning (ML) and artificial intelligence (AI), emphasizing interpretability, robustness, and ethical considerations. He explores computational models in music cognition, communication dynamics, and medical image analysis, aiming to bridge theory and practical tools for domain experts. Before Durham, he was a postdoctoral researcher at EPFL's Digital and Cognitive Musicology Lab (2018–2021) and earned his PhD from the Learning and Intelligent Systems Lab in Stuttgart/Berlin (2012–2017). His work combines probabilistic modelling, neuro-symbolic systems, and reinforcement learning to address challenges in music analysis, autonomous decision-making, and medical robotics. Key research themes include: Music structure and perception modelling Symbol emergence in multi-agent communication Ethical AI and autonomous systems governance Medical imaging applications (CT/MRI analysis) Recent projects involve developing patient-agnostic diabetes management systems using deep reinforcement learning and surgical workflow anticipation through graph learning algorithms. He actively contributes to conferences such as NeurIPS, ISMIR, and AAAI, with publications spanning music informatics, robotics, and biomedical engineering. Current supervision includes four postgraduate students focusing on AI applications in healthcare, music technology, and autonomous systems. His work bridges technical innovation with societal impact, addressing challenges in policy, legislation, and interdisciplinary collaboration.
Mariya Toneva is a tenure-track faculty member at the Max Planck Institute for Software Systems , conducting groundbreaking research at the intersection of Machine Learning , Natural Language Processing , and Neuroscience . She leads the Bridging AI and Neuroscience (BrAIN) group , focusing on computational models that align AI systems with human brain processes. Her work aims to enhance both AI capabilities and neuroscience understanding through this cross-disciplinary approach. Actively recruiting postdocs, PhDs, and research interns in areas like code/text representation, brain-AI alignment, and neuroimaging data analysis Collaborator on NIH-funded projects using fMRI and neuropixel data Research Themes : Her group explores neural mechanisms of language processing, event segmentation in narratives, memory reactivation via music, and effective human-AI collaboration frameworks. Key methods include LLM analysis, cross-modal similarity metrics, and naturalistic task-based fMRI studies. Key Publications (2024-2025): Brain-tuned speech models (INTERSPEECH 2025) Cognitive event boundaries in LLMs (Behavioral Research Methods 2025) Music-induced memory reactivation (biorxiv 2024) LLM-brain alignment reasons (EMNLP 2024) Advising : Mentors PhD candidates Omer Moussa (speech processing), Camila Kolling (representational similarity), and Gabriele Merlin (LLM alignment). Collaborates with institutions like MIT, NYU, and ETH Zurich.
Alexandra BELIBOU is a PhD Lecturer at the Department of Music Performance and Pedagogy, Faculty of Music, Transilvania University of Brașov. Her work bridges musicology with modern interdisciplinary approaches, focusing on music education technology, therapeutic applications, and 20th-century compositional analysis. She holds a prominent position in advancing digital pedagogy through software integration. Research Interests: Music therapy methodologies emphasizing pluralistic approaches in clinical settings AI applications in music composition and education Analysis of 20th-century composers like Schoenberg, Reich, and Pärt Cultural studies of folk music traditions (e.g., Irish dance music, Romanian psalmic liturgy) Publications Trends: Recent work explores pandemic-era musician well-being, AI-assisted composition tools, and the intersection of music with medicine/physics. Earlier research delves deeply into psalmic text settings across centuries, minimalist techniques, and numerical symbolism in atonal music. Her teaching and research emphasize bridging traditional musicology with emerging technologies, as seen in proposals for software-based creativity workshops and interdisciplinary curricula.
