Koray Tahiroglu is a University Lecturer at Aalto University's School of Arts, Design and Architecture, specializing in Sound and Music Computing. His work bridges artificial intelligence, digital musical instruments, and embodied interaction, with a focus on deep learning applications in audio synthesis and human-AI creative collaboration. His research explores New Interfaces for Musical Expression (NIME), sonic interaction, and physical computing. He collaborates with SOPI Research Group and Google Brain Team (Magenta) on AI-driven artistic innovation. Recent Publications : 2024 studies on dance-sound cross-correlation and intra-action frameworks; 2023 work on AI-terity and deep learning syllabi; 2022 explorations of GAN synthesis, musical expectations, and lifeworld sonification. Scientific Awards : Co-Creative Artificial Intelligence of Music (2022) 2010 grant for scientific publications and artistic activities 2017 Honorable Mention for mobile cultural heritage research Tahiroglu contributes to digital art education and leads projects at Media Lab Helsinki, advancing sonic interaction and generative audio systems.
Peter Karsmakers serves as Associate Professor at KU Leuven's Department of Computer Science within the Faculty of Engineering Technology, based at the Geel Campus. He coordinates the Declarative Languages and Artificial Intelligence (DTAI) research group and holds leadership roles including coordinator of Research and Education for Computer Science across Geel and Diepenbeek Campuses. Karsmakers earned his PhD in Engineering Science in May 2010, focusing on kernel-based learning algorithms for sparse modeling and efficient predictions from large datasets. His doctoral work established foundations for his current research trajectory in resource-constrained machine learning systems. His research integrates machine learning with signal processing for real-time sensor data interpretation, specializing in anomaly detection from acoustic, radar, and accelerometer signals on embedded devices. Current projects address industrial condition monitoring, elderly care systems, and livestock facility monitoring through three main tracks: acoustic monitoring (e.g., SINS, WATCHDOG), radar-based systems (e.g., FARADAY, NextPerception), and smart electronics for power converters. Recent publications demonstrate strong trends in constraint-guided deep learning architectures for industrial applications, cross-environment robustness in sensor systems, and domain-knowledge integration to reduce data requirements. His work consistently bridges theoretical machine learning with practical implementations in resource-constrained environments. No scientific awards or fellowships were mentioned in the provided materials. Karsmakers supervises over 10 master's theses annually and coordinates a research team of 10 PhD students and a post-doc within DTAI-ADVISE. He has secured approximately 2.3 million euros in funding through VLAIO, EU-ECSEL, and bilateral industry contracts, including 10 active projects such as AutoEdgeML (2024-2028) and Fault Tolerant Neural Networks for Space Applications (2024-2027). He leads the DTAI-ADVISE research group focused on developing software that attaches semantics to sensor data on resource-constrained devices. The team operates across multiple campuses with specialized labs for acoustic monitoring (Geel), radar-based systems (in collaboration with ESAT-TELEMIC), and smart electronics (with Electrical Engineering department), maintaining strong industry partnerships with companies in healthcare, manufacturing, and agriculture sectors.
Rachel Devorah Wood Rome is an Assistant Professor in the Electronic Production and Design (EPD) department at Berklee College of Music, where she teaches creative coding, live coding, and music technology. Her work bridges electronic music, improvisation, and critical theory, with a focus on sonic cyberfeminism, archival practices, and the social meanings of sound and space. Ph.D. in Music Composition and Computer Technologies, University of Virginia (2018) M.L.I.S., San José State University (2017) M.A. in Music Composition, Mills College (2013) B.Mus. in Horn Performance, CUNY Queens College (2007) Her research explores superhuman prolongation, opaque complexity, and the re-signification of archaic tools in sonic media. She values machines for their patience and memory, and her creative practice emphasizes critical agency in technology design and use. She performs under the name 'mehetabel' when using archival materials in improvised electronic music. The most recent publications and performances reflect a deep engagement with AI and music, live coding, feminist media theory, and spatialized sound. Her works often involve real-time data processing, generative systems, and collaborative improvisation, situating sound within broader social, political, and technological contexts. Ruth Anderson Installation Prize (IAWM) New Music USA Grant Fellowships from MIT OpenDocLab, Adrian Piper Foundation, Ina GRM, New Museum, and Jefferson Scholars Foundation Residencies at EMS Stockholm, STEIM Amsterdam, MassMoCA, and Cove Park Rome advises emerging artists in electronic music and creative coding, many of whom have gone on to establish their own practices. She is also active in academic service, including curriculum development, faculty governance, and labor organizing as a Councilor for the Berklee Faculty Union. She leads initiatives in DEI, sound design, and coding pedagogy within the EPD department. She has been involved in interdisciplinary collaborations with artists, technologists, and institutions worldwide, presenting work in galleries, festivals, and academic conferences across North America, Europe, and Asia. Her leadership extends to nonprofit arts organizations, where she has served as Executive Director and grantwriter.
Michael J. Spivey is a Professor of Cognitive Science at the University of California, Merced, affiliated with the School of Social Sciences, Humanities and Arts. His research focuses on understanding human cognition through embodied and dynamic systems approaches, with particular expertise in eye-tracking methodologies and real-time language processing. As a faculty member in the Cognitive and Information Sciences department, he contributes to interdisciplinary research that bridges psychology, linguistics, and neuroscience. Dr. Spivey's educational background includes: Ph.D. in Brain and Cognitive Sciences from the University of Rochester (1996) M.A. in Brain and Cognitive Sciences from the University of Rochester (1995) B.A. from the University of California, Santa Cruz (1991) His research interests span psycholinguistics, visual perception, sensorimotor processing, embodied cognition, and dynamical systems theory. Dr. Spivey investigates how cognitive processes unfold in real-time through eye movements and other behavioral measures, challenging traditional modular views of cognition. His work emphasizes the continuous interaction between perception, action, and cognition, demonstrating how language processing is deeply embedded in our sensorimotor experiences. He has made significant contributions to understanding the time course of language comprehension, the role of visual context in linguistic processing, and the dynamic nature of cognitive representations. Analysis of Dr. Spivey's recent publications reveals a strong focus on embodied and dynamic approaches to cognition. His work spans diverse areas including eye-tracking and mouse-tracking methodologies, team cognition, creativity research, bilingual language processing, and the application of foraging theory to cognitive processes. A recurring theme across these publications is the investigation of real-time cognitive dynamics using continuous behavioral measures. His research increasingly incorporates ecological approaches, examining cognition in more naturalistic contexts while maintaining experimental rigor. The interdisciplinary nature of his work is evident in collaborations across psychology, linguistics, neuroscience, and even music cognition. Dr. Spivey is affiliated with the Center for Human Adaptive Systems and Environments and collaborates with researchers at Western University, Northwestern University, Brown University, and UCLA. His work with students likely focuses on training in advanced methodologies for measuring real-time cognitive processes.
Jörg Fachner is a Professor of Music, Health, and the Brain at Anglia Ruskin University (ARU), serving as Co-Director of the Cambridge Institute for Music Therapy Research. His research focuses on translational issues in interdisciplinary topics between medical, humanities, and music sciences. He holds a Dr. rerum medicinalium (Medical Sciences) from the University of Witten/Herdecke and a Diplom Pädagoge (Master in Education) from the University of Dortmund. **Research Interests:** Music therapy in neurorehabilitation, addiction treatment, dementia care, and mental health. Specializes in social neuroscience, EEG-based studies of therapeutic processes, and the neural dynamics of music-induced emotions. **Grants & Consultancy:** Major grants include the Josef Ressel Centre for Personalised Music Therapy Research in Neurorehabilitation (€1.1M), UKRI funding for RadioMe dementia technology (£35k), and collaborations with institutions like Aalborg University and Jyväskylä University. Consulted on projects such as depression and music therapy (NHS) and art therapies in addiction treatment (Germany). **Awards:** None explicitly listed, but recognized for contributions to music therapy research and clinical practice. **Labs/Teams:** Leads the Cambridge Institute for Music Therapy Research, collaborating on interdisciplinary projects like RadioMe and EEG hyperscanning studies. Supervises a global cohort of PhD students in music therapy and neuroscience.
Dr. Shahram Shirani is a Professor and holds the L.R. Wilson/Bell Canada Chair in Data Communications in the Department of Electrical & Computer Engineering at McMaster University. He also serves as Acting Chair of the department. His research focuses on multimedia communications, image/video processing, medical imaging, and hardware architectures. He teaches courses like Image Processing (COMPENG 4TN4) and 3D Image Processing and Computer Vision (ECE 736). Shirani earned his B.Sc. from Isfahan University of Technology (1989), M.Sc. from Amirkabir University of Technology (1994), and Ph.D. from the University of British Columbia (2000). His achievements include the Faculty of Engineering Leadership Fellowship (2014–15) and leadership roles in editorial boards for IEEE Transactions on Multimedia and Circuits and Systems for Video Technology. Research interests include video quality assessment, biomedical signal processing, and edge computing for traffic monitoring. His lab develops algorithms for multimedia representation, compression, and hardware implementation. Recent work includes AI-driven medical sound datasets, real-time noise removal in MRI, and efficient CNN pruning techniques. He advises over 15 graduate students and collaborates on projects like the HLS-CMDS dataset and cardiac segmentation reviews. His lab’s contributions span biomedical engineering, autonomous systems, and smart sensor technologies.
Justin Thaler is an Associate Professor in the Department of Computer Science at Georgetown University, researching algorithms and computational complexity with focus on probabilistic proof systems, verifiable computation, and streaming algorithms. Education: PhD Computer Science, Harvard University BS Computer Science and Mathematics, Yale University Research Interests: Develops protocols for verifying computations (including zero-knowledge proofs), analyzes the power of low-degree polynomials, and designs efficient streaming/sketching algorithms for large datasets. Publications: Research advances theoretical foundations of proof systems, with recent work on SNARKs, lookup arguments, and Fiat-Shamir security. Authored the monograph 'Proofs, Arguments, and Zero-Knowledge'. Advising & Labs: Advises PhD students in theoretical computer science. Contributes to open-source projects including DataSketches library of streaming algorithms. Currently on leave at a16z crypto research.
Doug L. James is a Full Professor of Computer Science at Stanford University since 2015, following roles as Associate Professor at Cornell University (2006-2015) and Assistant Professor at Carnegie Mellon University (2002-2006). He holds a PhD in Applied Mathematics from the University of British Columbia (2001), alongside earlier degrees from the same institution and the University of Western Ontario. His research focuses on computer graphics, sound synthesis, and physically-based modeling, with notable contributions to fluid simulation, cloth animation, and medical modeling. Key achievements include the 2012 Technical Achievement Award from the Academy of Motion Picture Arts and Sciences for 'Wavelet Turbulence,' and the 2013 Katayanagi Prize. He serves as a consulting Senior Research Scientist at Pixar Animation Studios and has led roles like Technical Papers Chair at SIGGRAPH 2015. His work integrates physics-based principles with interactive systems, emphasizing real-time applications and data-driven methods. Research interests span sound synthesis for animations (e.g., cloth, water, impact sounds), deformable models for medical simulation, and tools like 'svMorph' for virtual surgery planning. His publications reflect a blend of algorithmic innovation and practical applications in film, gaming, and healthcare.
Valeria Bruschi is a Researcher at the Department of Information Engineering (DII) within the Faculty of Engineering at Università Politecnica delle Marche (UNIVPM) in Ancona, Italy. Her academic profile was last updated on April 13, 2024, and she maintains her office at the Engineering Faculty on via Brecce Bianche, with contact information including phone +39 071-220-4486 and email v.bruschi@staff.univpm.it. Dr. Bruschi's research spans multiple domains within audio and signal processing, with particular expertise in spatial audio systems, automotive human-computer interaction, and biomedical signal applications. Her work bridges theoretical signal processing techniques with practical implementations across diverse fields including automotive safety systems, hearing aid technology, sleep medicine, and agricultural monitoring. She has made significant contributions to head-related transfer function (HRTF) processing, real-time audio enhancement algorithms, and innovative monitoring systems that utilize acoustic signals for various applications. Analysis of Dr. Bruschi's recent publications reveals a strong trajectory in developing practical audio processing solutions with real-world applications. Her work shows increasing integration of machine learning techniques with traditional signal processing approaches, particularly in areas like driver monitoring systems, snoring detection and cancellation, and spatial audio rendering. A notable trend is her focus on creating lightweight, real-time implementations suitable for embedded systems and practical deployment scenarios, while maintaining high performance standards. Her research consistently demonstrates interdisciplinary collaboration, connecting audio engineering with fields as diverse as automotive safety, sleep medicine, and agricultural technology. Dr. Bruschi actively contributes to advancing audio engineering through her research on equalization techniques, noise reduction systems, and immersive audio technologies. Her work on pulse compression techniques for hearing aid distortion measurement represents an important contribution to audiological assessment methodologies. Her publication record demonstrates consistent scholarly output with increasing impact across multiple application domains, reflecting her ability to translate theoretical signal processing concepts into practical engineering solutions.
Dr. John McGowan is a Lecturer at the School of Computing Engineering and the Built Environment , Edinburgh Napier University. His work bridges Music Therapy , Interaction Design , and Assistive Technologies for autistic individuals. Research Focus: Development of the CymaSense application—a real-time 3D audio-visual tool for augmenting music therapy sessions. This research explores how interactive cymatics (sound visualization) can improve communication and social interaction for people on the autism spectrum. Research Trends: His publications emphasize multi-sensory environments , therapeutic software systems , and user-centered design for neurodiverse populations. Recent work addresses stress triggers in autistic adults using augmented reality and mobile technologies . Supervision: Co-supervised PhD projects on topics including auditory selective attention in mixed reality and adaptive sound design for video games . Grants: Secured funding from Edinburgh Napier University and Arts & Humanities Research Council ( Audio Mostly 2023 conference ). £5,000 grant (AHRC) for embodied music interaction research Labs: Affiliated with the Centre for Interaction Design , contributing to interdisciplinary projects in health technology and creative arts .
Maxwell Tfirn is a Lecturer and Director of Creative Studies at Christopher Newport University , Department of Music, Theatre and Dance, where he teaches Music Composition, Sound Synthesis, and Music Technology. His research focuses on real-time recursive compositions and data sonification for scientific analysis. PhD in Composition and Computer Technologies - University of Virginia M.A. in Music Composition - Wesleyan University His work bridges music composition with bacterial behavior studies through NSF-funded research on Data Sonification of Bacterial Chemotaxis . Notable performances include works at ICMC, SEAMUS, and Subtropics Music Festival. Collaborations with ensembles like Jack Quartet and Loadbang highlight his impact in contemporary music circles. Key Trends in Publications: Articles span real-time algorithmic compositions, sensor-based live performance tools, and interdisciplinary sonification projects merging microbiology with auditory analysis. Subfields include neural network integration, audiovisual data mapping, and glitch-based performance aesthetics. Scientific Awards: Best Use of Sound (Academic) - ICAD (2023) Research Collaborations: National Science Foundation grant exploring bacterial chemotaxis sonification. Mentorship roles include advising students at Christopher Newport University and contributing to experimental music festivals globally.
Dr. Alexander Hunter is a Lecturer and Composition Convenor at the School of Music, Australian National University (ANU). He holds a PhD in composition from Edinburgh Napier University (2014) and has taught composition, theory, and music history since relocating to Canberra in 2014. Hunter founded ANU's Experimental Music Studio, focusing on open-form compositions that engage performers in fluid interpretive roles. His research spans open musical forms, spectralism, acoustic ecology, and intersectional feminism, with a commitment to disability and autistic advocacy in the arts. Education includes studies at Northern Illinois University (BA 2006) and HNC from Colaisde Bheinn na Faoghla (2007). His work integrates multimedia collaborations with artists like Mike Parr and Martyn Jolly, exploring themes of dis/ability, environmental health, and Métis cultural heritage. Key projects include Helping the River Sing (2018–2021), linking river health with artistic expression, and AI-driven music composition research with Charles Martin. Hunter’s performance-led projects often involve magic lantern technology, reimagining 19th-century projection as a medium for contemporary ecological and historical narratives. Research interests also encompass New York School music, reductionist improvisation, and anarchist philosophies in composition. His collaborations with ensembles like Ensemble Dal Niente and the Edinburgh Quartet highlight his commitment to experimental performance practices. Recent publications (2023–2025) explore AI applications in music creation and interdisciplinary performance frameworks.
Kaidi Xu is an Assistant Professor in the Department of Computer Science at Drexel University's College of Computing & Informatics. His research focuses on Trustworthy AI, with expertise in formal verification of neural networks, adversarial attacks (especially in the physical world), and certified defenses. He actively publishes in top-tier conferences including NeurIPS, ICML, ICLR, CVPR, and AAAI, and leads the award-winning research team 'alpha-beta-crown'. PhD in Computer Science, Northeastern University (2021) MS in Computer Science, University of Florida (2017) BS in Computer Science, Sichuan University (2015) Dr. Xu's research spans critical areas in AI security and robustness. He investigates formal methods to verify neural network behavior, develops techniques to defend against real-world adversarial manipulations (such as the famous 'Adversarial T-shirt'), and explores model compression and explainability. His work bridges theoretical guarantees with practical applications in healthcare, material science, and autonomous systems. His recent publications reflect a strong trend toward certified robustness, interdisciplinary applications, and formal verification across vision, language, and multimodal systems. He has consistently published at NeurIPS, ICML, CVPR, and ACL, demonstrating sustained impact in both machine learning and computer vision communities. Winner of VNN-COMP'21 with highest score Three-time VNN-COMP champion (2021–2023) with team alpha-beta-crown Faculty Research Excellence Award, CCI@Drexel (2024) Recipient of multiple Carleone Faculty Awards (2025) NSF grant recipient for projects on transit systems and material synthesis Dr. Xu advises PhD students, including Jinhao, and has secured significant external and internal funding, including multiple NSF grants and Drexel internal awards. He is actively recruiting motivated students with strong machine learning backgrounds. He also contributes to the academic community as an Area Chair for NeurIPS 2025, organizer of workshops like GenAI4Health@AAAI 2025, and frequent program committee member. He leads the 'alpha-beta-crown' research team, known for its leadership in neural network verification and repeated success in the VNN-COMP competitions. The team focuses on developing scalable, sound, and complete verification tools for deep learning models, pushing the frontier of AI safety and reliability.
Dr Bastien Lechat is a Research Fellow at Flinders Health and Medical Research Institute (FHMRI): Sleep Health, within the College of Medicine and Public Health at Flinders University. He is also a Full Member of the College of Science and Engineering and the Medical Device Research Institute. As an NHMRC Emerging Leadership Fellow, he leads innovative research at the intersection of sleep medicine, artificial intelligence, and wearable technology. Education: PhD in Sleep Health, Adelaide Institute for Sleep Health, Flinders University (2018–2021) Bachelor of Engineering in Engineering Science/Acoustics, Université du Maine, France (2014–2017) Dr Lechat’s research focuses on understanding the physiological mechanisms and consequences of obstructive sleep apnea (OSA), particularly night-to-night variability and patient subtypes. He develops AI-driven tools for efficient and accurate diagnosis using wearables and signal processing. His work aims to create a scalable, low-cost model of care for sleep-disordered breathing, addressing global diagnostic gaps. His recent publications reveal a strong trend in digital health innovation, with a focus on machine learning for OSA detection, circadian rhythm modeling, cardiovascular risk prediction, and climate impacts on sleep. His research has been published in top journals including Nature Communications , Journal of Sleep Research , and Sleep Medicine , demonstrating interdisciplinary reach. Scientific Awards and Recognition: NHMRC Emerging Leadership Fellow (2023) Helen Bearpark Memorial Scholarship (2022) Emerging Research Leader Award, Flinders University (2021) Multiple early-career awards from Sleep Down Under, Australasian Sleep Association, and Adelaide Sleep Retreat Ranked in the top 5% of international authors in sleep apnea by Expertscape Dr Lechat has secured over $2.5 million in competitive research funding and actively supervises and mentors junior researchers. He serves on the program committee of the American Thoracic Society meetings and contributes to clinical guidelines. He collaborates globally with industry and academic partners to translate research into clinical practice. Laboratories and Research Teams: He co-leads the 'Novel use of digital innovations & technology development' theme at FHMRI: Sleep Health, working closely with Professor Danny Eckert. His team integrates expertise in biomedical engineering, data science, and clinical sleep physiology to advance digital sleep medicine.
Dr. Yen-Ting (Allen) Yeh is an Assistant Professor in the Department of Computer Science at the University of Saskatchewan, where he leads research in Human-Computer Interaction focusing on mobile interaction techniques, collaborative tools, and creative technologies. PhD, Cheriton School of Computer Science, University of Waterloo MS, Graduate Institute of Networking and Multimedia, National Taiwan University His research explores physical and cognitive human capabilities through: Innovative phone interaction methods (folding, dexterous gestures, side-touch expansion) Collaborative writing environments with privacy controls Creativity augmentation systems for 3D modeling Augmented reality and interactive fabrication tools Recent publications demonstrate strong focus on: Acoustic input techniques using finger snapping Motion-based creative reflection tools Dynamic gesture recognition systems Collaborative editing comfort optimization Scientific recognition includes: ACM Creativity and Cognition 2021 Honorable Mention The research group at the University of Saskatchewan's HCI Lab actively seeks students interested in phone interactions, human factors, AR/VR, collaborative tools, and creative arts applications.
