Jaakko Kauramäki is a Researcher at the Cognitive Brain Research Unit, University of Helsinki, affiliated with the Centre of Excellence in Music, Mind, Body and Brain (MMBB). His work bridges psychology, neurosciences, and cognitive science. University: University of Helsinki Department: Cognitive Brain Research Unit Fields of Interest: Auditory processing, speechreading, music therapy, aging neuroscience, social presence His recent publications focus on auditory rehabilitation technologies, neural responses to music in spinal injury patients, and social psycho-physiology in audio drama interactions. He has contributed to 20 publications since 2005 and is involved in two major projects, including a 2024–2026 Academy of Finland initiative. Jaakko serves as an Operator for the Research Infrastructure for Psychology and Logopedics (RIPL) and collaborates on multidisciplinary projects involving Finnish phonetics, deafness, and auditory cognition. His work includes developing mobile applications for hearing impairment and analyzing neural mechanisms in auditory perception.
Monte Taylor serves as Clinical Assistant Professor of Music Technology in the Patti and Rusty Rueff School of Design, Art and Performance at Purdue University, where he teaches courses integrating technical and creative aspects of electronic music production. His educational foundation includes: D.M.A. in Composition from University of Texas at Austin Butler School of Music M.M. in Composition from University of Miami Frost School of Music B.M. in Composition from University of Missouri–Kansas City Conservatory of Music and Dance Taylor's research explores generative audio systems , digital signal processing , and machine learning applications for musical composition and improvisation. His creative practice emphasizes real-time interaction between electric guitar and computer systems, investigating spectral analysis and algorithmic MIDI generation to expand expressive possibilities in electroacoustic performance. This work bridges academic research with professional audio engineering experience. His achievements include 2nd place in the KLANG! International Electroacoustic Composition Competition and finalist status for the 2020 American Prize in Orchestral Composition , with creative output featured at over 20 international festivals including Seoul International Computer Music Festival and Australian Percussion Gathering. As an educator, Taylor leverages his professional background as a freelance sound engineer to develop practice-oriented curriculum. He maintains active performance collaborations with ensembles like [Switch~ Ensemble] and Line Upon Line Percussion, providing students with exposure to professional networks. His advising emphasizes technical mastery of electronic music tools alongside creative risk-taking in composition and improvisation. Within Purdue's Rueff School infrastructure, Taylor utilizes electronic music studios to support student projects in algorithmic composition and interactive performance systems, fostering connections between music technology, visual arts, and design disciplines through the school's interdisciplinary framework.
Janne Kauttonen serves as a Visiting Professor in the Department of Neuroscience and Biomedical Engineering at Aalto University's School of Science. He holds a Doctor of Philosophy (Filosofian tohtori) from the University of Jyväskylä, awarded on October 17, 2012. His research contributes to Sustainable Development Goal 4 (Quality Education) through neuroscience education and research. Dr. Kauttonen's research interests focus on Neuroscience , particularly utilizing Functional Magnetic Resonance Imaging and Electroencephalogram techniques to study brain networks during naturalistic cognitive processes. His work explores how the brain processes social interactions, narrative comprehension, and memory formation during real-world stimuli like movies and audio dramas. Key research areas include angular gyrus functionality, social behavior neuroscience, and cognitive processing differences between holistic and analytical thinkers. His publication record shows consistent output since 2014, with significant impact in cognitive neuroscience. His research demonstrates strong interest in how brain networks respond to natural stimuli, with particular emphasis on social presence, narrative processing, and cue-based memory mechanisms. The 2018 NeuroImage paper on memory formation during movie viewing has garnered 44 citations, indicating substantial influence in the field. Dr. Kauttonen has presented his research at numerous international conferences including Neuroscience 2014 in Washington DC, the 5th Workshop on Computational Models of Narrative in Quebec City, and the APS March Meeting in Boston.
Dr. Vincent Nguyen serves as a Senior Lecturer in Orthoptics within the Graduate School of Health at the University of Technology Sydney. With a distinguished career spanning clinical practice, research, and academia, he brings extensive expertise in visual science and rehabilitation. His academic journey began with Honours in Orthoptics (1993) followed by a Master of Applied Science (1996), culminating in a PhD from the University of Sydney (2003) focused on binocular rivalry in visual psychophysics. Dr. Nguyen's research interests focus on low vision rehabilitation, depth perception, binocular vision, and the application of virtual reality and spatial audio technologies for assistive applications. His work bridges fundamental visual neuroscience with practical rehabilitation solutions, particularly for people with visual impairments. He has pioneered research in acoustic touch interfaces, virtual reality rehabilitation environments, and spatial audio navigation systems. His publication record demonstrates a clear trajectory from fundamental visual neuroscience to applied rehabilitation technologies. Recent work emphasizes immersive virtual reality applications for communication and physical rehabilitation, as well as innovative spatial audio systems that enhance navigation for people who are blind. His research integrates principles from neuroscience, engineering, and clinical practice to develop practical assistive solutions. Dr. Nguyen has secured significant research funding including NHMRC Ideas Grants (2023-2027) for 'Fluent Mobility for the Blind Individual Using Multimodal Auditory Sensory Augmentation' and CRC-P projects like 'ARIA - Bionic Visual-Spatial Medical Device for the Blind' (2022-2024). Current projects include 'EyeBot: AI-Powered Triage for Ophthalmology Referrals' (2025) and 'Next-Generation Extended Reality, Wearable Biosensors, and Metaverse Technologies for Medical Applications' (2024). As an educator, Dr. Nguyen teaches courses in Therapy and Rehabilitation (96037), Clinical Management of Refractive Error (96031), and Eye and Visual Systems (96027). His clinical background includes appointments as a Clinical Electrophysiologist with NSW Health (2007) and work with Vision Australia assisting people with low vision (2012). His postdoctoral work at York University's Centre for Vision Research with Professor Ian Howard focused on human depth perception, building on his foundational expertise in visual neuroscience.
Dr Shahana Bano is a Lecturer in the School of Computing, Engineering & Technology at Robert Gordon University, specializing in interdisciplinary applications of Artificial Intelligence. Her research spans biomedical imaging, environmental monitoring, infrastructure analytics, and socio-technical systems through the Machine Vision Research Group and Cybersecurity Research Group. Her educational background includes a PhD in Computer Science and Engineering, M.Tech in Computer Science and Engineering, MSc in Information Systems, and BCA - all completed full-time. Her research philosophy centers on convergence, bringing together diverse data types, technologies, and disciplines to create impactful, adaptive systems that bridge academic innovation with societal relevance. Dr Bano's research interests focus on Computer Vision, Image Analysis, Machine Learning, Data Analytics, Internet of Things, Text to Speech Systems, and Social Media Threat Intelligence. Her recent work demonstrates strong application of these interests to medical diagnostics (CAR-T cell classification), environmental monitoring (geothermal reservoir modeling), infrastructure analytics (pipeline defect detection), and social systems (hate detection in football communities). Her publication record shows consistent output with 32 research outputs from 2015-2025, demonstrating increasing focus on medical and environmental applications of AI in recent years. The work spans theoretical computer vision advancements to practical implementations addressing UN Sustainable Development Goals. Associate Fellow (AFHEA) 2023 from Advance HE Dr Bano actively supervises PhD students and mentors interns on diverse projects. Current PhD supervision includes research on morphological classification of CAR-T cell images for leukemia diagnosis and acoustic emission-based pipeline defect detection. She also guides students on projects involving AR-based navigation, NDVI vegetation mapping, hate detection in football communities, multimodal sensor fusion, and airport runway object detection. Her lab resources are supported through university research groups and collaborations focused on machine vision and cybersecurity applications.
Dr. Susan Naeve-Velguth is Professor of Audiology and American Sign Language at Central Michigan University, where she serves as Chairperson of the Department of Communication Sciences and Disorders and Director of Community Engagement for the College of Health Professions. She holds a Certificate of Clinical Competence in Audiology (CCC-A) and maintains active membership in the American Academy of Audiology and American Speech, Language, and Hearing Association. Education: PhD in Communication Disorders, University of Minnesota (1995) MA in Audiology, University of Minnesota (1989) BS in Speech and Hearing Science, University of Minnesota (1986) Research Focus: Her work spans three interconnected domains: FM/DM assistive hearing technologies, interprofessional education models for healthcare training, and patient counseling efficacy in audiological practice. This research addresses critical gaps in clinical education methodologies and hearing rehabilitation technology optimization. Publication Analysis: Her 30-year publication record demonstrates progression from foundational sign language linguistics (early 1990s) to contemporary hearing technology innovation (2023). Recent works emphasize evidence-based clinical education techniques and FM system performance, while earlier contributions established frameworks for pediatric assessment and family counseling in audiology. Teaching: She instructs graduate-level Audiologic Rehabilitation (CSD 431) and undergraduate American Sign Language (ASL 101H), integrating clinical simulation and community engagement practices.
Vincent Tourre is an Associate Professor in the Department of Computer Science at Centrale Nantes, affiliated with the CRENAU Research Team (UMR CNRS 6051), a joint unit involving CNRS, Université Grenoble Alpes, and multiple architecture schools. His academic career spans urban data visualization, morphological analysis of urban spaces, and natural lighting simulation. His research interests focus on Urban Data Visualization , Morphological Analysis of Urban Spaces , and Virtual Reality Applications for urban environments. Recent work examines 360° image perception, urban soundscapes classification, and immersive geospatial data visualization. Tourre's publications demonstrate consistent output in top venues including ISPRS Annals, International Journal of Geographical Information Science, and the Journal of the Acoustical Society of America. Tourre's 15 most recent articles reveal a strong trajectory in interdisciplinary urban computing , with growing emphasis on machine learning applications for urban data analysis (particularly in acoustics and visual perception) since 2020. His work increasingly integrates virtual reality with multi-sensor urban monitoring systems. As course leader at Centrale Nantes, Tourre teaches urban data analysis, scientific visualization, and knowledge representation. His research training contributions include doctoral supervision and development of the CORAULIS VR Platform for immersive urban studies. The CRENAU team's collaborative structure provides access to extensive urban datasets and interdisciplinary expertise across architecture, computer science, and environmental studies.
Associate Professor Muzaffer Aslan is a faculty member at Bingöl University's Faculty of Engineering and Architecture, specializing in applied artificial intelligence research. His work bridges computer science, electrical engineering, and biomedical domains with practical implementations in industrial, medical, and energy systems. His academic journey includes a BSc in Electronic-Computer Education from Gazi University (1993), MSc from Fırat University (2004), and PhD in Electrical-Electronics Engineering from Fırat University (2016). This multidisciplinary foundation enables his cross-domain research approach. Professor Aslan's research centers on developing efficient deep learning solutions for real-world problems. His primary focus areas include medical imaging analysis (brain tumor and COVID-19 detection from X-rays), fall detection systems using depth sensors, emotion recognition from EEG signals, and appliance classification for smart grids. He innovates through hybrid architectures that combine CNNs with signal processing techniques like wavelet transforms and dispersion entropy, achieving high accuracy while maintaining computational efficiency. His publication record shows accelerating output since 2020, with 11 journal articles in 2021-2022 alone spanning medical diagnostics, agricultural technology, and industrial quality control. Recent work demonstrates increasing sophistication in model design, particularly in efficient architectures for resource-constrained environments as seen in his 2023 surface defect detection paper. As Principal Investigator for a TÜBİTAK 1002 project on appliance classification, he secures active research funding while mentoring graduate students. His supervision style emphasizes practical implementation, with students frequently co-authoring publications and contributing to textbook development. The collaborative nature of his work is evident in multi-institutional authorship patterns across his publications.
Xiaobai Liu is an Assistant Professor in the Department of Computer Science at San Diego State University, College of Sciences. His research bridges Computer Vision, Machine Learning, and Computational Statistics, with applications in Clinic Diagnosis, Sports, Transportation, Surveillance, and Video Games. Education: PhD in Computer Science from HuaZhong University of Science and Technology (2012) His research focuses on image parsing, video analysis, and deep learning techniques for 3D reconstruction, object tracking, and marine mammal detection. Recent publications highlight advancements in LiDAR generation, scene text recognition, and automated spectrogram processing. Notable grants include NSF-funded projects on autonomous vehicle safety simulations, marine mammal classification, and AI-driven recycling systems. He has advised over 30 students in real estate analytics, robotics, and computer vision projects. Scientific Awards: 2018 San Diego State University President’s Excellence Award
Dr. Iain McCurdy is an Assistant Professor in the Department of Music at Maynooth University. A composer originally from Belfast, his career includes international residencies at EMS (Stockholm), NK (Berlin), and ZKM (Karlsruhe). His work has been commissioned by the Arts Council of Northern Ireland, Sonic Arts Network, and Walter Fink Preis, and performed globally. His research explores: Electroacoustic composition and computer music Sensor technology integration in musical interfaces Hardware hacking for creative applications Visual reinforcement in instrumental composition He actively promotes open-source software in his teaching and creative practice. Dr. McCurdy's publication record includes co-editing 'The Csound Journal', focusing on computer music synthesis and programming. His scholarly output reflects consistent engagement with contemporary music technology and interdisciplinary approaches to composition. While not currently leading a formal lab, his work involves developing innovative human-computer interfaces for musical expression. He teaches across undergraduate and graduate programs in music technology at Maynooth University.
Shree K. Nayar is the T. C. Chang Professor of Computer Science in the School of Engineering at Columbia University, where he heads the Columbia Vision Laboratory (CAVE). He served as Department Chair from 2009-2012 and was Director of Research at Snap Inc. from 2018-2024. Nayar received his PhD from Carnegie Mellon University and has been at Columbia since 1991, progressing from Assistant to Full Professor. His educational background includes a PhD in Electrical and Computer Engineering from Carnegie Mellon University (1990), an MS from North Carolina State University (1986), and a BS from Birla Institute of Technology in India (1984). He began his career as a Research Engineer at Taylor Instruments in New Delhi before pursuing graduate studies. Nayar's research spans three interconnected areas: novel computational cameras that capture new forms of visual information, physics-based models for vision and graphics, and algorithms for scene understanding. His work in computational imaging has transformed digital photography, with applications in smartphones, robotics, virtual reality, and human-computer interfaces. His research has produced over 300 publications with nearly 60,000 citations and 80 patents. Analysis of his recent publications reveals a strong focus on computational imaging challenges including low-light vision, depth sensing, mobile interaction, and accessibility technologies. His work consistently bridges theoretical foundations with practical applications, as evidenced by commercial implementations of his assorted pixels technology in smartphone cameras. Elected to National Academy of Engineering (2008), American Academy of Arts and Sciences (2011), National Academy of Inventors (2014), and Indian National Academy of Engineering (2022) Okawa Prize (2023), IEEE PAMI Distinguished Researcher Award (2019) Two-time David Marr Prize winner (1990, 1995) - the highest honor in computer vision Multiple best paper awards at major conferences including SIGGRAPH Asia (2024) and ECCV (2024) National Young Investigator Award (1991), Packard Fellowship (1992) Nayar has supervised numerous PhD and Master's students throughout his career at Columbia. His lab has received continuous funding from NSF, industry partners, and foundations. The Columbia Vision Laboratory (CAVE) is known for its interdisciplinary approach, combining optics, hardware design, and algorithms to solve fundamental vision problems. Nayar's Bigshot Camera project demonstrates his commitment to education, providing hands-on learning experiences for students worldwide. The Columbia Vision Laboratory (CAVE) develops cutting-edge computational imaging and computer vision systems. Under Nayar's leadership, the lab has pioneered technologies including self-powered cameras, high dynamic range imaging systems, and novel computational cameras. The lab maintains strong industry connections, particularly through Nayar's role at Snap Research, and emphasizes translating research into real-world applications that benefit society.
Lili Qiu is a Professor in the Department of Computer Science at the University of Texas at Austin and Vice Managing Director of Microsoft Research Asia (Shanghai). She previously worked at Microsoft Research Redmond (2001-2004). Her research spans wireless networks, mobile systems, and network protocols, with recent work in acoustic sensing and AI-driven networking solutions. Research Focus Qiu's research addresses fundamental challenges in: Wireless network performance and interference management Mobile system optimization for real-world environments Acoustic-based localization and tracking technologies Deep learning applications for network reliability Next-generation cellular architectures (5G and beyond) Publication Trends Her recent publications (2020-2023) demonstrate a shift toward multimodal sensing systems combining acoustics and computer vision, edge intelligence optimization, and robust mobility management for next-generation networks. This reflects industry-academia convergence through her dual appointments. Awards and Honors IEEE Fellow (2017) ACM Fellow (2018) National Academy of Inventors Fellow (2022) N2Women: Stars in Networking (2017) ACM Distinguished Scientist (2013) NSF CAREER Award (2006) Best Paper Awards: ACM MobiSys 2018, IEEE ICNP 2017 Leadership and Affiliations She bridges academic research and industrial innovation through her joint appointment at UT Austin and Microsoft Research Asia, where she oversees strategic research directions in computing systems.
Dr Jon Stammers serves as the Senior Theme Lead for Data, Connectivity and AI within the Integrated Manufacturing Group at the Advanced Manufacturing Research Centre (AMRC), University of Sheffield. He joined the AMRC in 2013, initially working in the Machining Group's Process Monitoring and Control team, and has since taken on leadership of the Data, Connectivity and AI theme. Additionally, he has lectured at the AMRC Training Centre and is an active member of the Centre for Machine Intelligence and the IET Manufacturing Technical Network. Stammers holds an MEng and PhD in Electronic Engineering. His doctoral research investigated automated identification of urban and natural audio signals using time-domain feature extraction and ensemble neural network classifiers. His primary research interests focus on leveraging data from connected manufacturing processes to enable Smart Factories. This includes developing open-source data architectures, data visualization techniques, computer vision applications, AI and machine learning algorithms, data security measures, and data science methodologies. He is particularly interested in how AI can serve as a practical tool to enhance daily manufacturing operations and the broader societal impacts of technology adoption in industrial settings. Analysis of his recent publications reveals a consistent emphasis on machine tool health monitoring, anomaly detection in machining processes, and the integration of AI for predictive maintenance. His work bridges theoretical advancements in signal processing and machine learning with practical industrial applications, contributing to more efficient and reliable manufacturing systems. No scientific awards, prizes, or fellowships were mentioned in the provided information. Stammers has previously lectured at the AMRC Training Centre, contributing to workforce development in advanced manufacturing. While no formal PhD or Master's advisees are listed in the provided information, his role in training is evident through his educational contributions. He has secured significant research funding as Principal Investigator and Co-Investigator on multiple projects, including the ATI-funded "Securing Aerospace Manufacture in the UK" (£974,000), Innovate UK's "Data-driven manufacturing" (£111,000), EPSRC's "Autonomous Method for Detecting Cutting Tool and Machine Tool Anomalies" (£1.02M), and several others totaling over £2.5 million. His current projects span AI for machining design, hydrogen storage, and geospatial AI for housing layouts. Stammers leads the Data, Connectivity and AI theme at the AMRC, which focuses on enabling Smart Factories through innovative data and AI solutions. He is part of the Integrated Manufacturing Group, a key research team within the AMRC dedicated to advancing manufacturing technologies.
Patrick Lehmeier serves as a Part-Time Lecturer at Amberg-Weiden University of Applied Sciences within the Faculty of Electrical Engineering, Media and Computer Science, specializing in event audio production systems and technologies. His academic focus centers on practical audio engineering applications for live events, with core competencies in: Real-time sound reinforcement systems Event-specific media signal processing Integrated audio-visual production environments Contact is available through his institutional email: p.lehmeier@oth-aw.de .
