Cocktail-party Problem Professors and Supervisors

Jon Barkerمشاهده پروفایل

استاد

University of SheffieldUnited Kingdom

Professor Jon Barker is a faculty member at the University of Sheffield , where he holds a Personal Chair in the School of Computer Science . He leads the Speech and Hearing (SpandH) research group and co-founded the CHiME international workshop series on robust speech recognition. Education : PhD in Computer Science (University of Sheffield, 1999); BA in Electrical and Information Sciences (Cambridge University). Research Focus : His work bridges machine listening and human auditory perception , with key contributions to noise-robust speech recognition , speech intelligibility prediction , and hearing aid signal processing for speech and music. Recent projects include the Clarity Challenges and Cadenza Challenges , large-scale machine learning initiatives to improve accessibility for hearing-impaired users. Publication Trends : Recent articles emphasize machine learning for hearing aid optimization , dysarthric speech recognition , audio-visual integration , and music demixing algorithms . Collaborations span speech processing, psychoacoustics, and biomedical engineering. Scientific Awards : EURASIP Best Paper Award (2009) ISCA Best Paper Award (2008) Grants and Leadership : He has secured major EPSRC grants including EnhanceMusic (2022-2026) and Challenges to Revolutionise Hearing Device Processing (2019-2025). He co-led the TAPAS Marie Curie Training Network (2017-2022) and led projects like AV-COGHEAR (2015-2018) and CHiME (2009-2012). Labs and Teams : Barker collaborates closely with the Speech and Hearing Research Group and contributes to international initiatives like the CHiME Workshop . His lab develops open datasets such as the Clarity Speech Corpus and Audio-Visual Lombard Corpus .

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Jonathan Simonمشاهده پروفایل

استاد

University of Maryland, College ParkUnited States

Jonathan Simon is a Professor in the Department of Electrical and Computer Engineering at the University of Maryland (UMD), with affiliations in Biology, the Institute for Systems Research (ISR), and the Brain and Behavior Institute. He holds joint appointments in multiple departments, reflecting his interdisciplinary research in neuroscience and engineering. Simon earned his B.S. in Physics from Princeton University and his Ph.D. in Physics from UC Santa Barbara, followed by postdoctoral work in theoretical relativity before transitioning to auditory neuroscience. His research focuses on auditory neuroscience, particularly how the brain processes speech and complex sounds using non-invasive techniques like magnetoencephalography (MEG). Key interests include the 'cocktail party problem'—selective attention in noisy environments—and the neural mechanisms underlying speech comprehension. He co-directs the KIT-Maryland Magnetoencephalography Center and the Computational Sensorimotor Systems Laboratory (CSSL). Simon’s work bridges computational neuroscience and engineering applications, such as improving hearing aids and cochlear implants. His recent studies investigate aging-related changes in auditory processing, neural plasticity from auditory-cognitive training, and post-stroke cognitive recovery. He has published extensively on cortical responses to speech, neural decoding of attention, and functional connectivity in aging and clinical populations. His research has been featured in journals like *Neuron*, *Nature Communications*, and *Proceedings of the National Academy of Sciences (PNAS)*, and he collaborates internationally on projects funded by grants from NIH, NSF, and industry partners.

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Ross Maddoxمشاهده پروفایل

دانشیار

University of RochesterUnited States

Ross Maddox, Ph.D., is an Associate Professor in the Department of Otolaryngology-Head and Neck Surgery at the University of Michigan, where he is affiliated with the Kresge Hearing Research Institute. Previously, he served on the faculty of the Departments of Biomedical Engineering and Neuroscience at the University of Rochester. His academic journey includes a B.S. in Sound Engineering from the University of Michigan, followed by an M.S. and Ph.D. in Biomedical Engineering from Boston University. He completed a postdoctoral fellowship at the University of Washington Institute for Learning & Brain Sciences (I-LABS). Educations: B.S. in Sound Engineering, University of Michigan M.S. in Biomedical Engineering, Boston University Ph.D. in Biomedical Engineering, Boston University Research Interests: The Maddox Lab focuses on understanding how the human brain processes auditory information in complex environments. Research combines electroencephalography (EEG) and psychophysics to study selective attention and listening. Key areas include: Development of the parallel auditory brainstem response (pABR) for rapid, comprehensive hearing diagnostics in infants Investigation of subcortical neural responses to natural sounds, enabling studies of real-world listening behaviors like the 'cocktail party problem' Integration of auditory and visual cues for sensory processing Labs & Teams: The Maddox Lab operates within the Kresge Hearing Research Institute, collaborating across disciplines to bridge basic science, clinical applications, and methodological innovation. Current projects emphasize diagnostic tool development and translational research for hearing healthcare.

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David J Lewkowiczمشاهده پروفایل

پژوهشگر

Yale UniversityUnited States

David J. Lewkowicz is a Senior Research Scientist at Yale University’s Child Study Center and Department of Psychology. He holds a BA from Brandeis University (1974), a PhD in Biopsychology from the City University of New York (1979), and completed a postdoctoral fellowship in child mental health at Albert Einstein College of Medicine (1980). His research focuses on perceptual and cognitive development in infancy and early childhood, particularly multisensory attention to speech and its integration in neurotypical and at-risk populations. Key areas include the 'multisensory cocktail party problem,' developmental shifts in attention to facial features, and the impact of early experience on language and social skills. Dr. Lewkowicz has been funded by NIH, NSF, and private foundations. His work has been featured in major media outlets like the New York Times and NPR. Awards include Fellowships from APA, APS, and AAAS, as well as a Senior Investigator Award from the International Society for Developmental Psychobiology. Recent studies explore how infants and children process audiovisual speech in complex environments, with implications for understanding autism spectrum disorders. Collaborations include work with researchers like Richard Aslin, Katarzyna Chawarska, and Angelina Vernetti. Grants focus on translational research linking behavioral and neural mechanisms of development.

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Rachel Kallenمشاهده پروفایل

دانشیار

Macquarie UniversityAustralia

Rachel Kallen is an Associate Professor and Director of the Honours Program in the School of Psychological Sciences at Macquarie University, Sydney. She holds a PhD in Social Psychology from the University of Connecticut (2005) and previously served as Assistant Professor (2012–2017) and Associate Professor (2017) at the University of Cincinnati. Her research bridges social psychology and cognitive science, focusing on complex systems frameworks to study social behaviors, multiagent coordination, and dynamical modeling. Key areas include stigma, intergroup relations, diversity science, and VR applications for social interaction. She leads projects on human-machine systems, virtual embodiment, and collaborative problem-solving dynamics. Notable awards include the LightHouse Award for Empowerment (2022) and Psi Chi’s Teacher of the Year (2011). Her work spans 80+ publications, emphasizing interdisciplinary methods like dynamical systems theory and machine learning. She actively organizes conferences, including the Annual PhD Seminar series on Complex Social Systems (2024), and collaborates internationally on projects such as ‘Control and User Interface Design Factors for the Metaverse’ (2022–2023).

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Li Wanمشاهده پروفایل

مدرس

Queen Mary University of LondonUnited Kingdom

Li Wan serves as a Lecturer at the Language Centre within Queen Mary University of London's School of Languages, Linguistics and Film. Despite her institutional affiliation with language education, her research output demonstrates deep expertise in acoustics, machine learning, and sensor networks, reflecting an unusual interdisciplinary profile spanning engineering and biomedical applications. Her research interests center on acoustics and speech processing, with significant contributions to machine learning applications in sensor networks, signal processing, and natural language processing. Recent work focuses on binaural audio rendering, emotion recognition systems, and biomedical diagnostics using electrocardiogram data, often addressing real-world challenges like missing sensor data and class imbalance in classification tasks. This research bridges engineering disciplines despite her Language Centre appointment. Analysis of her 15 most recent publications reveals a strong trend toward physics-informed neural networks for audio applications and sensor-based human activity recognition. Her work frequently appears in specialized challenges like the SHL and Odyssey competitions, emphasizing practical implementations for locomotion recognition, drone audition, and text segmentation. Key methodological themes include multimodal fusion, data augmentation, and cross-domain adaptation. Scientific Awards: No formal awards or fellowships documented in provided sources While her Language Centre role suggests teaching responsibilities in Chinese language, her publication record indicates active research mentorship in engineering domains. No grants or student advisement details are publicly available, though her challenge competition participation implies collaboration with technical research teams. The absence of lab affiliations in current documentation contrasts with her hardware-oriented work on drone audition and sensor systems.

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John Cullingمشاهده پروفایل

استاد

Cardiff UniversityUnited Kingdom

John Culling is Professor at Cardiff University's School of Psychology, specializing in psychoacoustics, binaural hearing, and speech perception in noise. His research investigates perceptual mechanisms enabling speech understanding in challenging auditory environments like reverberant rooms, with applications in hearing aid design and cochlear implant technology. Research focuses on: Cocktail-party problem solutions Binaural unmasking mechanisms Effects of reverberation on speech segregation Fundamental frequency differences in voice separation Hearing impairment compensation strategies Publication analysis reveals consistent focus on auditory perception in complex soundscapes, with recent work emphasizing computational modeling, assistive device optimization, and neurophysiological underpinnings of hearing. Scientific honors include: Fellow of the Hanse Wissenschaftskolleg Fellow of the Acoustical Society of America Current PhD supervision includes Ryab Barnsley's work on bone-conduction hearing aids. Major grants secured: EPSRC: 'Physiologically inspired hearing loss simulation' (£366K, PI) Leverhulme Trust: 'Active audiovisual perception' (£239K, Co-I) Oticon Foundation: 'Bilateral cochlear implants' (£139K, PI) Collaborates internationally with researchers in auditory science including Dr Mathieu Lavandier (Lyon) and Prof. Jon Barker (Sheffield).

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Aaron Nidifferمشاهده پروفایل

دانشگاهی

University of RochesterUnited States

Aaron Nidiffer, Ph.D., is a Research Assistant Professor in the Department of Neuroscience at the University of Rochester's School of Medicine and Dentistry (SMD). His research focuses on understanding multisensory integration, speech processing, and neurophysiological mechanisms underlying social cognition. He employs EEG and computational modeling to investigate how the brain processes naturalistic stimuli, with clinical applications in schizophrenia research and neurodevelopmental disorders. Dr. Nidiffer's work emphasizes the interplay between sensory modalities, attentional processes, and neural plasticity. His recent studies explore how gaze direction and temporal synchrony influence multisensory perception, as well as the role of predictive coding in speech comprehension. He advocates for open science practices, contributing to standardized frameworks for neural data sharing. Key research themes include: Multisensory integration in complex environments EEG biomarkers for schizophrenia spectrum disorders Cross-modal speech processing (lipreading, audiovisual speech) Computational modeling of subcortical-cortical interactions His publications span 2011–2025, demonstrating sustained focus on temporal dynamics, attentional modulation, and clinical neuroscience applications. No academic awards are explicitly listed in the provided materials.

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Norman Leeمشاهده پروفایل

دانشیار

St. Olaf CollegeUnited States

Norman Lee is an Associate Professor of Biology and Director of Neuroscience at St. Olaf College. His research focuses on sensory systems, particularly auditory mechanisms in animals, with emphasis on frog communication, parasitoid fly behavior, and environmental noise impacts. He holds a position in the Biology department and actively contributes to neuroscience education and research at the college. His work bridges evolutionary biology, neurophysiology, and applied acoustics. Research interests include animal communication strategies under environmental pressures, the coevolution of sensory systems with host-parasitoid interactions, and adaptations to acoustic noise. Lee’s studies often involve experimental approaches to understand how organisms process and respond to complex auditory signals, such as frog vocalizations and parasitoid fly eavesdropping behaviors. His recent articles highlight investigations into temperature effects on host-parasitoid interactions, lung-mediated auditory enhancements in frogs, and the behavioral implications of ambient noise in safety systems. These studies underscore his interdisciplinary approach, integrating biology, physics, and neuroscience. Lee’s work has been supported by grants such as the NSF CAREER award for coevolutionary sensory system studies. Norman Lee’s research also extends to educational initiatives in neuroscience, emphasizing undergraduate involvement in cutting-edge biological research. His lab focuses on experimental and analytical methods to decode sensory adaptations in diverse taxa, contributing to both basic science and applied contexts like urban acoustics and safety signal design.

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Christian Brodbeckمشاهده پروفایل

استادیار

McMaster UniversityCanada

Christian Brodbeck is an Assistant Professor in the Department of Computing and Software at McMaster University, with an associate membership in the McMaster School of Biomedical Engineering. His research focuses on computational cognitive neuroscience, neurobiology of language, and speech recognition. He develops computational models and neural data analysis tools, such as the Eelbrain Python toolkit, to study how the brain processes speech and language. His work integrates methods from neuroscience, computer science, and engineering to investigate neural mechanisms underlying speech comprehension, particularly in complex listening scenarios like the 'cocktail party' problem. Brodbeck's team explores topics including predictive coding in speech perception, neural representations of non-native speech, and the impact of aging on auditory processing. Recent publications highlight contributions to neural dynamics of speech feature processing, recurrent neural network models of speech recognition, and cortical tracking under divided attention. His research bridges computational modeling with experimental neuroscience, aiming to advance both theoretical understanding and practical tools for analyzing neural data. Brodbeck actively mentors students and researchers, offering opportunities for postdocs and graduate students in his lab. His work is supported by collaborations in computational methodologies, health, and bio-innovation clusters, reflecting a commitment to interdisciplinary science.

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Nathan Weiszمشاهده پروفایل

استاد

Paris Lodron University of SalzburgAustria

Nathan Weisz is a Professor of Physiological Psychology in the Department of Psychology at the University of Salzburg , where he leads the Salzburg Brain Dynamics Lab and the MEG Laboratory at the Center for Cognitive Neuroscience Salzburg (CCNS). He has previously served as Associate Professor at the University of Trento’s CIMeC and as an Emmy Noether Group Leader at the University of Konstanz. . Doctorate: Department of Psychology, University of Konstanz (2001–2004) Diploma in Psychology: Catholic University of Eichstätt (1996–2001) His research focuses on understanding how the brain processes acoustic stimuli, particularly speech, using electrophysiological methods such as MEG and EEG. He investigates neural mechanisms in challenging listening environments (e.g., the 'cocktail party' problem), the role of neural oscillations in perception and memory, multisensory integration (e.g., audio-visual speech), and the development of tinnitus following hearing loss. His work has direct implications for hearing rehabilitation and cochlear implantation. The recent publications highlight advanced applications of M/EEG in decoding conscious perception across modalities, the role of alpha desynchronization in auditory working memory, and predictive neural activity in the auditory system. These reflect a strong trend in cognitive electrophysiology , predictive coding , and neural dynamics of perception . Nathan Weisz has not been mentioned as receiving specific scientific awards in the provided text. He advises graduate students in psychology and neuroscience, though specific names are not listed. His research is supported by institutional and likely external funding given his leadership roles and publication record. He leads a prominent research group focused on non-invasive brain imaging and cognitive dynamics. He leads the Salzburg Brain Dynamics Lab , which operates within the Center for Cognitive Neuroscience Salzburg (CCNS), utilizing MEG and EEG to study brain dynamics in perception and cognition.

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Josh McDermottمشاهده پروفایل

استاد

New York UniversityUnited States

Josh McDermott is a Professor in the Department of Brain and Cognitive Sciences at the Massachusetts Institute of Technology (MIT), where he also serves as Associate Department Head and previously as Interim Department Head. He leads the Laboratory for Computational Audition and conducts groundbreaking research at the intersection of psychology, neuroscience, and engineering, with a primary focus on understanding human auditory perception and its computational underpinnings. Dr. McDermott's educational background includes: PhD in Brain and Cognitive Sciences from MIT (2001-2006), advised by Edward Adelson MPhil in Computational Neuroscience from University College London (1998-2000), advised by Geoff Hinton B.A. in Brain and Cognitive Science, summa cum laude, from Harvard University (1994-1998), advised by Nancy Kanwisher McDermott's research program centers on understanding how humans derive information from sound in complex environments. His lab investigates why biological auditory systems outperform even the most sophisticated machine hearing systems in everyday situations like noisy city streets. He explores computational audition, natural sound statistics, music perception, and the relationship between sensory modalities, with long-term goals to improve treatments for hearing impairment and enable the design of machine systems that mirror human auditory abilities. His work bridges fundamental neuroscience with practical applications for hearing technologies. His recent publications reveal a strong trend toward integrating deep learning and neural network models with auditory neuroscience. His lab has been exploring how generative models, metamers, and task-optimized networks can illuminate human auditory processing. There's a clear progression from basic auditory phenomena to more complex computational models that bridge neuroscience and artificial intelligence, particularly in areas like sound segregation, music perception, and cross-modal integration. His work consistently demonstrates how computational approaches can reveal fundamental principles of auditory perception. Dr. McDermott has received numerous prestigious awards, including: Troland Research Award (2018) NSF CAREER Award (2015) APAN Young Investigator Award (2017) BCS Awards for Excellence in Undergraduate Advising (2014, 2018) BCS Award For Diversity, Equity, Inclusion and Justice (2023) As an advisor, McDermott has mentored numerous PhD students who have gone on to make significant contributions in auditory neuroscience and computational modeling. His Laboratory for Computational Audition serves as a hub for interdisciplinary research that bridges psychology, neuroscience, and engineering approaches to understanding hearing. The lab has developed innovative methodologies for studying auditory perception, including sound synthesis techniques, computational models, and cross-cultural approaches to music cognition. McDermott's work continues to push the boundaries of our understanding of auditory perception and its computational underpinnings.

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