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Kamakshi GopalView profile

Professor

• Objective measures of tinnitus
• Prevention of music-induced hearing loss
• Auditory Processing Disorders
• +6 more

Kamakshi Gopal is a Professor in the Department of Speech and Hearing Sciences at the University of North Texas. Her research focuses on objective measures of tinnitus and prevention of music-induced hearing loss , with additional expertise in auditory processing disorders, neuropharmacology, and neurotoxicology. Her research interests include: Objective measures of tinnitus Prevention of music-induced hearing loss Auditory Processing Disorders Neurotoxicity Pharmacological Interventions in Auditory Disorders Recent publications highlight interdisciplinary work combining electrophysiological analysis , neuroimaging , and pharmacological studies to understand auditory disorders and develop potential treatments. Her work spans from autism spectrum disorder research to hearing conservation technology and in vitro neuronal network models .

Zoran CvetkovicView profile

Professor

• Digital Signal Processing
• Wavelets
• Time-Frequency Analysis
• +9 more

Professor Zoran Cvetkovic is currently based at the Faculty of Natural, Mathematical & Engineering Sciences at King's College London , where he serves as Professor of Digital Signal Processing and Deputy Head of Department (Research) . He is affiliated with the Centre for Telecommunications Research , Engineering Security Hub , and Music Computing Lab . Education: PhD (University of California, Berkeley, 1995), MPhil (Columbia University, 1998), MSc (University of Belgrade, 1992), BSc (University of Belgrade, 1989) Previous Positions: Principal Member of Technical Staff at AT&T Labs (1997-2022), Research Fellow at Harvard University (2002-2003), Research Associate at EPFL (1996-1997) and UCSF (1994), Research/Teaching Assistant at University of Belgrade (1989-1992) Professor Cvetkovic's research spans signal processing theory , wavelets , time-frequency analysis , and their applications in neurophysiology , audio/spoken language technology , and biomedical systems . His recent work focuses on immersive audio technology , real-time acoustic simulation , superdirective beamforming , and multimodal speech recognition . With over 146 research outputs, his publications demonstrate expertise in machine learning for speech processing , acoustic environments , and information theory . His academic activities include organizing IEEE conferences , editorial roles at IEEE Transactions on Signal Processing , and collaborations with institutions like Stanford University , University of California, Berkeley , and SRI International . He supervises 7 research projects totaling over £3.5 million in funding from EPSRC , Leverhulme Trust , and Royal Academy of Engineering . His work contributes to UN Sustainable Development Goals related to education and technological innovation .

Chin-Hui LeeView profile

Professor

• Speech Recognition
• Machine Learning
• Signal Processing
• +2 more

Dr. Chin-Hui Lee is a Professor at the Georgia Institute of Technology's School of Electrical and Computer Engineering. He holds a doctorate in Electrical Engineering from the University of Washington and previously held positions at Bell Laboratories where he became a Distinguished Member of Technical Staff. His research spans speech processing, machine learning, and quantum sensing. Major research areas include deep learning approaches for speech enhancement and recognition, multimodal audio-visual systems, quantum metrology, and applications of generalized Gaussian distributions in signal processing. Recent publications reflect his interdisciplinary research, covering topics from neural network architectures for speech separation to quantum sensing techniques and clinical oncology trials. His work integrates principles from computer science, electrical engineering, and quantum physics.

James A SimmonsView profile

Professor

• auditory system
• Bats
• biosonar
• +2 more

James A Simmons is a Professor of Biology at Brown University with primary affiliation in the Department of Neuroscience. His research focuses on the biological sonar systems of bats, particularly the big brown bat (Eptesicus fuscus), studying how these animals process ultrasonic, frequency-modulated echolocation sounds to create neural representations of their target scenes. PhD, Princeton University (1969) MA, Princeton University (1968) BA, Lafayette College (1965) Simmons' research spans multiple dimensions of bat biosonar, including auditory system processing, target shape perception, clutter rejection mechanisms, and neural representation of acoustic environments. His work integrates neurophysiological, behavioral, and computational approaches to understand how bats create 'natural images' from neural reconstruction of target scenes. His laboratory has made significant contributions to understanding how echolocating bats overcome challenges like range ambiguity in cluttered surroundings, how they process phase information for high-resolution spatial imaging, and how they segregate ambiguous pulse-echo streams. Analysis of his recent publications reveals a strong focus on biosonar imaging mechanisms, with particular emphasis on how bats process complex acoustic environments. His work bridges neuroscience, sensory biology, and bioacoustics, with implications for biomimetic sonar systems and understanding neural computation principles. NIMH Research Scientist Development Award (Level II) Elected Fellow of the Acoustical Society of America Elected Fellow of the American Association for the Advancement of Science Silver Medal in Animal Bioacoustics, Acoustical Society of America Elected Fellow, International Society for Neuroethology Professor Simmons has mentored numerous students and collaborators who have contributed to his extensive publication record spanning over four decades. His teaching includes NEUR 0650/1065 (Biology of Hearing) and specialized courses like NEUR 1940B on Deep Learning in Neuroethology and Neuroethology. His research has been supported by various funding sources that enabled long-term investigation of bat biosonar systems, including development of sophisticated acoustic measurement systems and computational models of neural processing.

Mads Græsbøll ChristensenView profile

Professor

• Audio Signal Processing
• Acoustic Signal Processing
• Speech Enhancement
• +5 more

Mads Græsbøll Christensen is a Full Professor and Head of the Department of Electronic Systems at Aalborg University's Technical Faculty of IT and Design. He has held visiting positions at Philips Research Labs, ENST, UCSB, and Columbia University. Dr. Christensen earned his M.Sc. in 2002, Ph.D. in 2005, and dr.techn. in 2022, all from Aalborg University. He is a Senior Member of IEEE, a Member of EURASIP, a Fellow of the Danish Academy of Technical Sciences, and a Villum Fellow. His research focuses on audio and acoustic signal processing , with expertise in microphone arrays, noise reduction, signal modeling, speech analysis, and spatial audio. His work spans theoretical developments to practical applications in speech enhancement, hearing technology, and medical diagnostics using voice analysis. Dr. Christensen has authored 4 books and over 300 peer-reviewed papers, with recent publications focusing on speech enhancement, Parkinson's disease detection from speech, and advanced audio processing techniques. His research shows a clear trend toward applying signal processing to real-world problems, particularly in healthcare and human-computer interaction. IEEE best paper awards Spar Nord Foundation's Research Prize Danish Independent Research Council Young Researcher's Award Statoil Prize EURASIP Early Career Award (2016) Villum Foundation Young Investigator (2012) Member of the Danish Academy of Technical Sciences (2017) Dr. Christensen has supervised 13 PhD students and secured major research grants from the Independent Research Fund Denmark, the Villum Foundation, and Innovation Fund Denmark. He has served as Chairman of the EURASIP Acoustic, Speech, and Music Processing TAC and Editor-in-Chief of the EURASIP Journal on Audio, Speech, and Music Processing. He leads the Audio Analysis Lab at Aalborg University, which focuses on cutting-edge audio signal processing research with applications in healthcare, communication, and human-computer interaction.

Peter D. LawrenceView profile

Professor

• Human-Machine Interfaces
• Robotics and Control Systems
• Computer Vision
• +4 more

Professor Peter D. Lawrence holds a faculty position at the University of British Columbia (UBC) within the Department of Electrical & Computer Engineering, part of the Faculty of Applied Science. He has been a Professor since 1974 and has held visiting research roles at Chalmers University of Technology (1970-1972) and MIT (1972-1974). His educational background includes a B.A.Sc. from the University of Toronto (1965), M.Sc. from the University of Saskatchewan (1967), and Ph.D. from Case Western Reserve University (1970). He is a Professional Engineer (P.Eng.) and Fellow of the Canadian Academy of Engineering (FCAE). Research interests focus on improving human-machine interfaces, sensor technologies for control systems, and medical robotics. Key areas include teleoperation of heavy machinery, vision-based control, EEG-based brain interfaces, and functional approximation methods for complex systems. Collaborations span multiple disciplines at UBC, including Mechanical Engineering, Computer Science, Mining Engineering, and Forestry, with funding from NSERC and PRECARN/IRIS. Medical Robotics: Brain-computer interfaces and ultrasound-guided surgery. Autonomous Systems: Path planning and vision-based tracking for excavators and haul trucks. Sensing Technologies: Eye-tracking, joint-angle sensors, and slip detection for mobile robots. His teaching contributions include coordinating the Project Integrated Program (PIP) for ECE students and co-developing the interdisciplinary New Venture Design course with the Sauder School of Business. He leads the RCL Lab and has authored books on real-time microcomputer systems and contributed to IEEE publications. Awards include recognition as a Fellow of the Canadian Academy of Engineering.

James LandayView profile

Professor

• Human-Computer Interaction (HCI)
• Mobile & Ubiquitous Computing
• Human-Centered AI
• +4 more

James Landay is a Professor of Computer Science and the Anand Rajaraman and Venky Harinarayan Professor at Stanford University's School of Engineering. He serves as the Denning Co-Director of the Stanford Institute for Human-Centered AI (HAI). His expertise spans Human-Computer Interaction (HCI), Mobile Computing, and Human-Centered AI. Landay holds a BS from UC Berkeley (1990), and MS/PhD from Carnegie Mellon University (1993/1996). He has held roles at the University of Washington, Cornell Tech, and Intel Labs Seattle. His research focuses on behavior change technologies, user interface design, and cross-cultural interfaces. Education: BS, UC Berkeley, Electrical Engineering & Computer Science (1990) MS, Carnegie Mellon University, Computer Science (1993) PhD, Carnegie Mellon University, Computer Science (1996) Research Interests: Landay explores how technology can support health and sustainability through behavior change. His work includes tools like WhoIsZuki (narrative-based health apps) and Smart Primer (educational storytelling). He also studies workplace design impacts on well-being and drone-human interaction. Awards & Recognition: ACM Fellow (2016) ACM SIGCHI Academy Member (2011) ACM SIGCHI Lifetime Research Award Teaching & Advising: Landay teaches courses like Cross-Platform Mobile App Development (CS147L) and oversees over 20 advisees across doctoral, master’s, and undergraduate programs. His labs include collaborations with Tsinghua University’s World Lab. Labs & Projects: Leads initiatives such as the Hybrid Physical-Digital Spaces project and the Smart Primer educational tool. His work bridges academia, industry, and policy, with contributions to NSF advisory roles and startups like NetRaker.

• Acoustics and noise control
• Dynamics, vibration and vibration control
• Signal processing
• +3 more

Dr. Sipei Zhao is a Senior Lecturer at the School of Mechanical and Mechatronic Engineering at the University of Technology Sydney (UTS), where he has been employed since January 2021. Prior to this, he worked as a Post-doctoral Research Fellow at the Centre for Audio, Acoustics and Vibration of UTS from July 2018 to December 2020. His educational background includes a PhD in Electrical Engineering from RMIT University (2018), a Master's degree in Acoustics from Nanjing University (2015), and a Bachelor's degree in Electronics Engineering from Nanjing University (2012). Dr. Zhao's research focuses on acoustics and noise control, dynamics and vibration control, and signal processing. His work spans theoretical development and practical applications in active noise control, architectural acoustics, and machine learning for acoustic analysis. He has made significant contributions to distributed acoustic systems, neural network applications in sound field reconstruction, and innovative approaches to sound zone control. His recent publications demonstrate a strong trajectory in distributed acoustic systems, neural network applications in acoustics, and innovative approaches to sound field control and reproduction. His work combines theoretical rigor with practical implementations, often resulting in significant reductions in computational complexity while maintaining or improving performance. Best Student Paper at the 22nd International Congress on Sound and Vibration (ICSV22) in 2015 Best Paper Prize at the 21st International Conference of the Association for Computer-Aided Architectural Design Research in Asia (CAADRA2016) in 2016 Best Paper Award at the 23rd International Congress on Acoustics (ICA2019) in 2019 Young Professionals Grant from the International Institute of Noise Control Engineering (I-INCE) Ford Publication Commendation Prize from RMIT University in 2017 ARC Early Career Industry Fellowship in 2024 Dr. Zhao has successfully secured multiple research grants and contracts from organizations including the Australian Research Council, NSW Environment Protection Authority, and industry partners like Noizend Pty Ltd. His research has practical applications in industrial settings, transportation, and building acoustics. He serves as a peer reviewer for prestigious journals including the Journal of Sound and Vibration and IEEE/ACM Transactions on Audio, Speech, and Language Processing.

Israel NelkenView profile

Professor

• Auditory Neuroscience
• Neurophysiology
• Sensory Processing
• +3 more

Prof. Israel Nelken is a Full Professor at the Hebrew University of Jerusalem, affiliated with the Edmond and Lily Safra Center for Brain Sciences. His research focuses on auditory neurophysiology, specifically the neural mechanisms underlying sound processing, perception-action loops, and statistical learning in audition. He has contributed significantly to understanding how the brain detects deviant sounds and encodes complex auditory information across multiple temporal and spectral scales. Affiliations: Hebrew University of Jerusalem, Edmond and Lily Safra Center for Brain Sciences Roles: Full Professor, Principal Investigator of the Israel Nelken Lab Research Interests Prof. Nelken’s work explores the transformation of sensory signals into meaningful representations in the auditory system. Key areas include: Neuronal responses to complex sounds and their behavioral relevance Stimulus-specific adaptation (SSA) and prediction error detection Integration of auditory information across cortical and subcortical regions Role of auditory cortex in rhythmic motor synchronization and statistical learning Key Contributions His studies on deviance detection in auditory cortex have advanced our understanding of mismatch negativity (MMN) and predictive coding. Recent work highlights rats’ ability to synchronize movements with auditory rhythms, challenging assumptions about species-specific musicality. He has also developed innovative tools like the Rat Interactive Foraging Facility (RIFF) to study neural-behavioral interactions in real-time. Awards & Honors Rector’s Prize for Excellence in Research and Teaching (2015) Landau Prize for Sciences and Research (2015) Michael Bruno Memorial Award (2008) ERC Advanced Grant (2013) Grants & Collaborations Recipient of prestigious grants including the ERC Advanced Grant for studying auditory processing in natural environments. Active collaborations include work on cortical dynamics in Alzheimer’s models and computational frameworks for attentional blink phenomena. Labs & Teams Leads the Israel Nelken Lab, which integrates electrophysiology, computational modeling, and behavioral experiments to dissect auditory processing. The lab collaborates widely, contributing to projects like the dense cortical microcircuit simulations for understanding surprise responses.

Siyuan ChenView profile

Lecturer

• Physiological Computing
• Eye Activity Analysis
• Human-Computer Interaction
• +3 more

Dr Siyuan Chen is a Lecturer at the School of Electrical Engineering and Telecommunications , UNSW Sydney. Her research focuses on physiological computing , particularly eye activity analysis for mental state recognition using wearable technology . She has contributed to signal processing and machine learning methodologies for non-invasive cognitive load and task transition detection. Ph.D. in Electrical Engineering (UNSW Sydney) M.E. in Microelectronics (RMIT University) Research Intern, NII Tokyo Research Fellow, University of Melbourne Research Visitor, INRIA France Chen's research investigates eye behavior through infrared video datasets and multimodal sensor signals. Her work addresses physiological computing for applications in human-computer interaction , wearable mental state analysis , and biomedical signal processing . Key contributions include the IREye4Task dataset and novel methods for blink-saccade synchronization and pupillary response analysis . Recent publications demonstrate trends in wearable eye tracking using acoustic sensors, low-power facial expression tracking , and event-based task transition detection . Her work spans both journal and conference venues including IEEE Transactions, ACM, and INTERSPEECH. NICTA Postgraduate Scholarship (2011-2013) Commercialization Training Scheme Scholarship (2012) Australia Endeavor Fellowship (2015) $711K US Army grant for wearable behavioral signal modeling (2019) Chen contributes to teaching in electronics , signal processing , and engineering ethics , covering courses from first-year design to postgraduate leadership modules. She serves as a topic editor for Frontiers in Computer Science special issues.

Jason E GeistweidtView profile

Assistant Professor

• Electroacoustics
• Physical computing
• Creative coding
• +6 more

Jason E Geistweidt is an Assistant Professor in the Department of Media Study at the University at Buffalo's College of Arts and Sciences. His work intersects electroacoustics, physical computing, and experimental practices with a focus on digitally mediated experiences. Education: PhD in Electroacoustic Composition from Queen's University Belfast, MA in Music Technology from University of Limerick, BMusEd from Southwestern University Geistweidt's creative practice explores intimate encounters through sound art using contact microphone recordings and human voice. His telematic practice interconnects spaces via sensor arrays for ambient sonification/visualization, while generative systems employ natural language processing for text/image recontextualization. Chance operations and experimental processes define his approach, emphasizing audience activation through embodied experiences as described in John Dewey's Art as Experience . Specialties include sonic arts, networked performance, live electronics, and happenings. He designs digital tools for remote artistic projection and ambient data collection.

Mireille BoutinView profile

Professor

• Applied Mathematics
• Signal Processing
• Machine Learning
• +5 more

Mireille Boutin is a Professor at the Eindhoven University of Technology , affiliated with the Department of Mathematics and Computer Science within the Discrete Algebra and Geometry group. Her research spans applied mathematics, signal processing, and machine learning, with a focus on discrete inverse problems and the integration of geometric tools in probabilistic frameworks. Academic Background : She earned a Ph.D. in Mathematics from the University of Minnesota under Peter Olver, followed by postdoctoral positions at Brown University and the Max Planck Institute for Mathematics in the Sciences . Before joining TU/e, she served on the faculty at Purdue University . Research Trends : Recent publications demonstrate her interdisciplinary approach, including solutions to global positioning uniqueness problems via algebraic geometry, computer-aided qualitative data analysis in education, symmetry-breaking in acoustic path tracking, and novel clustering models for high-dimensional data. Her work often bridges theoretical mathematics with practical applications in engineering and education. Educational Contributions : She actively teaches Computational Algebra at TU/e and has collaborated on studies applying machine learning to qualitative education research, such as analyzing student explanations in programming and faculty teaching conceptions.

• Computational Mechanics
• Material Science
• Biomechanics
• +5 more

Prof. Bernd Markert serves as Professor and Head of the Institute of General Mechanics at RWTH Aachen University's Faculty of Mechanical Engineering. He concurrently holds critical university-wide roles including Rector's Representative for Alumni and Rectorate Mandate for Mexico Cooperation, based in Aachen's Faculty of Mechanical Engineering building. His research spans computational mechanics with emphasis on phase-field modeling, molecular dynamics, and machine learning integration. Key focus areas include biodegradable magnesium alloys for biomedical implants, multiscale composite material behavior, and AI-enhanced structural failure prediction. Recent work bridges physics-based simulations with neural networks for constitutive modeling and corrosion prediction. Analysis of his 2022-2025 publications reveals accelerating convergence of mechanics and artificial intelligence, particularly in physics-informed neural networks for crystal plasticity and phase-field frameworks. His team demonstrates consistent innovation in modeling porous media, network materials, and biomechanical systems while maintaining strong industry-relevant applications in additive manufacturing and biomedical engineering. As Institute Head, Markert leads the Chair and Institute of General Mechanics (IAM), directing research on fundamental mechanics principles applied to advanced materials and structural systems through computational and experimental methodologies.

Bracha LauferView profile

Lecturer

• Acoustic Source Localization
• Speech Signal Processing
• Gaussian Processes
• +3 more

Dr. Bracha Laufer is a senior lecturer at the School of Electrical Engineering , part of the Iby and Aladar Fleischman Faculty of Engineering at Tel Aviv University. Her research focuses on acoustic source localization, speech signal processing, and machine learning techniques for audio engineering. Her recent work explores conformal prediction and manifold-based approaches for robust source localization, deep learning architectures for sound source separation, and simplex geometry in multichannel signal analysis. These publications highlight interdisciplinary applications of machine learning and statistical methods in acoustics. Dr. Laufer's research integrates Bayesian inference , probabilistic graphical models , and uncertainty quantification to address challenges in adverse acoustic environments. She has contributed to advancements in multi-microphone speaker localization and speech inpainting .

• Robotics
• Robot Audition
• Optimal Filtering and Estimation
• +4 more

He Kong is an Associate Professor at Southern University of Science and Technology (SUSTech), affiliated with the School of Automation and Intelligent Manufacturing, where he also serves as Deputy Director of the SUSTech Institute of Robotics. Previously, he was an Assistant Professor in the Department of Mechanical and Energy Engineering at SUSTech from January to May 2022. Prior to joining SUSTech, he was a Research Fellow at the Australian Centre for Field Robotics, University of Sydney (2016-2021), and at Cranfield University's Advanced Vehicle Engineering Centre (2015-2016). He received his Ph.D. in Electrical Engineering from the University of Newcastle, Australia (2014), M.E. in Control Science and Engineering from Harbin Institute of Technology (2010), and B.E. in Electrical Engineering and Automation from China University of Mining and Technology (2004). His research focuses on robotic intelligent perception and decision making, robot audition, optimal filtering and estimation, and advanced control methods. Specifically, he works on active multi-mode perception, parameter calibration of robot audition systems, optimal filtering under unknown inputs, and fully actuated system approaches. His work has significant applications in precision agriculture, environmental monitoring, and robotic inspection of hazardous industries such as chemical and mining operations. His recent publications reveal a strong emphasis on multi-modal perception systems, particularly combining visual and auditory sensing for robotic applications. His research shows a progression from theoretical control methods toward practical implementations in field robotics, with increasing focus on real-world applications in agriculture and hazardous environments. Finalist for Youth Author Prize, IFAC Workshop on Robot Control (2019) Fifth China Robotics Academic Annual Conference Best Poster Award (2024) 14th International Conference on Indoor Positioning and Indoor Navigation Best Paper Award (2024) The Equity Scholarship, Council of International Students Australia (2011) Outstanding Postgraduate Students Award, Harbin Institute of Technology (2010) Professor Kong actively supervises numerous PhD and Master's students and has established a productive research group focused on active intelligent systems. His laboratory is equipped with advanced facilities including over 30 motion capture systems, Unitree humanoid robots, robot dogs, wheeled mobile robots, and custom-developed platforms like Cubli and acoustic perception systems. He serves on editorial boards for several prestigious journals including IEEE Robotics and Automation Letters and IEEE Sensors Letters, and has been an Associate Editor for major robotics conferences such as IEEE ICRA and IEEE/RSJ IROS.