Speech Decoding Professors and Supervisors | ApplySharif

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Tetsunori KobayashiView profile

Professor

Waseda UniversityJapan

Tetsunori Kobayashi is a Professor in the School of Fundamental Science and Engineering at Waseda University, Japan, where he has served since 1997. He is renowned for pioneering research in human–robot interaction, spoken language processing, and multimodal conversational systems, leading to over 230 refereed papers and an h-index of 35 (Google Scholar). Education: 1980 B.Eng. in Electrical Engineering, Waseda University 1982 M.Eng. and 1985 Dr.Eng. from Graduate School of Science and Engineering, Waseda University Research Interests: His work spans intelligent robotics , perceptual information processing , pattern recognition , image and audio processing , and conversational AI . He develops algorithms for real-time dialogue systems, multi-party conversation facilitation robots, and non-autoregressive speech recognition leveraging CTC and pre-trained language models. Recent Publication Trends: Since 2020 his group has advanced non-autoregressive end-to-end ASR (Mask-CTC, Intermpl, BECTRA), noise-robust attention , multi-look-ahead conversational ASR , and neural speaker diarization . They integrate BERT-style pre-training with CTC losses to accelerate inference while maintaining accuracy. Parallel work explores vision-and-language topics such as scene-graph generation, video semantic indexing, and personalized summarization for spoken news delivery. Scientific Awards: IEICE Fellow 2023 – for multi-modal multi-party conversation research IPSJ Fellow 2016 – for pioneering robot conversation studies JST Award for Academic Start-ups 2024 Best Paper Awards from IEICE, IEEE BTAS, ACM SIGGRAPH VRCAI, and several IPSJ workshop prizes Advising & Grants: He has mentored dozens of PhD and Master’s students who now lead in academia and industry. Major funded projects include JST CREST on conversational robotics, NEDO and JST-support for AI-based speech interfaces, and industry collaborations with NHK, OKI, and NEC. Labs & Teams: Kobayashi heads the Perceptual Computing Laboratory at Waseda, conducting interdisciplinary research with domestic and international partners such as MIT, ATR, and NHK Science & Technology Labs.

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Yves BoubenecView profile

Associate Professor

Paris Sciences et Lettres UniversityFrance

Dr. Yves Boubenec is an Associate Professor at École Normale Supérieure (ENS)-PSL University, Paris, France. He serves as Head of the LSP Neuro Platform and Director of Studies at the Department of Cognitive Studies. Academic Rank: Associate Professor Institution: ENS-PSL Departments: Cognitive Studies (ENS), LSP Neuro Platform Email: yves.boubenec@ens.psl.eu Research Focus: Boubenec investigates neural mechanisms of auditory perception and cognition using integrated methodologies spanning single-neuron electrophysiology to large-scale neuroimaging. His work reveals how context, learning, and multisensory interactions shape sound encoding in mammalian neocortex. Primary Research Themes Context-dependent auditory encoding Perceptual attention mechanisms Task-driven neural plasticity Self-supervised learning models Population-level cortical dynamics Human/ferret auditory comparisons Publication Trends: Recent work (2024-2025) examines speech production networks, premotor auditory categorization, and algebraic structures in sound learning. Earlier studies (2018-2022) focus on population gating, hierarchical auditory coding, and self-voice mechanisms. 2025 Self-voice frequency analysis Hierarchical ferret auditory cortex mapping Temporal window constraints 2024 Premotor category hemodynamics Self-supervised sound structures Human speech cortical encoding Methodological Expertise: Combines awake ferret functional UltraSound, Neuropixels recordings, and computational modeling to analyze neural representations across spatial scales. Specializes in translating animal model findings to human auditory processes.

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Elisa PellegrinoView profile

Research Fellow

University of ZurichSwitzerland

Dr. Elisa Pellegrino is a senior Post-Doc in Phonetics at the Department of Computational Linguistics , affiliated with Zeppelin University and the Digital Society Initiative of the University of Zurich . Her research focuses on voice individualization, vocal accommodation, and the role of speaker-specific information in speech temporal variability. Role: Senior Post-Doc in Phonetics University: Zeppelin University School: Faculty of Arts and Social Sciences Department: Department of Computational Linguistics Email: elisa.pellegrino@uzh.ch Research Interests: Prosody and speech rhythm in native and second language acquisition Vocal accommodation in cross-dialectal interactions Speaker individuality and forensic phonetics Age-related speech temporal variability Speech disorders and Parkinson’s disease Applications of speech technology in linguistics and education

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Kurt KeutzerView profile

Professor

University of California, BerkeleyUnited States

Kurt Keutzer is a Professor in the Department of Electrical Engineering and Computer Science at the University of California, Berkeley, and a key member of the Berkeley AI Research Lab (BAIR). He holds a Ph.D. in Computer Science from Indiana University (1984) and was previously Chief Technical Officer at Synopsys, Inc. His research focuses on systems issues in deep learning, particularly for computer vision, speech recognition, NLP, and finance. He has published over 250 refereed articles and six books, and is a highly cited author in hardware and design automation. Keutzer has received multiple IEEE Fellowships, DAC awards, and best paper accolades at conferences like Embedded Vision Workshop and ICPP. Educations: 1984, PhD, Computer Science, Indiana University Kurt Keutzer's research interests span Artificial Intelligence , Computer Architecture , and Scientific Computing , with a focus on computational efficiency in AI systems. His work explores hardware-aware neural architecture search, domain adaptation, and quantization techniques to optimize models from edge to cloud. Recent publications highlight advancements in vision transformers , LLM inference efficiency , and autonomous driving . He also contributes to multimodal AI and self-supervised learning frameworks. Scientific Awards: Institute of Electrical & Electronics Engineers (IEEE) Fellow (1996) DAC's Most Influential Paper Award (2023) Top Ten Cited Author and Paper at DAC Best Paper Awards at Embedded Vision Workshop and ICPP Kurt Keutzer has advised numerous Ph.D. and Master’s students, including Forrest Iandola (co-founder of DeepScale), Sheng Shen, and Michael Murphy. His research teams have pioneered hardware-efficient deep learning solutions like SqueezeNet and FireCaffe. Current projects include optimizing large language models (LLMs) for edge deployment and advancing 3D reconstruction for autonomous vehicles. He is also involved in diffusion models , sparse attention mechanisms , and multi-agent coordination for complex tasks.

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Jon BarkerView profile

Professor

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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Edward F. ChangView profile

Professor

University of California, San FranciscoUnited States

Edward F. Chang, MD is a distinguished Professor and Chair of the Department of Neurological Surgery at the University of California, San Francisco (UCSF) School of Medicine. He co-directs the Center for Neural Engineering and Prostheses, a collaborative enterprise between UCSF and UC Berkeley, and leads the Chang Lab focused on speech neuroscience and neural engineering. As a practicing neurosurgeon, he specializes in treating adults with difficult-to-control epilepsy, brain tumors, trigeminal neuralgia, hemifacial spasm, and movement disorders. Dr. Chang's educational background includes a B.A. in Chemistry from Amherst College (1997), an M.D. from UCSF (2004), a Neurological Surgery residency at UCSF (2010), and a postdoctoral fellowship in Cognitive Neuroscience at UC Berkeley (2009). His research focuses on the brain mechanisms for speech, movement, and learning, with particular emphasis on advanced brain mapping methods to preserve crucial areas for speech and motor functions. He has pioneered work in speech neuroprostheses, developing technology that allows patients with paralysis to communicate through brain signals. His work integrates engineering, neurology, and neurosurgery to develop state-of-the-art biomedical technology to restore function for patients with neurological disabilities such as paralysis and speech disorders. Analysis of his recent publications reveals a strong trend toward developing advanced neuroprosthetic technologies, particularly speech decoding systems, and exploring the neural basis of speech production across multiple languages. His research also spans epilepsy surgery optimization, deep brain stimulation for psychiatric conditions, and molecular profiling of brain tumors. Blavatnik National Laureate for Life Sciences (2015) Elected to the National Academy of Medicine (2020) Inaugural Bowes Biomedical Investigator at UCSF HHMI Faculty Scholar Dr. Chang leads multiple NIH-funded research projects totaling millions of dollars, including a pilot clinical trial for speech neuroprosthesis and studies on the neural coding of speech across human languages. He has mentored numerous researchers in the field of neural engineering and speech neuroscience, though specific student names aren't listed in the provided materials. His work has resulted in groundbreaking technologies that have helped restore communication abilities to individuals with paralysis. As co-director of the Center for Neural Engineering and Prostheses, Dr. Chang leads a multidisciplinary team of engineers, neurologists, and neurosurgeons working at the intersection of neuroscience and technology. His lab has been instrumental in developing brain-computer interfaces that translate neural activity into speech, with recent publications demonstrating streaming brain-to-voice neuroprostheses that restore naturalistic communication.

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Alexey Evgenievich OsadchiyView profile

Professor

HSE UniversityRussia

Alexey Evgenievich Osadchiy is a Professor at the National Research University Higher School of Economics (HSE University), where he serves as Director of the Center for Bioelectric Interfaces at the Institute of Cognitive Neuroscience. He has been working at HSE since 2013 with 21 years of scientific and teaching experience. His academic appointments include Professor at the Faculty of Computer Science in the Department of Data Analysis and Artificial Intelligence. 2023 - Doctor of Science: National Research University Higher School of Economics 2003 - PhD: University of Southern California, specialty "Physical and Mathematical Sciences" and "Neurobiology" 1997 - Specialty: Bauman Moscow State Technical University, major in Autonomous Information and Control Systems Professor Osadchiy's research focuses on digital signal processing, magnetoencephalography (MEG), electroencephalography, inverse problems, synchronization, non-invasive detection, and brain mapping. His work bridges neuroscience, computer science, and medical applications, with particular emphasis on brain-computer interfaces, neurofeedback systems, and precision medicine applications for neurological disorders. He has pioneered methods for real-time brain activity monitoring and developed novel approaches for functional connectivity estimation in neural networks. His recent publications demonstrate a strong trend toward developing hardware-enabled low-latency systems for brain-state dependent stimulation, improving MEG technology with optically pumped magnetometers, and advancing speech mapping techniques for neurosurgical applications. His work increasingly integrates AI and deep learning approaches with traditional neuroimaging techniques to create more precise and accessible brain measurement and modulation systems. Scientific Awards and Recognition HSE University "Recognition - 10 Years of Successful Work" Medal (July 2025) Letter of Gratitude from the Higher School of Economics (September 2021) Letter of Gratitude from the Faculty of Computer Science at HSE (August 2018) Allowance for defending a doctoral dissertation (2023–2026) Bonuses for publications in international peer-reviewed journals (2015–2029) Professor Osadchiy has successfully advised numerous graduate students and doctoral candidates, with eight dissertation research projects currently under his supervision. His research has been supported by significant grants including a Russian Ministry of Education and Science contract for "System for registration and decoding of human brain bioelectric activity" (2014-2017), RFBR grants for "New non-invasive experimental-mathematical paradigm for preoperative magnetoencephalographic mapping of speech cortex" (14-02-00917, 16-04-01863), and projects on "Endogenous enhancement of brain-computer interface efficiency." As Director of the Center for Bioelectric Interfaces at the Institute of Cognitive Neuroscience, Professor Osadchiy leads a multidisciplinary team working on cutting-edge neurotechnology. His center collaborates with the Federal Brain and Neural Technology Centre at the Federal Medical and Biological Agency, where they established the Laboratory of Medical Neural Interfaces and Artificial Intelligence for Clinical Applications. The center is actively involved in developing brain-computer interfaces for rehabilitation, particularly for stroke patients and those with locomotor function disorders, and has created Russia's first neurointerface for controlling exoskeletons using imagined lower limb movements.

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Jacob WhitehillView profile

Associate Professor

Worcester Polytechnic InstituteUnited States

Jacob Whitehill is an Associate Professor in the Department of Computer Science at Worcester Polytechnic Institute (WPI), affiliated with the Learning Science & Technologies (LST) program. His research focuses on applying machine learning to education and human-computer interaction, including speech recognition, emotion analysis, and automated classroom observation. He leads the NSF-funded project Developing New Scientific Instruments for Classroom Observation and collaborates on the AI Institute for Student-AI Teaming (iSAT) . His research interests span Applied Machine Learning (e.g., multi-modal systems, speaker diarization), AI for Education (e.g., automated instructional evaluation, child speech recognition), and Emotion Recognition (e.g., affective computing in classrooms). Recent work emphasizes classroom observation tools and improving student-teacher interaction analysis through video and audio data. Notable projects include: NSF-funded classroom observation tools AI Institute for Student-AI Teaming (iSAT) Schmidt Futures-funded Hybrid Human-Agent Tutoring for math education His team includes PhD students Xinlu He (Data Science), Jiani Wang (Computer Science), and Yiwen Guan (Computer Science), along with visiting scholar Cecilia Tivir. He advises students on topics like speaker recognition, educational data mining, and computer vision in classroom settings. Grants and collaborations include NSF, Schmidt Futures, and industry partnerships. His lab develops tools for automated feedback on teaching practices, leveraging LLMs and multimodal data. For more details, contact jrwhitehill@wpi.edu .

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Patrick A StewartView profile

Professor

University of Arkansas FayettevilleUnited States

Patrick A Stewart serves as Professor and Director of Online Education in the Department of Political Science at the University of Arkansas, Fayetteville, within the College of Arts and Sciences. His research bridges political science, psychology, and technology, focusing on nonverbal communication dynamics in high-stakes political contexts. His educational trajectory includes an A.A. from St. Petersburg J.C. (1987), B.A. (1988) and M.A. (1991) from the University of Central Florida, and a Ph.D. from Northern Illinois University (1998). Stewart specializes in decoding emotional responses to political leaders' nonverbal behavior using Facial Action Coding System (FACS) methodology. His work examines micro-expressions, laughter, and audience reactions during debates, presidential addresses, and elections, with growing emphasis on AI biometrics ethics. This research has been published in PLoS ONE , Political Psychology , and Computers in Human Behavior , and featured in The New York Times , The Washington Post , and Vox . He co-created the educational game "Citizenship Quest" to explore trust-building in political simulations. Analysis of his recent publications reveals consistent focus on presidential communication effectiveness, particularly laughter and micro-expressions as leadership indicators. His work spans historical analyses (Reagan's "great communicator" persona) and contemporary events (Trump-era debates, Brexit), utilizing interdisciplinary methods combining ethology, biometrics, and game-based learning. No scientific awards were documented in the provided materials. Stewart directs online education initiatives while maintaining an active research agenda; no student advising details or grant information were specified in the source texts. His "Citizenship Quest" project represents applied efforts to translate political psychology research into educational tools.

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Jonathan ViventiView profile

Associate Professor

Duke UniversityUnited States

Jonathan Viventi is the Hawkins Family Associate Professor of Biomedical Engineering at Duke University, with additional appointments as Assistant Professor in Neurosurgery and Neurobiology, and as a Faculty Network Member of the Duke Institute for Brain Sciences. His research focuses on developing flexible, high-resolution neural interfaces for diagnosing and treating neurological disorders, particularly epilepsy, and advancing brain-machine interfaces. Education: Ph.D. in Engineering from the University of Pennsylvania (2010). Research Interests: Dr. Viventi's work centers on flexible electronics for high-resolution brain interfacing . Key areas include: Micro-electrocorticography (μECoG) arrays with thousands of channels Wireless, fully implantable neural prosthetics for speech restoration Real-time seizure detection and prediction systems Chronic biointegration of soft electronic materials Translational applications in epilepsy, stroke, and Parkinson's disease Scientific Awards: MIT Technology Review Innovators Under 35 (2014) Popular Science Brilliant 10 (2014) Grants & Funding: Dr. Viventi leads multiple NIH-funded projects including: A Wireless µECoG Prosthesis for Speech (2021-2026) Neuro-CROWN: Optimized Ultra-Flexible CMOS Electrode Arrays (2021-2025) Next-Generation Wireless Intracranial Arrays for Post-traumatic Epilepsy (2021-2025) Laboratory & Teams: His lab develops cutting-edge neural interface technologies, collaborating across engineering, neuroscience, and clinical departments at Duke to translate flexible electronics into therapeutic devices.

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Eamonn O'NeillView profile

Professor

University of BathUnited Kingdom

Eamonn O'Neill is a Professor and Head of the Department of Computer Science at the University of Bath. His research focuses on innovative human-technology interaction, including mixed/augmented/virtual reality, and interaction with intelligent systems. His work emphasizes applied science, deriving design principles grounded in theory and empirical testing. He leads the UKRI CDT in Accountable, Responsible and Transparent AI and is affiliated with multiple centers, including the Centre for the Analysis of Motion, Entertainment Research & Applications (CAMERA) and the REal and Virtual Environments Augmentation Labs (REVEAL). His projects span EU-funded initiatives such as EMIL and UNREST, addressing topics like embodied interaction, AI regulation, and social cohesion. Recent research explores emotion recognition in VR exergaming, EEG-based brain-computer interfaces, and regulatory frameworks for AI. His work contributes to UN Sustainable Development Goals related to innovation and infrastructure. Collaborations include academic institutions and industry partners across Europe.

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Glenn GulakView profile

Professor

University of TorontoCanada

Glenn Gulak is a Professor in the Department of Electrical and Computer Engineering at the University of Toronto's Faculty of Applied Science and Engineering. He holds the Canada Research Chair in Signal Processing Microsystems and the Edward S. Rogers Sr. Chair in Engineering. A Senior IEEE Member and Professional Engineer in Ontario, he received his Ph.D. from the University of Manitoba. His research spans: Digital Communication Systems: VLSI implementations of MIMO detectors, lattice reduction algorithms, and homomorphic encryption accelerators Lab-on-Chip Microsystems: CMOS biosensors for rapid pathogen detection and integrated fluorescence imaging Recent publications (2019-2025) demonstrate a dominant focus on privacy-enhancing technologies, with 73% concentrated in cryptographic hardware and homomorphic encryption. This reflects industry-aligned work on confidential computing and secure data processing. Awards & Honors: IEEE Millennium Medal (2001) Canada Research Chair in Signal Processing Systems (Tier 1, 2005-2012) Edward S. Rogers Sr. Chair (2005-2010) RBC Research Prize L. Lau Chair (1999-2004) Teaching Award (1999) He has supervised 44+ graduate students (PhD/MASc) with thesis topics spanning VLSI communication systems, CMOS biosensors, and cryptographic accelerators. Notable industry collaboration includes serving as CTO of a semiconductor startup (2001-2003). His lab develops hardware for quantum cryptography and secure medical computation.

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Jayneel ParekhView profile

Research Fellow

Télécom ParisFrance

Jayneel Parekh is a Postdoctoral Researcher in the MLIA (Machine Learning and Artificial Intelligence) team at ISIR (Institut des Sciences et Industries du Réel), Faculty of Science, Sorbonne University, working with Prof. Matthieu Cord. His research focuses on understanding and enhancing large multimodal models, with applications across audio, visual, and multimodal domains. Parekh completed his PhD at LTCI, Telecom Paris under Prof. Florence d'Alche and Prof. Pavlo Mozharovskyi, researching neural network interpretability applied to image and audio data. He earned his undergraduate degree in Electrical Engineering from IIT Bombay, where he worked with Prof. Preeti Rao and Prof. Yi-Hsuan Yang on Speech-to-Singing conversion. His research spans neural network interpretability, audio processing, computer vision, and multimodal models, with emphasis on explainable AI. His work demonstrates a consistent trajectory from foundational audio/image interpretability methods to cutting-edge large multimodal model analysis, showing increasing complexity and impact across NeurIPS, ICML, and ICCV publications. L2I paper awarded 2nd prize for STIC Best Scientific Contribution 2023 Top Reviewer at NeurIPS 2023 Parekh actively contributes to the academic community through workshop organization (ICCV on Explainable Computer Vision, ELLIS Unconference on Robustness/Fairness/Explainability) and presentations at institutions including IIT Jodhpur, Deezer Research, and IBM Research. His collaborative network spans MPI Informatics, TU Darmstadt, TU Munich, and Télécom Paris.

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Stephanie RièsView profile

Associate Professor

San Diego State UniversityUnited States

Stephanie Riès is an Associate Professor in the Department of Speech, Language, and Hearing Sciences at San Diego State University, where she directs the Laboratory for the Brain Dynamics of Language. Her research specializes in the cognitive neuroscience of human language, examining brain dynamics in language production, control processes, and neural reorganization following brain disorders. Education: BS in Biology from University of Rennes 1 MS in Cognitive Neuroscience from Aix-Marseille University MS in Cellular Biology and Animal Physiology from University of Rennes 1 PhD in Cognitive Neuroscience from Aix-Marseille University Her work integrates electrophysiology (EEG, EMG) and neuroimaging to study language production mechanisms and compensatory plasticity in conditions like stroke, epilepsy, and brain tumors. Key research areas include bilingual interference resolution, speech monitoring mechanisms, and neural reorganization patterns. Recent publications focus on neural hierarchies in speech production, neuroplasticity in language recovery, and advanced brain mapping techniques. Article analyses reveal strong emphasis on electrophysiological methods (sEEG, ERP), bilingual cognition, and clinical translation of neuroscience findings. Dr. Riès leads significant research initiatives through her laboratory, investigating brain-behavior relationships using intracranial recordings and developing novel approaches for speech activity detection across neurological populations.

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Luis Jose Fuentes MeleroView profile

Professor

University of MurciaSpain

Luis Jose Fuentes Melero is a Full Professor of Basic Psychology at the University of Murcia, Spain, affiliated with the Faculty of Psychology and Speech Therapy. His career includes leadership roles in research groups such as the Cognitive Neuroscience Laboratory and the former Neuropsychology of Attention group at the University of Almería (1988–2004). He holds a PhD in Psychology from the University of Granada (1987), supervised by Dr. Pío Tudela Garmendia. Research Focus: Cognitive neuroscience, attention mechanisms, differential outcomes procedure, neurodegenerative diseases, and educational psychology. Affiliations: Principal investigator in projects funded by the Spanish Ministry of Science and Innovation (Consolider Ingenio 2010, Plan Nacional I+D+i) and Fundación Séneca. His work combines experimental psychology with neuroimaging, focusing on attention deficits, aging, and applied behavioral interventions. He has supervised 17 doctoral theses and contributed to over 200 publications, with an h-index of 32. Collaborations include institutions like the Virgen de la Arrixaca Hospital and Oxford University. Notable achievements include developing the Differential Outcomes Procedure (DOP) to enhance learning and memory, and pioneering studies on electrical brain stimulation for attention and memory improvement (e.g., PID2021-125408NB-I00 project).

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