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Anne KoelewijnView profile

Assistant Professor

• Human Movement
• Optimal Control
• In the wild movement analysis
• +4 more

Dr. Anne Koelewijn is an Assistant Professor leading the Biomechanical Motion Analysis and Creation (BioMAC) group at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) since 2019. Her research bridges biomechanics, computational modeling, and wearable technology to analyze human movement. She holds a Junior Professorship in Computational Movement Science within the Department of Electrical-Electronic-Communication Engineering. Her educational background includes a Doctor of Engineering in Mechanical Engineering from Cleveland State University (focus: prosthesis design and gait simulations), an MSc in Mechanical Engineering (BioMechanical Design specialization), and a BSc in Aerospace Engineering , both from Delft University of Technology. She completed postdoctoral work at École Polytechnique Fédérale de Lausanne on neuromuscular control. Research interests center on human movement optimization , neuromuscular control mechanisms , and in-the-wild movement analysis . Her work integrates musculoskeletal modeling, optimal control theory, and machine learning to study gait adaptations, exoskeleton design, and pathological movement patterns (e.g., Parkinson’s disease). Publications emphasize predictive simulations , wearable sensor technology , and biomechanical energy optimization , with recent advances in radar-based motion capture, inertial pose estimation, and digital twin applications for medical engineering. Promising Scientist Award , International Society of Biomechanics (2023) Best Paper Award , 5th International Symposium on Wearable Robotics (2020) She leads the BioMAC research group, focusing on computational methods for movement science and collaborating internationally on projects involving exoskeletons, injury prevention, and neuroprosthetics.

Usha GoswamiView profile

Professor

• Cognitive Developmental Neuroscience
• Developmental Psychology
• Educational Neuroscience
• +7 more

Professor Usha Goswami is a leading academic in Cognitive Developmental Neuroscience at the University of Cambridge, serving as Professor of Cognitive Developmental Neuroscience and Director of the Centre for Neuroscience in Education. She is also a Fellow at St John's College, Cambridge. Her work focuses on understanding the neural and cognitive foundations of language acquisition, reading development, and developmental disorders such as dyslexia. Key areas of interest include the role of rhythm perception, speech processing, and EEG-based studies of neural entrainment in typical and atypical development. Her research integrates insights from neuroscience, cognitive psychology, and education, emphasizing translational approaches to improve literacy interventions. She has conducted longitudinal studies on infants and school-aged children, examining predictors of language outcomes and the impact of rhythmic training on executive function. Her work bridges developmental linguistics, auditory neuroscience, and educational policy, with a focus on universal speech structures in child-directed communication. Professor Goswami’s contributions include pioneering studies on the neural basis of phonological awareness and the application of machine learning to decode speech information from EEG data in infants. She has also explored cross-linguistic patterns in poetry and infant-directed speech, highlighting universal acoustic features underlying language acquisition. Her research has significant implications for understanding and remediating developmental disorders, particularly dyslexia and developmental language disorder. Her lab, the Centre for Neuroscience in Education, focuses on translating neuroscientific findings into practical educational strategies. Current projects include investigating rhythm-based interventions for children with language difficulties and analyzing the acoustic properties of speech in diverse linguistic contexts.

Jiaxiang ZhangView profile

Professor

• Artificial Intelligence
• Machine Learning
• Cognitive Neuroscience
• +2 more

Jiaxiang Zhang is Professor of Artificial Intelligence in the Department of Computer Science at Swansea University's Faculty of Science and Engineering. He holds a PhD in Computational Neuroscience from the University of Bristol and previously held positions at the University of Birmingham, MRC Cognition and Brain Sciences Unit (Cambridge), and Cardiff University where he founded the Cognition and Computational Brain Lab. Zhang's research integrates computational modeling, machine learning, brain imaging (MEG/EEG/fMRI), and experimental approaches to study human cognition, aging, and neurological disorders. Key focus areas include: Neural mechanisms of decision-making and problem-solving Computational models of cognitive processes AI applications in healthcare diagnostics and neuroimaging Brain network dynamics in neurological conditions Recent publications emphasize deep learning models for neural data, multimodal brain connectivity, decision-making impairments in Parkinson's disease, and neuroinformatics tools. His work shows strong clinical translation through epilepsy biomarker development and emergency department outcome prediction. Zhang has led research grants from ERC, MRC, BBSRC, and Wellcome Trust. As primary investigator for multiple projects, he oversees significant computational neuroscience initiatives. He is available for postgraduate supervision.

Petr JanataView profile

Professor

• Cognitive Neuroscience
• Music Psychology
• Auditory Perception
• +4 more

Petr Janata is a Professor in the Department of Psychology at the University of California, Davis, and a faculty member at the UC Davis Center for Mind and Brain. His research centers on cognitive neuroscience of music, investigating neural mechanisms underlying music-evoked autobiographical memories and the experience of "groove." He serves on the Board of the Society for Music Perception and Cognition and co-founded the UC Music Experience Research Community Initiative (UC MERCI). Janata's educational background includes: Ph.D. in Biology (Neuroscience) from the University of Oregon (1996) B.A. in Interdisciplinary Studies (Biology/Psychology) from Reed College (1990) His research employs behavioral experiments, fMRI, EEG, and computational modeling to explore how music engages memory, emotion, and sensorimotor systems. Key projects examine music-evoked remembering, the psychology of groove, auditory attention mechanisms, and timbre-emotion links. His work reveals how music activates domain-general brain networks for expectation, memory, and emotional processing. Recent publications (2018-2025) show increasing focus on cross-cultural emotional responses to music, neural correlates of nostalgia, mental replay mechanisms, and clinical applications of music cognition. His lab develops innovative paradigms like the Groove Enhancement Machine (GEM) to manipulate sensorimotor synchronization while measuring subjective enjoyment. Janata's scientific recognition includes: Guggenheim Fellowship (2010) Dual Fulbright Fellowships (1990-91, 2010-11) Music Has Power Award from the Institute of Music and Neurological Function (2010) He has delivered over 100 invited lectures globally and served as scientific advisor to Coro Health LLC before founding Meamer, Inc. in 2017 to connect people through memories and music. His translational work bridges basic cognitive neuroscience with real-world applications in health and technology. The Janata Lab at UC Davis integrates neuroimaging, behavioral testing, and computational modeling to advance understanding of music cognition. Current projects explore lifespan neural changes in music processing, adaptive virtual partners for synchronization studies, and sonification systems for physiological monitoring.

• Computational Neuroscience
• Neurobiology
• Visual Cortex
• +3 more

Mario Dipoppa is an Assistant Professor in the Department of Neurobiology at the University of California, Los Angeles. His research focuses on computational neuroscience, cortical adaptation, and neural circuit dynamics. Position: Assistant Professor, Neurobiology Email: mdipoppa@g.ucla.edu Research Interests: Mario's work explores how neural populations in the visual cortex adapt to sensory input, with a particular emphasis on the interplay between neural oscillations, synchrony, and cognitive functions like working memory. His recent studies investigate optimal coding strategies in visual adaptation, contextual modulation mechanisms, and the role of transcriptomic diversity in cortical interneuron function. Publications Trends: His research spans computational modeling of cortical networks, visual neuroscience, and neurogenetic analyses of brain circuits. Early work (2013-2016) focused on working memory mechanisms and neural oscillations, while recent studies (2022-2025) emphasize visual cortex adaptation, population coding, and cross-species circuit comparisons.

Surjo R. SoekadarView profile

Professor

• Clinical Neurotechnology
• Brain-Computer Interfaces (BCI)
• Neuromodulation
• +8 more

Surjo R. Soekadar is the Einstein Professor of Clinical Neurotechnology at Charité – University Medicine Berlin. He leads the Clinical Neurotechnology Laboratory , which focuses on developing noninvasive neurotechnologies for treating neurological and psychiatric disorders through closed-loop brain stimulation and advanced brain-machine interfaces (BCI/BMI). His work integrates real-time EEG/MEG monitoring with electromagnetic stimulation to modulate pathological brain oscillations and enhance neuroplasticity in conditions like stroke, spinal cord injury, and psychiatric disorders. Education : Studied medicine in Mainz, Heidelberg, and Baltimore Clinical Training : Residency in Psychiatry and Psychotherapy at University of Tübingen Academic Journey : 2008-2011 Research Fellow at NINDS (USA); 2017 Venia Legendi at University of Tübingen; 2018 First Professor of Clinical Neurotechnology in Germany His research interests span: • Closed-loop neurostimulation combining real-time brain state monitoring with targeted intervention • Next-generation BCI using optically pumped magnetometers (OPM) for mobile MEG recordings • Neurorehabilitation through exoskeleton control and sensory feedback • Neurophysiological modeling of entropy measures and phase flows Recent publications highlight: • Adaptive deep brain stimulation protocols • Real-time phase-sensitive tACS applications • OPM-based BCI innovations • Stroke recovery mechanisms through corticospinal tract analysis Scientific recognition includes: International BCI Research Award BIOMAG Award NARSAD Young Investigator Award Funded by the European Research Council (ERC) , his lab trains doctoral students like David Haslacher (EEG/MEG integration), Khaled Nasr (multicoil TMS optimization), and Annalisa Colucci (entropy-driven BCI development). The team also explores quantum AI applications in clinical decision-making and bidirectional BCI systems using OPM and tES.

Alexey Evgenievich OsadchiyView profile

Professor

• digital signal processing
• magnetoencephalography
• electroencephalography
• +9 more

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.

Fausto CaruanaView profile

Adjunct Professor

• Cognitive Neuroscience
• Affective Neuroscience
• 4E Cognition (Embodied, Embedded, Extended, Enactive)
• +5 more

Fausto Caruana is Senior Researcher at the Italian National Research Council's Institute of Neuroscience and Adjunct Professor at the University of Parma's Department of Medical and Surgical Sciences (DIMEC). His career bridges neurophysiology , cognitive neuroscience , and neurophilosophy , focusing on mirror neuron systems , emotional contagion , and embodied cognition . Research Pillars : System neuroscience, laughter studies, social cognition, and 4E cognitive science Methodological Expertise : Intracranial EEG, brain stimulation, tractography, and cross-species comparisons His publications (over 100) demonstrate temporal progression from primate electrophysiology to human clinical neuroscience. Key themes include: Laughter's neurochemical and network basis Insula-cingulate pathways in emotional processing Sensorimotor abductive mechanisms in social cognition Pragmatist approaches to emotion theories Scientific recognition includes the prestigious Sante de Sanctis Prize for his volume "Come Funzionano Le Emozioni". He serves editorial boards for Frontiers in Theoretical Psychology and Mind & Society , while organizing international conferences like the 2024 Erice workshop on Emotional Expressions.

Jordan TaylorView profile

Professor

• Motor Control
• Neuroscience
• Computational Motor Learning
• +2 more

Professor Jordan Taylor is affiliated with Princeton University as a faculty member in the Department of Biomedical Engineering within the School of Engineering and Applied Science. His research focuses on unraveling computational processes in motor control and learning, with particular emphasis on interactions between explicit cognitive strategies and implicit motor adaptation during skill acquisition. Taylor leads the Intelligent Performance and Adaptation Laboratory , aiming to develop optimal training protocols for motor rehabilitation post-stroke or disease. Research Interests : Taylor investigates how humans learn motor skills through dual mechanisms of declarative strategy formation and implicit neural adaptation. His work explores the neural systems underlying these processes and their functional consequences, especially in pathological conditions like cerebellar degeneration. Current studies examine working memory constraints, reward modulation of implicit adaptation, and plan-based generalization of motor learning. Publication Trends : Recent articles analyze dual mechanisms in sensorimotor learning, reward-driven adaptation, and contextual influences on motor memory. His computational neuroscience approach combines behavioral experiments, neural imaging, and theoretical modeling to study cognitive-motor interactions across various tasks.

• Brain-Computer Interface
• Biomedical Engineering
• Neuroprosthetics
• +5 more

Prof. Dr. Gernot R. Müller-Putz is Head of the Institute of Neural Engineering and the Graz Brain-Computer Interface Lab at Graz University of Technology. He serves as Dean of the Faculty of Computer Science & Biomedical Engineering and holds editorial roles at Frontiers in Human Neuroscience IEEE Transactions in Biomedical Engineering Brain-Computer Interface Journal . With over 212 peer-reviewed publications and an h-index of 80, his research focuses on Brain-Computer Interfaces , Neuroprosthetics , and EEG-based Motor Control . His work investigates: Neural signal decoding for spinal cord injury rehabilitation Hybrid BCI systems with error processing Artificial sensory feedback mechanisms Machine learning applications in neural engineering VR-based neurofeedback environments Non-invasive multimodal biosignal recording Research trends show strong emphasis on EEG signal processing , BCI clinical applications , and neurotechnology integration . Scientific Awards : ERC Consolidator Grant (2015) Ludwig-Guttman Award (2017) CYBATHLON Best Paper (2019) State of Styria Research Award (2019) Förderstipendium (2013-2014) He advises 21 PhD students and has managed major projects like MoreGrasp (EU Horizon 2020) , Feel Your Reach (ERC) , and INTRECOM (EU EIC Pathfinder) . The Institute hosts the BCI Racing Team Mirage91 and offers international thesis opportunities.

Qiushi FuView profile

Associate Professor

• Neuromuscular Control
• Human-Robot Interaction
• Biomechanics
• +5 more

Qiushi Fu is an Associate Professor in the Department of Mechanical and Aerospace Engineering at the University of Central Florida, focusing on neuromuscular control, human-robot interaction, and biomechanics. His work leverages assistive and rehabilitation technologies to improve motor function and performance. Ph.D. in Biomedical Engineering – Arizona State University M.S. in Mechanical Engineering – State University of New York at Buffalo B.S. in Automation – Tsinghua University Research interests include sensorimotor learning, bioinspired robotics, and rehabilitation prosthetics, integrating neuroscience, robotics, and machine learning. His recent publications emphasize adaptive control in dexterous manipulation, haptic communication, and wearable rehabilitation devices. Fu leads a multidisciplinary lab advancing human movement through technology, with applications in stroke recovery and prosthetic design. His work demonstrates trends in machine learning integration for neural decoding, bioinspired exoskeletons, and collaborative human-robot systems. Though no specific awards are listed, his research has been published in high-impact journals like Frontiers in Neurorobotics and Journal of Neuroscience .

Kristina BackerView profile

Assistant Professor

• Cognitive Neuroscience
• Auditory Processing
• Bilingualism and Cognition
• +3 more

Kristina Backer is an Assistant Professor in the Department of Cognitive and Information Sciences at the University of California, Merced. Her research focuses on cognitive neuroscience, auditory processing, and the intersection of sensory systems with higher-order cognition. She employs methods such as EEG, fMRI, and behavioral experiments to investigate topics like bilingualism effects, neuroplasticity in aging, and multisensory integration mechanisms. Her work explores how auditory and visual systems interact, particularly in phenomena such as the McGurk illusion and the continuity illusion in musicians. She also examines how auditory cues influence motor timing and the neural mechanisms underlying attentional modulation in short-term memory. Backer’s studies often involve clinical populations, such as children with cochlear implants and older adults with hearing loss, to understand the cognitive and neurophysiological impacts of sensory deficits. Key research themes include the temporal dynamics of sensory processing, the neural basis of cross-modal perception, and individual differences in cognitive abilities linked to language experience and aging. Her experimental methods emphasize electrophysiological techniques combined with computational modeling to dissect neural correlates of perception and cognition. Backer’s publications highlight advancements in understanding auditory-motor integration, neuroplasticity in bilingualism, and the development of rapid diagnostic tools for sensory pathway assessment. Her research bridges fundamental neuroscience with clinical applications, aiming to improve rehabilitation strategies for auditory and cognitive impairments.

• Cognitive Psychology
• Neuroscience
• Neurophysiology
• +3 more

Prof. I. Toni (Ivan) is a Professor of Cognitive Psychology at the Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen. He leads the Intention & Action research group, focusing on the neural mechanisms underlying instrumental and communicative actions. Research Interests: Integration of perceptual, conceptual, and rule-based information into sensorimotor processes Neural substrates of goal-directed movements (object prehension, tool use) Computational models of communicative innovation and shared symbol systems Role of lateral occipito-temporal, inferior parietal, and premotor cortices in action planning Research Grants: 2022-2027: ERC Advanced Grant (€2.5m) for "Human communication as joint epistemic engineering" 2021-2027: NWO-STW Open Competition Grant (€0.75m) on social-emotional regulation 2017-2022: NWO Language in Interaction Consortium Grant (€1.5m) for "Creating a shared cognitive space" 2011-2015: NWO Grant (€500k) on mental simulation 2009-2014: NWO-MAGW VICI Grant (€1.3m) for "Raising glasses and pointing fingers" Editorial Roles: Senior Editor, The Journal of Neuroscience (since 2012)

Utku YavuzView profile

Assistant Professor

• Biomedical Engineering
• Neurophysiology
• Neuromuscular Systems
• +5 more

Dr. Utku Yavuz is an Assistant Professor in the Biomedical Signals and Systems Department at the TechMed Centre. His expertise spans neuromuscular physiology, wearable sensor technologies, and clinical monitoring systems. He holds a PhD in Biomedical Engineering from Ege University, complemented by earlier degrees in Physics Engineering (Hacettepe University) and Biophysics (Hacettepe University). Research Focus: Motor unit physiology, neuromuscular modeling, and clinical applications of wearable sensors. Key Areas: Spinal motor neuron behavior, electromyography (EMG), and translational technologies for diabetes and musculoskeletal health. Dr. Yavuz’s work bridges neuroscience and engineering, addressing challenges in prosthetic design, real-time neuromuscular signal decoding, and improving clinical decision-making through sensor data analysis. Recent studies include optimizing wearable glucose monitors and analyzing muscle-tendon dynamics in amputees. His research outputs span 43 publications, with contributions to high-impact journals like BMC Digital Health and IEEE Sensors Journal . Collaborations include institutions focused on biomechanics, robotics, and clinical informatics. Advising: Supervised 1 graduate project, though specific advisee names are not listed. Active in academic activities such as thesis examinations and conference presentations.

Dongheui LeeView profile

Assistant Professor

• Human motion understanding
• Physical human-robot interaction
• Machine learning in robotics
• +5 more

Dongheui Lee is an Assistant Professor at the Institute of Automatic Control Engineering (LSR) within the Faculty of Electrical Engineering and Information Technology at Technische Universität München (TUM). She leads the Dynamic Human Robot Interaction for Automation System Lab. Her research focuses on human motion understanding, physical human-robot interaction, and machine learning in robotics. Education: B.S. and M.S. in Mechanical Engineering from Kyunghee University (2001-2003), PhD in Mechano-Informatics from the University of Tokyo (2007). Prior roles include research scientist at KIST Korea (2001-2004) and project assistant professor at the University of Tokyo (2007-2009). Research Interests: Human-robot collaboration, probabilistic robotics, motion recognition, and incremental lifelong learning mechanisms. She has contributed to advancements in motion primitives, compliant physical interaction, and real-time object tracking. Selected Awards: Finalist for KUKA Service Robotics Best Paper Award (2009), Hirose Scholarship (2006-2007), and multiple grants from KRF, KOSEF, and international robotics competitions. Key Publications: Focus on prioritized inverse kinematics, motion imitation, and adaptive control systems. Her work bridges robotics theory and practical applications in humanoid robots and human-robot interaction.