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Ernesto Elias Vidal RosasView profile

Lecturer

• Neuroimaging
• Brain-computer interfaces
• Medical optics imaging
• +2 more

Dr. Ernesto Elias Vidal Rosas is a Lecturer at the School of Electronics and Computer Science, University of Southampton. Previously, he was a Postdoctoral Researcher at UCL Medical Physics and Biomedical Engineering Department. He specializes in neuroimaging and optical technologies with extensive expertise in near-infrared spectroscopy (NIRS), diffuse optical tomography (DOT), and wearable brain imaging systems. He is currently accepting PhD students. Research Focus: Dr. Vidal-Rosas leads research in neuroimaging methodologies and brain-computer interfaces. His work emphasizes wearable technologies for clinical and home-based monitoring, with applications spanning from neonatal care to motor rehabilitation. Key research domains include: Development of high-density diffuse optical tomography (HD-DOT) systems Integration of EEG and fNIRS for brain-computer interfaces Real-time processing algorithms for neurofeedback applications Non-invasive monitoring of therapeutic responses in oncology He is currently involved in the Horizon Europe PUREMIND project focused on preventing mental illness through multimodal biomarker analysis. Academic Activities: Actively advises PhD candidates in Computer Science and teaches undergraduate courses including Healthcare Technology Design (ELEC2231) and Digital Control System Design (ELEC3206). His pedagogical research includes developing virtual tools for engineering education. Affiliations: Member of the Digital Health and Biomedical Engineering research group and the Institute for Life Sciences at Southampton.

Marc SommerView profile

Professor

• Neuroscience
• Biomedical Engineering
• Neural Circuits
• +5 more

Marc Sommer is a Professor of Biomedical Engineering and Psychology & Neuroscience at Duke University. He directs the Duke Institute for Brain Sciences and contributes to the Duke Initiative for Science & Society. His research focuses on neural circuits for cognition , particularly how the brain maintains visual perception and behavior through interactions between frontal cortex and subcortical regions. Key Techniques : Single neuron electrophysiology, optogenetics, psychophysics, computational modeling Translational Goals : Improving transcranial magnetic stimulation (TMS) and viral vector therapies for psychiatric and motor disorders Scientific Awards : Capers and Marion McDonald Award for Excellence in Teaching and Research (2021) Capers and Marion McDonald Award for Excellence in Mentoring and Advising (2017) Bass Fellow, Duke University (2017) Research Fellowship in Neuroscience, Alfred P. Sloan Foundation (2005) Marc Sommer's recent publications span visual stability across saccades , optogenetics in primates , TMS mechanisms , and viral vector applications . His work bridges cognitive neuroscience and biomedical innovation , with significant contributions to corollary discharge theory and neural circuit mapping . Lab Collaborations : Interdisciplinary partnerships across Duke University and external institutions, integrating engineering , neurobiology , and computer science to decode primate brain circuitry.

Christian Grefkes-HermannView profile

Professor

• Stroke Rehabilitation
• Neural Plasticity
• Brain Connectivity
• +4 more

Christian Grefkes-Hermann serves as Professor of Neurology at Goethe University Frankfurt's Faculty of Medicine, based at University Hospital Frankfurt's Center of Neurology and Neurosurgery. His research targets stroke-induced brain network disruptions and develops novel rehabilitation strategies using non-invasive brain stimulation to restore motor function. His work focuses on neural plasticity, brain connectivity, and stroke rehabilitation through multimodal approaches including structural/functional MRI, EEG, transcranial magnetic stimulation (TMS), and machine learning. He investigates how interhemispheric network reorganization enables functional recovery and develops biomarkers for personalized rehabilitation protocols. Analysis of his publication history reveals an evolution from foundational studies on crossmodal processing (2002) to clinical applications in stroke recovery, with recent work emphasizing individualized biomarkers and frontoparietal connectivity as predictors of motor recovery. This trajectory demonstrates a consistent translation of basic neuroscience into clinical neurorehabilitation. Professor Grefkes-Hermann leads a research team within the Center of Neurology and Neurosurgery dedicated to bridging neural network science with practical rehabilitation solutions for stroke survivors, addressing Germany's challenge of 200,000 annual stroke cases where over 50% experience permanent disability.

Karim OweissView profile

Professor

• Neuroscience
• Biomedical Engineering
• Electrical Engineering
• +5 more

Karim Oweiss is a Pre-eminent Professor at the University of Florida, with joint appointments in the Department of Biomedical Engineering (Herbert Wertheim College of Engineering), Electrical and Computer Engineering, and Neuroscience (McKnight Brain Institute). He holds a Ph.D. in Electrical Engineering and Computer Science from the University of Michigan (2002). His research focuses on neural mechanisms of sensorimotor integration and the development of clinically viable brain-machine interfaces (BMIs) to restore damaged neurological function. His work spans computational neuroscience, neural decoding, optogenetics, and advanced neurotechnology, with a strong emphasis on closed-loop systems and neural plasticity. 2025 : Chemogenetic stimulation of phrenic motor output and diaphragm activity 2024 : Chemogenetic phrenic motoneuron activation enables increased tidal volume 2023 : Compressive sensing of functional connectivity maps from patterned optogenetic stimulation Oweiss has received the NSF Excellence in Neural Engineering Award (2001) and is a Senior Member of the IEEE. He has published extensively on topics including neural decoding, compressive sensing, and multiscale neural interfacing. As editor of Statistical Signal Processing for Neuroscience and Neurotechnology (2010), he has contributed significantly to the field's methodological foundations. His lab develops tools like NeuroQuest for large-scale neural data analysis and implantable neuroprocessors for wireless BMI applications.

Dana BrooksView profile

Research Professor

• Biomedical Signal Processing
• Medical Imaging
• Statistical Signal Processing
• +8 more

Dana Brooks is a Research Professor in the Department of Electrical and Computer Engineering at Northeastern University, with affiliations in Bioengineering. He holds a PhD from Northeastern University (1991) and has received the Søren Buus Outstanding Research Award (2006). His primary research focuses on biomedical signal and image processing, medical imaging techniques (including MRI and electrocardiography), and neuromodulation technologies such as transcranial magnetic stimulation (TMS). He is also involved in protein conformation estimation using X-ray scattering and optimization algorithms for medical applications. Dr. Brooks leads the Biomedical Signals Processing Lab and collaborates with the Center for Integrative Biomedical Computing . His work bridges engineering and medicine, with recent grants including a $400K NSF MRI grant for advanced TMS systems and a $600K NSF grant for motor cortical organization studies. He has advised students like Setareh Ariafar (PhD’20) and contributed to innovations in image mosaicking for confocal microscopy and machine learning applications in dermatology. His publications span computational neuroscience, cardiac imaging, and uncertainty quantification in biomedical simulations. Notable achievements include developing algorithms for ECG imaging, optimizing TMS protocols, and creating tools like UncertainSCI for simulation reliability assessment.

Mia LiljeströmView profile

Researcher

• Magnetoencephalography
• Functional Connectivity
• Brain Networks
• +3 more

Mia Liljeström is a Staff Scientist at the Department of Neuroscience and Biomedical Engineering, Aalto University. She holds a Doctoral Degree in Engineering and Technology from Aalto University (2010) and a Master's Degree in Engineering and Technology from Helsinki University of Technology (2002). Doctoral Degree: Aalto University, 2010 Master's Degree: Helsinki University of Technology, 2002 Her research focuses on Magnetoencephalography (MEG) , Functional Connectivity , and Brain Networks . She explores Transcranial Magnetic Stimulation (TMS) , Functional MRI , and Neural Networks to map language-critical brain areas and study cortical dynamics. Recent work includes automated speech artefact removal from MEG data and test-retest reliability of brain connectivity metrics. Mia actively participates in conferences like MEG Nord and has presented invited talks on language processing and large-scale brain networks. Her publications emphasize MEG-informed TMS, cortical beta modulation, and brain stimulation precision. She contributes to the UN Sustainable Development Goal of Quality Education through neuroimaging research.

Enrico OpriView profile

Assistant Professor

• Neuromodulation
• Deep Brain Stimulation (DBS)
• Neurological Disorders
• +4 more

Dr. Enrico Opri is an Assistant Professor in the Department of Biomedical Engineering at the University of Michigan , where he directs the Opri Lab. His research focuses on engineering novel methodologies to automate and enhance clinical procedures in neuromodulation for neurological disorders such as Parkinson’s, Tourette syndrome, essential tremor, and epilepsy. Research Focus Neurophysiological activity in basal ganglia-thalamocortical circuits Therapeutic effects of neuromodulation (e.g., Deep Brain Stimulation, cortical stimulation mapping) Identification of neurological biomarkers for improved clinical procedures Advancements in closed-loop neurostimulation systems Article Trends Dr. Opri's recent publications emphasize closed-loop deep brain stimulation (DBS) systems, computational modeling of neural activity, and the identification of biomarkers for neurological disorders. Key subfields include Parkinson’s disease motor dynamics, Tourette syndrome tic detection, essential tremor treatment, and cortico-thalamic coupling mechanisms. His work bridges biomedical engineering and clinical neuroscience, focusing on translating technological innovations into therapeutic applications.

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.

Leila WehbeView profile

Associate Professor

• Machine Learning
• Cognitive Neuroscience
• Neuroscience
• +4 more

Leila Wehbe is an Associate Professor in the Machine Learning Department and Neuroscience Institute at Carnegie Mellon University (CMU), with affiliations in Psychology and Computational Biology. She leads a research group focused on understanding high-level brain representations of language and vision using machine learning techniques. Her work combines neuroimaging (fMRI/MEG) with computational models to investigate how the brain processes meaning and visual stimuli. Education : PhD in Machine Learning from CMU, advised by Tom Mitchell BE in Electrical and Computer Engineering from the American University of Beirut Postdoc at UC Berkeley's Helen Wills Neuroscience Institute with Jack Gallant Research Interests : Her research bridges cognitive neuroscience and AI, focusing on: Decoding language and visual processing from brain activity Developing machine learning models aligned with brain representations Investigating semantic composition in language Exploring visual cortex selectivity for objects/food Improving neural decoding with advanced methods (e.g., transformers, generative models) Awards & Recognition : NSF CAREER Award (2022) NIH R21/R01 Awards Human Frontier Science Program Award Google Faculty Research Award Grants & Labs : Leads the Wehbe Lab, part of brAIn at CMU. Active in grant programs including NSF and NIH, focusing on language-brain alignment and visual cortex studies. Co-organized workshops at ICLR and CVPR on brain-inspired AI.

Edward F. ChangView profile

Professor

• Neurosurgery
• Neuroscience
• Speech Neuroscience
• +7 more

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.

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.

Siegrid LöwelView profile

Professor

• Systems Neuroscience
• Neural Plasticity
• Cortical Development
• +7 more

Siegrid Löwel is a Full Professor of Systems Neuroscience at the University of Göttingen, affiliated with the Department of Systems Neuroscience within the Johann-Friedrich-Blumenbach-Institute for Zoology and Anthropology. She is also a Board Member of the Göttingen Campus Institute for Dynamics of Biological Networks since 2021, highlighting her leadership in interdisciplinary neuroscience research. Her educational background includes a Dr. phil. nat. from the University of Frankfurt am Main, completed under Prof. Wolf Singer at the Max Planck Institute for Brain Research. Her career includes professorships at the University of Jena (2005–2010), a guest professorship at Magdeburg, and a research associate professorship at the University of California, San Francisco. Siegrid Löwel's research focuses on the development and plasticity of neuronal circuits in the mammalian cortex. Her lab employs optical and 2-photon imaging, electrophysiology, and viral gene knockdown to study how experience and learning shape neural networks. Her work has pivotal implications for brain regeneration and rehabilitation after injury or disease. She was among the first to demonstrate that correlated neural activity underlies long-range cortical circuit development—famously summarized as 'neurons that fire together, wire together.' The recent publications reflect a strong focus on structural and functional cortical plasticity, particularly in the visual system. Themes include silent synapses, critical period regulation, optogenetic interventions for blindness, and the impact of environmental enrichment and exercise on neural plasticity. These studies span molecular, cellular, and systems levels, contributing to both basic neuroscience and translational applications. Scientific awards and recognitions include: Hertie Excellence Program Scholarship in Neurosciences (2004–2005) Dorothea Erxleben Guest Professorship, University of Magdeburg (2003–2004) Löwel leads an active research group and is affiliated with the Göttingen Graduate Center for Neurosciences (GGNB) in multiple programs, including Systems Neuroscience and Sensory and Motor Neuroscience. She has secured long-term research support through institutional roles and collaborative networks. While specific grant details are not listed, her sustained publication record and leadership positions indicate robust funding and research activity. Her lab continues to explore mechanisms of neural plasticity with potential clinical applications in stroke recovery, amblyopia, and neurodegenerative conditions. She is associated with the research group homepage: http://systemsneuroscience.uni-goettingen.de .

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.

• Cognitive Neuroscience
• Developmental Disorders
• Speech Perception
• +3 more

Professor Kate Watkins is a Professor of Cognitive Neuroscience and Tutorial Fellow at St Anne's College, University of Oxford. Her research focuses on the neural mechanisms underlying speech and language, particularly in developmental disorders such as stuttering and developmental language disorder (DLD). She employs neuroimaging (MRI/fMRI) and brain stimulation techniques (TMS/tDCS) to investigate speech perception, production, and motor control. Key contributions include discoveries about striatal iron concentrations in stuttering and cerebellar abnormalities in DLD. Watkins trained at the Institute of Child Health, Great Ormond Street Hospital, and the Montreal Neurological Institute. She co-founded the Neurobiology of Language journal and has held academic roles since 2003. Her work bridges clinical and experimental approaches, aiming to improve understanding of communication disorders and inform therapeutic strategies. Research interests span developmental stuttering, speech motor control, bilingual language processing, and neuroimaging methodologies. She collaborates with institutions like the Wellcome Centre for Integrative Neuroimaging and has published extensively on language lateralization, motor cortex plasticity, and neurobiological markers of speech disorders.

• Biomedical Engineering
• Neuroscience
• Neural Engineering
• +6 more

Hayriye Cagnan is a Senior Lecturer (Associate Professor) in the Department of Bioengineering at Imperial College London’s Faculty of Engineering. She specializes in neural engineering and movement disorders, focusing on deep brain stimulation (DBS) and tremor pathophysiology. Her research integrates computational modeling, signal processing, and clinical neuroscience to develop adaptive neurotherapies. Cagnan holds a Ph.D. in Neuroscience from the University of Amsterdam and Philips Research, and has held postdoctoral positions at the University of Oxford and University College London. Education: B.Sc. in Electrical and Electronics Engineering (Cornell University, 2000–2004) – Fulbright Scholar M.Sc. in Engineering and Physical Science in Medicine (Imperial College London, 2004–2005) – Chevening Scholar Ph.D. in Neuroscience (University of Amsterdam/Philips Research, 2010) Research Interests: Her work addresses neural mechanisms underlying Parkinson’s disease, essential tremor, and other movement disorders. Key areas include: Development of adaptive DBS systems for tremor management Neural circuit dynamics and oscillations in basal ganglia networks Non-invasive neurostimulation techniques (e.g., TMS, tRNS) Machine learning for optimizing neurotherapeutic interventions Publications: Recent work emphasizes closed-loop systems, phase-specific stimulation, and translational neuroscience. Her studies explore how DBS modulates movement speed, reward processing, and neural oscillatory patterns in Parkinsonian patients. Awards: MRC Career Development Award (2018) MRC Skills Development Fellowship (2015) British Chevening Scholarship (2004) Lab & Collaboration: Leads the Neuroengineering and Dynamic Systems Lab at Imperial, collaborating with clinicians and engineers to advance neuromodulation therapies. Active in initiatives like NEUROMOD+ for next-generation neurotherapies.