جست‌وجوی استاد و پژوهشگر

Indranath Chatterjeeمشاهده پروفایل

استادیار

• Computational Neuroscience
• Medical Imaging
• Schizophrenia
• +۷ مورد دیگر

Dr. Indranath Chatterjee is an Assistant Professor at Manchester Metropolitan University's Department of Computer and Mathematics, with adjunct roles at Woxsen University and the International Center for Neuroscience Research. He specializes in Computational Neuroscience, Schizophrenia, and Medical Imaging, focusing on fMRI analysis and machine learning applications. His research spans over 12 authored/edited books and numerous peer-reviewed publications, including works on neuroimaging, AI in healthcare, and blockchain solutions. He leads the Chatterjee's NeuroImaging and AI Lab at Tongmyong University, collaborating globally on projects like 'Uncovering Neuroscience History in South Korea' (FENS grant) and 'Green Neuromarketing'. Awards include the 2021 Best Young Neuroscientist Award and multiple paper accolades. Education: PhD in Computational Neuroscience from University of Delhi. Previous roles include Assistant Professorships at Tongmyong University (2019–2024) and JK Lakshmipat University. He serves as Chief Section Editor of international journals and holds leadership roles in organizations like ACM, FENS, and INCF. Active in conferences worldwide, delivering over 26 keynotes. Research interests include Schizophrenia neurobiology, AI-driven medical diagnostics, and neuromarketing strategies. Current projects address chronic pain in osteoarthritis, green neuromarketing via EEG, and historical neuroscience studies. His lab employs 8 researchers focusing on neuroimaging, machine learning, and interdisciplinary AI applications. Awards highlight his contributions to neuroscience and computational methods, including FENS-funded research and editorial recognition. Grants include government/non-profit collaborations for societal impact through medical imaging and machine learning.

• Neuroimaging in Psychiatry
• Psychiatric Disorders Pathophysiology
• Neurocognitive Profiles
• +۴ مورد دیگر

Marcella Bellani is an Associate Professor at the University of Verona's Department of Neuroscience, Biomedicine and Movement Sciences, Section of Psychiatry and Clinical Psychology. She chairs the Neuroimaging Section of the European Psychiatric Association and directs the Brain Imaging and Neuropsychology Research Unit. Her research focuses on applying neuroimaging techniques (MRI, fMRI) to study psychiatric disorders, with emphasis on biomarkers for early diagnosis and intervention. She investigates psychiatric disorders like bipolar disorder, schizophrenia, and depression using translational approaches combining neuroimaging, neuropsychology, and rehabilitation strategies. Her teaching roles include contributing to medical and psychiatric rehabilitation programs, covering topics like psychiatry fundamentals and cognitive therapy principles. She actively participates in postgraduate psychiatry specialization courses, overseeing clinical case discussions and literature updates. Bellani's work integrates computational neuroscience methods to analyze brain structure/function relationships, with recent projects exploring machine learning applications in mental health diagnostics. Her research unit collaborates internationally through initiatives like the ECNP neuroimaging network, emphasizing data harmonization for large-scale studies. Key areas include the impact of inflammation on brain microstructure in psychosis, cognitive remediation therapies, and digital interventions for social isolation. She advocates for ethical considerations in psychiatric care, such as opposing assisted suicide for severe depression cases.

Joanne Jao Keehnمشاهده پروفایل

استاد پژوهشی

• Autism
• Sensory Processing
• Multisensory Integration
• +۳ مورد دیگر

Dr. Joanne Jao Keehn is a Research Professor of Psychology at San Diego State University (SDSU), affiliated with the College of Sciences and the Department of Psychology. She is part of the SDSU/UC San Diego Joint Doctoral Program in Clinical Psychology. Her research focuses on neural and behavioral mechanisms of sensory processing, multisensory integration, and sensorimotor development in children with and without autism, utilizing advanced neuroimaging techniques like fMRI and MEG. Her work explores links between sensory abnormalities, stress responsivity, and autism symptomatology. Dr. Keehn’s expertise spans autism, sensory processing, functional neuroimaging, and developmental neuroscience. She leads the BDIL Lab, conducting studies on sensory and multisensory integration in clinical populations. Her research emphasizes understanding atypical neural connectivity and its implications for behavioral symptoms in autism. She has contributed to collaborative efforts like the Autism Brain Imaging Data Exchange (ABIDE) to enhance connectome studies in autism. Her academic contributions include over 25 peer-reviewed publications since 2009, with recent work focusing on functional connectivity patterns, sensory network interactions, and neuroimaging methodological advancements. Though specific awards are listed under placeholders, her work is recognized for advancing understanding of autism’s neurobiological underpinnings. She collaborates across institutions and mentors students in clinical and developmental psychology.

Jens H. Jensenمشاهده پروفایل

استاد

• Magnetic Resonance Imaging (MRI)
• Neurological Disorders
• Neuroimaging Techniques
• +۳ مورد دیگر

Dr. Jens H. Jensen is a Professor of Neuroscience at the Medical University of South Carolina (MUSC) and Director of the Center for Biomedical Imaging. He holds a PhD in Physics from Princeton University and previously worked at New York University School of Medicine before joining MUSC in 2011. His research focuses on advanced MRI techniques applied to neurological disorders, including Alzheimer’s disease, epilepsy, stroke, and addiction. His work emphasizes diffusion MRI, brain microstructure analysis, and translational neuroimaging. Education: PhD in Physics, Princeton University Prior affiliation: New York University School of Medicine Research Interests: Dr. Jensen’s lab develops and applies diffusion MRI methods to study brain microstructure in health and disease. Key areas include: Diffusional kurtosis imaging White matter integrity assessment Neuroimaging biomarkers for Alzheimer’s disease Therapeutic monitoring using MRI (e.g., transcranial stimulation) His recent work explores longitudinal changes in mouse models of neurodegeneration and clinical applications in stroke and addiction. Advising & Grants: While specific grant details are not listed here, his prolific publication record suggests sustained federal and institutional funding. He mentors students in physics, engineering, and neuroscience. Labs/Teams: Leads the Center for Biomedical Imaging at MUSC, focusing on cutting-edge neuroimaging technologies and clinical translation.

Sarah W. Bookمشاهده پروفایل

استاد

• Alcohol and Drug Addiction
• Mood and Anxiety Disorders
• Biomarkers in Substance Use Disorders
• +۳ مورد دیگر

Sarah W. Book is a Professor at the Medical University of South Carolina 's College of Medicine , Department of Psychiatry and Behavioral Sciences . She serves as Medical Director of the Center for Drug and Alcohol Programs and Director of the Clinical Neurobiology Laboratory , focusing on substance use biomarkers and treatment efficacy. Alcohol and Drug Addiction Mood and Anxiety Disorders Pharmacogenetics Clinical Neurobiology Medical Education Addiction Research Training Dr. Book's research integrates clinical trials with biomarker analysis , evaluating medications like Mazdutide and TMP-301 for Alcohol Use Disorder. Her work bridges psychopharmacology with educational program development , aiming to enhance clinician-scientist training. Recent publications highlight her team's exploration of COMT regulation , sleep variability , and genetic predictors in addiction treatment. Her clinical trials portfolio reveals trends in: Neuropharmacological interventions (e.g., tolcapone, gabapentin) Biological markers for substance use detection Integrated treatment models for dual diagnosis 12-step program effectiveness Medical student research engagement Postoperative pain management in addiction patients Dr. Book mentors medical students, psychiatry residents , and addiction fellows , while leading interdisciplinary teams in Charleston, SC.

Alexander A Stevensمشاهده پروفایل

استادیار

• Neuroimaging
• Sensory Adaptation
• Cognitive Neuroscience
• +۷ مورد دیگر

Alexander A. Stevens is a Research Assistant Professor at the Advanced Imaging Research Center and holds Assistant Professor roles in Psychiatry and Behavioral Neuroscience at Oregon Health & Science University’s School of Medicine. His research focuses on neuroimaging techniques (e.g., fMRI, EEG) to study brain adaptations in sensory and motor systems. Key interests include auditory perception in blindness, sleep-state metabolic effects, and ADHD-related neural mechanisms. Education : Ph.D. in 1995 from the University of New Hampshire, followed by postdoctoral training at Yale University in diagnostic radiology and child psychiatry. Research Interests : Stevens explores cross-modal plasticity in sensory deprivation (e.g., blindness), functional connectivity in ADHD, and neuroimaging applications like simultaneous EEG-fMRI. His work bridges clinical neuroscience and developmental studies, emphasizing translational research. Articles : Recent studies address cross-species visual cortex changes in blindness and brain metabolic responses to sleep states. Earlier work includes auditory cortex plasticity in the blind and ADHD-related neural network modulation. Awards/Grants : No awards explicitly listed, but extensive NIH/NIMH-funded postdoctoral training indicates grant activity. Labs/Teams : Affiliated with the Advanced Imaging Research Center, collaborating on neuroimaging methodologies and clinical applications.

Laurent Cleret de Langavantمشاهده پروفایل

استادیار

• Cognitive Neuroscience
• Neurology
• Clinical Neurology
• +۳ مورد دیگر

Laurent Cleret de Langavant is an Assistant Professor in Neurology at Paris Est University and a senior Atlantic Fellow for Equity in Brain Health at the Global Brain Health Institute (GBHI). He holds a faculty position at the NeuroPsychologie Interventionnelle laboratory, affiliated with the Ecole Normale Supérieure (Paris) and Henri Mondor Hospital (Créteil). His research focuses on improving care for patients with cognitive disorders, particularly social disturbances and dementia, using experimental psychology, neuroimaging, and machine learning. He leads studies on Huntington’s disease progression, dementia prediction through population data analysis, and the impact of Annonaceae consumption on neurodegenerative conditions. Clinical roles include neurology at AP-HP (Assistance Publique – Hôpitaux de Paris). Education details are not explicitly stated, but his academic trajectory is reflected in his roles and publications. Research interests emphasize translational neurology, machine learning applications in healthcare, and clinical trial methodologies. His articles highlight work on dementia epidemiology using unsupervised clustering, Huntington’s disease biomarkers, and the role of striatal dysfunction in timing deficits. Recent studies explore modifiable risk factors and care burden in neurodegenerative diseases. His lab collaborations span neuroimaging, behavioral studies, and interdisciplinary clinical trials.

• Biomedical Informatics
• Medical Imaging
• Medical Data Fusion
• +۳ مورد دیگر

Prof. Georgios Matsopoulos is a Professor at the Department of Information Transmission Systems and Materials Technology, School of Electrical and Computer Engineering, National Technical University of Athens (NTUA). He holds a Master's in Biomechanics and a PhD from the University of Strathclyde, Glasgow. As Director of the Biomedical Technology Laboratory, his expertise spans biomedical informatics, medical imaging, and healthcare data systems. His research focuses on diagnostic support systems, medical data fusion, biosignal processing, and AI-driven health technologies. Education: Bachelor's: School of Electrical & Computer Engineering, NTUA Master's: Biomechanics, University of Strathclyde PhD: University of Strathclyde Research Interests: Development of decision support systems, medical imaging analysis, health information systems, and AI applications in healthcare. He emphasizes large-scale medical data processing, radiomics, and clinical decision frameworks. His over 300 publications (2025-2021) highlight advancements in AI-driven diagnostics, medical robotics (e.g., HERON ontology), and telehealth systems. He leads projects like TeleRehaB DSS for stroke rehabilitation and the Retention project for heart failure monitoring. Grants/Projects: Extensive experience in managing research programs across public and private sectors, including EU-funded initiatives in medical AI and robotics. Labs & Teams: Oversees the Biomedical Technology Laboratory, focusing on translational research in biomedical engineering and digital health.

Johanna Zumerمشاهده پروفایل

مدرس

• Visual attention
• Neuroimaging (MEG/EEG)
• Neural oscillatory mechanisms
• +۳ مورد دیگر

Johanna Zumer is a Lecturer in Psychology at Aston University's School of Psychology within the College of Health and Life Sciences. Her research focuses on understanding how the brain processes attention-demanding tasks using neuroimaging techniques like MEG, EEG, and fMRI. She investigates neural mechanisms underlying attention and perception disorders such as ADHD and autism, and explores multisensory integration. Dr. Zumer holds a PhD in Bioengineering from UC San Francisco/UC Berkeley and a BS in Applied Physics and Psychology from Yale University. **Educations:** PhD in Bioengineering (UCSF/UC Berkeley, 2007) BS in Applied Physics & Psychology (Yale University, 2001) PGCert in Higher Education (2022) **Research Interests:** She studies visual attention, neural oscillatory mechanisms, and open-source neuroimaging software (e.g., NUTMEG). Her work bridges basic neuroscience with clinical applications, particularly in developmental disorders. Recent projects explore human engagement technologies and neurophysiological correlates of reward-related attention. **Awards:** Academy of Medical Sciences Springboard Grant (2022-24) Marie Curie Intra-European Fellowship (2015-18) Whitaker Scholar Award (2007-09) **Teaching & Supervision:** She teaches cognitive neuroscience courses at Aston and supervises PhD students (e.g., Ashley Goneso, Cliona Kelly). She has co-supervised multiple MSc projects at Radboud University and the University of Nottingham. **Labs & Teams:** Affiliated with the Cognition & Neuroscience Research Group (CNRG) and the Aston Institute of Health & Neurodevelopment. Active contributor to open-source neuroimaging software (NUTMEG).

• Transcranial Magnetic Stimulation
• Neuroscience
• Epilepsy Treatment
• +۱ مورد دیگر

Dr. Salla Autti is a Researcher at Aalto University's Department of Neuroscience and Biomedical Engineering within the School of Science. Her research focuses on advanced neuroimaging techniques and neuromodulation therapies. Research interests include: Non-invasive brain mapping using MEG and TMS integration Artifact removal algorithms for neuroimaging data Network-level brain engagement pre-stimulation Clinical applications for epilepsy and speech disorders Her publications demonstrate consistent focus on improving diagnostic precision in neurology through multimodal approaches combining TMS, fMRI, and MEG technologies. Recent work shows growing emphasis on real-time artifact correction and network-level neural analysis.

Kathryn C Dickersonمشاهده پروفایل

دانشیار

• Real-time fMRI neurofeedback
• Dopamine system
• Reward processing
• +۶ مورد دیگر

Kathryn C Dickerson is an Associate Professor in Psychiatry and Behavioral Sciences at Duke University, with secondary appointments as a Member of the Center for Cognitive Neuroscience and Duke Institute for Brain Sciences since 2018. Her interdisciplinary work bridges neuroscience, psychiatry, and behavioral medicine through innovative real-time fMRI neurofeedback approaches. Education: B.A. in Brain and Cognitive Sciences, University of Rochester (2006) Ph.D. in Behavioral and Neural Sciences, Rutgers University (2011) Dr. Dickerson's research pioneers three interconnected domains: (1) Cognitive neurostimulation for volitional activation of the dopaminergic midbrain using internally generated thoughts; (2) Integration of real-time fMRI neurofeedback with cognitive behavioral therapy to enhance treatment efficacy through immediate neural feedback; and (3) Characterization of reward-motivation interactions in learning and memory systems. Her work demonstrates how internally generated motivation can modulate brain function without external rewards, with clinical applications for ADHD, addiction, and depression. Her publication trajectory reveals consistent methodological innovation in real-time fMRI, expanding from basic dopamine system research to clinical translation and workforce diversity initiatives. Recent work emphasizes machine learning applications for neurofeedback prediction, open-source software development (Pyneal), and addressing health disparities through clinical research workforce diversification. Scientific Awards: KL2 Research Scholar Award (NIH, 2013-2018) NIH Fellowship for Dopaminergic Midbrain Activation Research (2014-2016) Dr. Dickerson actively mentors undergraduate researchers and serves as Research Administrative Director for the Duke PRIME Cancer Research Program (NCI-funded, 2023-2028), which advances diversity in biomedical research. Her grant portfolio includes the Brain and Behavior Research Foundation project on nicotine dependence (2016-2022) and Duke CTSA KL2 award. She co-directs institutional initiatives including SPEAK (Scientists Promoting Equity And Knowledge) mentoring for underrepresented scholars and the Inclusion and Power Dynamics workshop series, while leading community neuroscience outreach for K-12 students through Brain Awareness Week and MRI facility tours.

Emmanuel Emmanuelمشاهده پروفایل

مدرس

• Artificial Intelligence in Healthcare
• Machine Learning
• Medical Imaging Analysis
• +۳ مورد دیگر

Dr. Emmanuel Emmanuel is a Lecturer in the School of Engineering, Computing and Mathematics at the University of Plymouth, part of the Faculty of Science and Engineering. His research focuses on the intersection of artificial intelligence, medical imaging, and network engineering. He holds a PhD and has contributed significantly to advancing AI-driven solutions for neurodegenerative diseases (e.g., Alzheimer’s, Parkinson’s), autism diagnosis, and stroke risk prediction. His work also extends to optimizing multimedia service quality in 5G and SDN/NFV networks. Key research interests include machine learning applications in healthcare diagnostics, explainable AI for medical decision-making, and quality-of-experience (QoE) optimization in telecommunications. He has authored over 50 peer-reviewed articles, with recent studies emphasizing AI-based diagnosis tools, biomarker development, and adaptive network management systems. Dr. Emmanuel’s technical contributions span MRI analysis, EEG signal processing, and data-efficient deep learning models. His projects often bridge clinical needs with technical innovation, such as developing XAI frameworks for MRI interpretation and optimizing video streaming quality in heterogeneous networks. He is actively involved in interdisciplinary collaborations, including the LiveWell initiative promoting ICT-based interventions for Parkinson’s patients. Contact: Room 208D Smeaton Building, emmanuel.jammeh@plymouth.ac.uk.

Marianne van der Vaartمشاهده پروفایل

پژوهشگر

• Development and validation of EEG biomarkers
• Neurodevelopmental conditions
• Multimodal approaches in sensory processing
• +۳ مورد دیگر

Marianne van der Vaart is a Postdoctoral Research Associate at King’s College London’s Department of Forensic and Neurodevelopmental Sciences, part of the Institute of Psychiatry, Psychology & Neuroscience (IoPPN). Her work focuses on validating EEG biomarkers for clinical trials and neurodevelopmental conditions, aiming to enhance tailored support for individuals seeking interventions. She holds advanced degrees including a PhD from the University of Oxford (2022) and MSc/BSc degrees from Leiden University, Netherlands. Her research interests span EEG/fMRI analysis in infants, multimodal approaches to sensory processing, and translational neuroscience. She emphasizes reproducible methodologies and inclusive research practices. Key contributions include advancing pain assessment tools for neonates and developing the PiNe Box, an electronic device for synchronized multimodal data collection in hospitalized infants. Her recent work explores parental touch’s role in neonatal pain relief (Petal trial), caffeine’s effects in preterm neonates, and systematic reviews of EEG reliability in analgesic efficacy. She advocates for standardised protocols to bridge neuroscientific discoveries with clinical applications. Marianne’s career trajectory includes postdoctoral research in the University of Oxford’s Paediatric Neuroimaging Group, where she investigated neonatal pain management in preterm and term infants. Her interdisciplinary approach integrates medicine, biomedical sciences, and computational methods to address unmet clinical needs in neonatal care.

Ke Pengمشاهده پروفایل

استادیار

• Neuroimaging
• Functional Near Infrared Spectroscopy (fNIRS)
• Electroencephalography (EEG)
• +۷ مورد دیگر

Dr. Ke Peng is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Manitoba's Price Faculty of Engineering. His research focuses on multimodal brain imaging techniques (fNIRS, EEG, fMRI), virtual reality integration, and machine learning applications in neurological disorders. He holds a PhD in Biomedical Engineering from Polytechnique Montreal (2016) and completed postdoctoral fellowships at Harvard Medical School and Boston Children's Hospital before joining the University of Manitoba in 2023. Education: PhD in Biomedical Engineering, Polytechnique Montreal, 2016 MSc in Computer Engineering, Polytechnique Montreal, 2012 BEng in Automation, Tsinghua University, 2008 Research Interests: Dr. Peng develops medical devices and analytical methods for studying brain function in health and disease. His work includes: Integration of fNIRS, EEG, and VR systems to explore brain-environment interactions Machine learning models for medical imaging analysis Neurological disorder studies (epilepsy, chronic pain, stroke) Research Trends in Publications: His articles emphasize multimodal imaging fusion (e.g., EEG-fNIRS), seizure prediction algorithms, and opioid pain modulation mechanisms. Over 60% of his work addresses clinical pain management and epilepsy diagnostics through advanced neuroimaging techniques. Awards & Grants: 2018 Anesthesia Distinguished Trailblazer Award (Boston Children's Hospital) Funding from NIH (US) and CIHR (Canada) Collaborations: Active partnerships with Harvard Medical School, Massachusetts General Hospital, University of Montreal, and Boston University. Current projects include VR-based brain imaging systems and AI-driven medical imaging tools.

• Neuroscience
• Neurodegenerative Disorders
• Metabolism
• +۴ مورد دیگر

Prof. Marc Tittgemeyer leads the Department of Translational Neurocircuitry at the Max Planck Institute for Metabolism Research in Cologne, Germany. His work bridges neuroendocrinology, neurodegenerative diseases, and neuroimaging, focusing on dopamine pathways, obesity mechanisms, and Parkinson’s disease progression. His research employs multimodal approaches including PET imaging, neuropharmacology, and computational modeling. Research Interests: His key areas include: Neurocircuitry of reward and motivation Dopamine-driven motor and cognitive deficits in Parkinson’s Neuroendocrine regulation of appetite and metabolism Genetic and metabolic drivers of impulse control disorders Deep brain stimulation mechanisms Key Findings: Recent work highlights dopamine’s role in movement motivation, thalamic opioid effects on sugar craving, and liraglutide’s cognitive benefits in obesity. His articles emphasize network connectivity disruptions in neurodegenerative diseases and metabolic-neural interactions. Collaborations: Engages in translational research combining clinical imaging (PET/fMRI), genetic analysis, and behavioral studies to advance disease biomarkers. Active in developing AI-driven diagnostic tools for Parkinson’s using machine learning on radiomic data.