Find Academic Supervisors

• Biomedical Informatics
• Medical Imaging
• Medical Data Fusion
• +3 more

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 ZumerView profile

Lecturer

• Visual attention
• Neuroimaging (MEG/EEG)
• Neural oscillatory mechanisms
• +3 more

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
• +1 more

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 DickersonView profile

Associate Professor

• Real-time fMRI neurofeedback
• Dopamine system
• Reward processing
• +6 more

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 EmmanuelView profile

Lecturer

• Artificial Intelligence in Healthcare
• Machine Learning
• Medical Imaging Analysis
• +3 more

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 VaartView profile

Researcher

• Development and validation of EEG biomarkers
• Neurodevelopmental conditions
• Multimodal approaches in sensory processing
• +3 more

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 PengView profile

Assistant Professor

• Neuroimaging
• Functional Near Infrared Spectroscopy (fNIRS)
• Electroencephalography (EEG)
• +7 more

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
• +4 more

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.

• Neuroscience
• Data Science
• Neuroimaging
• +3 more

Toshikazu Ikuta is an Associate Professor in the Department of Communication Sciences and Disorders at the University of Mississippi's School of Applied Sciences. His research focuses on neuroimaging, computational modeling of neurological disorders, and big data analysis in neuroscience. He holds a Ph.D. in Neuroscience and Linguistics from Indiana University (2008) and previously worked at the Zucker Hillside Hospital and Feinstein Institute for Medical Research as a Post-Doc and Research Scientist. Key research areas include functional MRI analysis of Alzheimer's, Schizophrenia, Autism, and Anxiety disorders, alongside electrophysiology and machine learning applications. His work spans structural and functional brain connectivity, white matter microstructure, and neuroimaging biomarkers for mental health conditions. Ikuta's publications emphasize systematic reviews and meta-analyses of neurological treatments (e.g., antipsychotics, neurostimulation protocols) and explore links between brain anatomy, cognition, and behavior. He investigates age-related neural changes, the impact of physical activity on brain connectivity, and the role of genetic factors like APOE ε4 in neurodegeneration. His academic contributions include contributions to the ENIGMA consortium for OCD studies and the development of classification algorithms using neuroimaging data. Current projects involve advancing computational models for psychiatric diagnostics and understanding neural circuits in appetite regulation and social communication deficits.

• Substance Abuse Treatment
• Help-Seeking Behavior
• Cognitive-Behavioral Therapy Outcomes
• +3 more

Benjamin D'Angelo, PhD is an Assistant Professor affiliated with the Department of Psychiatry and Behavioral Medicine at the Medical College of Wisconsin. He also serves as a Psychologist at the Clement J. Zablocki VA Medical Center and the Cleveland (WI) VA Outpatient Clinic. His work bridges academic research and clinical practice in mental health. Affiliations: Medical College of Wisconsin, VA Medical Centers Dr. D'Angelo holds a doctorate from Marquette University and completed undergraduate studies at Miami University (OH). His research focuses on substance abuse treatment efficacy, factors influencing cognitive-behavioral therapy outcomes, and patient help-seeking behaviors. His work also extends into neuroimaging studies of consciousness, as seen in fMRI investigations. His publications (2005-2006) explore barriers to alcohol treatment and neural mechanisms of consciousness. No scientific awards are explicitly listed in the provided text. Advising and grants sections remain unspecified in the data. No lab affiliations or teams are mentioned.

Richard LopezView profile

Assistant Professor

• Social neuroscience
• Emotion regulation
• Digital media use
• +4 more

Richard Lopez is an Assistant Professor of Neuroscience and Psychology in the Department of Social Science and Policy Studies at Worcester Polytechnic Institute (WPI). He also holds affiliate status with the Psychological Science and Neuroscience programs and directs the Social Neuroscience of Affective Processes (SNAP) Lab. Education B.A. in Psychology, Princeton University, 2009 Ph.D. in Cognitive Neuroscience, Dartmouth College, 2017 Postdoctoral Fellowship in Translational Social Cognitive and Affective Neuroscience, Rice University, 2019 Research Interests Lopez’s work lies at the intersection of social neuroscience, emotion regulation, and health. Using multimodal neuroimaging (EEG, fNIRS, fMRI), longitudinal behavioral modeling, and digital phenotyping, his lab investigates how individuals align emotions and behaviors with personal values and long-term goals. Specific foci include: Digital-media effects on adolescent mental health Scalable emotion-regulation interventions for borderline personality disorder and stress-related conditions Self-continuity and its influence on health behaviors such as eating and smoking Translational health neuroscience that bridges basic affective science and real-world intervention design Recent Scholarly Trends Across his fifteen most recent publications (2020-2025), a clear trajectory emerges: early mechanistic neuroimaging studies on food-cue reactivity and emotion-regulation circuitry have evolved into applied, ecologically-valid investigations that use mobile sensing and longitudinal modeling to test scalable mental-health and behavior-change interventions in daily life. The work increasingly integrates computational linguistics, digital phenotyping, and large-scale consensus efforts to inform public-health guidelines on screen time and social-media use. Awards & Honors CAPES Emerging Scholar, 2025 WPI President’s Research Catalyst Grant, 2024 Funding & Mentorship Lopez currently leads an interdisciplinary team of graduate and undergraduate researchers in the SNAP Lab. His President’s Research Catalyst Grant funds collaborative projects that translate neuroscience findings into digital interventions aimed at improving wellbeing. While specific student names are not listed, he is actively involved in mentoring across WPI’s Psychological Science and Neuroscience programs. Laboratory & Affiliations He directs the Social Neuroscience of Affective Processes (SNAP) Lab located in Salisbury Labs 317C. The lab is equipped with state-of-the-art EEG, fNIRS, and access to fMRI facilities, and it serves as a hub for cross-disciplinary projects spanning psychology, neuroscience, data science, and digital health.

Emiliano RicciardiView profile

Professor

• Cognitive Neuroscience
• Psychophysiology
• Neuroimaging
• +7 more

Emiliano Ricciardi is a Full Professor of Psychobiology and Psychophysiology at the IMT School for Advanced Studies Lucca. He holds leadership roles as Director of the PhD Program in 'Cognitive, Computational and Social Neurosciences' and Vice-Rector for Didactics. His expertise spans cognitive neuroscience, neuropsychology, and neuroimaging, with a focus on sensory deprivation and neural plasticity. Ricciardi completed his MD at the University of Pisa and a PhD in Neurosciences at Scuola Superiore Sant'Anna. He spent two years at NIH labs, acquiring expertise in PET and fMRI techniques. Research interests include cross-modal plasticity in sensory-deprived individuals, neural correlates of perception, and advanced neuroimaging analysis. His MoMiLab group integrates cognitive neuroscience with structural/functional imaging. Ricciardi has published over 120 peer-reviewed articles and serves on editorial boards for journals like Scientific Reports and Frontiers in Neurology . Awards include Young Investigator and Travel Fellowships, alongside invited lectures globally. His work bridges neuroscience with technology and cognitive science, emphasizing practical applications for sensory and cognitive enhancement. Education: MD (University of Pisa), PhD (Scuola Superiore Sant'Anna) Leadership: PhD Program Director, Vice-Rector Key Research Areas: Sensory Deprivation, Neuroplasticity, Multimodal Perception, Brain Imaging His research explores how sensory deprivation reshapes brain function, leveraging neuroimaging tools like fMRI and M/EEG. Ricciardi’s contributions include studies on sleep neurobiology, emotion regulation failures linked to frontal brain activity, and the impact of self-control on neural systems. He has pioneered interdisciplinary projects, including the 'Train the Brain' cognitive intervention trial for mild cognitive impairment.

James V. HaxbyView profile

Professor

• Computational Cognitive Neuroscience
• Neural Decoding
• fMRI Analysis
• +3 more

James V. Haxby is a Professor in the Department of Psychological and Brain Sciences at Dartmouth College, where he leads the Haxby Lab, part of the Center for Cognitive Neuroscience. His research focuses on computational cognitive neuroscience, neural decoding, and the development of hyperalignment techniques to model shared neural information across individuals. He holds a B.A. from Carleton College and a Ph.D. from the University of Minnesota. Education: B.A., Carleton College Ph.D., University of Minnesota Research Interests: James’s work emphasizes hyperalignment, functional topography analysis, and fMRI studies of visual and social cognition. His lab develops open-source tools like PyMVPA and the HyperBrain project to standardize neuroimaging data. Key projects include modeling individualized neural architectures and exploring how attention influences semantic representation. Lab & Collaborations: His lab collaborates internationally (e.g., the 'Monkey Kingdom' project) and has produced influential studies on face perception, object recognition, and neural representation spaces. Current and past students include Vassiki Chauhan, Matteo Visconti, and Samuel Nastase. The lab actively seeks researchers for projects like HyperBase, aiming to build normative neuroimaging datasets. Grants & Resources: Recent funding supports the HyperBase initiative. The lab emphasizes open science, sharing software and data via their website and GitHub repositories.

Felix HoffstaedterView profile

Researcher

• Neuroscience
• Brain Imaging
• Computational Biomedicine
• +1 more

Dr. Felix Hoffstaedter is a researcher at the Institute of Neuroscience and Medicine (INM-7) at Research Center Jülich, focusing on brain-behavior relationships. His work integrates neuroimaging and computational methods to study brain morphology and functional networks. Research interests include: Advanced MRI techniques for brain mapping Machine learning applications in neuroscience Systems medicine approaches to neurological disorders Recent publications demonstrate a strong focus on hippocampal morphology and self-regulatory neural networks, utilizing cutting-edge analytical frameworks. No awards or student advisement details are currently available. Dr. Hoffstaedter collaborates with the Ernst Ruska Center for electron microscopy and maintains active research partnerships across European institutions.

Nicola Palomero-GallagherView profile

Adjunct Professor

• Neuroimaging
• Receptor Autoradiography
• Cytoarchitecture
• +5 more

apl.-Prof. Dr. Nicola Palomero-Gallagher is a Working Group Leader of the 'Receptors' research group at the Institute of Neuroscience and Medicine (INM-1), Research Center Jülich. Affiliated with Heinrich Heine University Düsseldorf, she leads the National Node Germany of EBRAINS, a pan-European research infrastructure for brain research. Her work focuses on integrating neuroanatomical, molecular, and functional data to map brain organization across species. Research interests include connectomics, neuroimaging techniques (e.g., 3D-PLI), receptor autoradiography, and the structural-functional relationships of brain regions. Key projects involve creating multi-modal brain atlases (e.g., MEBRAINS for macaques) and investigating neurotransmitter receptor distributions in human and non-human primate brains. Her contributions bridge neuroanatomy, computational neuroscience, and translational research. Publications emphasize cortical architecture, receptor-driven area mapping, and applications of AI in neuroimaging. She collaborates internationally to advance digital neuroscience tools and cross-species comparisons, with a focus on Alzheimer’s disease mechanisms and brain network dynamics.