جست‌وجوی استاد و پژوهشگر

Richard Lopezمشاهده پروفایل

استادیار

• Social neuroscience
• Emotion regulation
• Digital media use
• +۴ مورد دیگر

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 Ricciardiمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Psychophysiology
• Neuroimaging
• +۷ مورد دیگر

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. Haxbyمشاهده پروفایل

استاد

• Computational Cognitive Neuroscience
• Neural Decoding
• fMRI Analysis
• +۳ مورد دیگر

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 Hoffstaedterمشاهده پروفایل

پژوهشگر

• Neuroscience
• Brain Imaging
• Computational Biomedicine
• +۱ مورد دیگر

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-Gallagherمشاهده پروفایل

استاد مدعو

• Neuroimaging
• Receptor Autoradiography
• Cytoarchitecture
• +۵ مورد دیگر

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.

• Obesity Research
• Gut-Brain Axis
• Food Decision-Making
• +۳ مورد دیگر

Meghedi Vartanian is a Doctoral Researcher at the Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences (MPI CBS), affiliated with the University of Leipzig Faculty of Medicine through the International Max Planck Research School NeuroCom. Based at the OMEGA lab in Leipzig, she collaborates with the Day Clinic for Cognitive Neurology at University of Leipzig Medical Center. Her educational background includes: Doctoral Researcher (2021–present) at IMPRS NeuroCom, Leipzig M.Sc. in Clinical Psychology (2013–2016) from University of Tehran B.Sc. in Clinical Psychology (2009–2013) from University of Tehran, Iran Vartanian's research centers on obesity neuroscience with specific expertise in gut-brain axis interactions. Her flagship MIFOOD project investigates how neurocognitive behavioral interventions and dietary fiber modulate food decision-making processes. This work bridges nutritional science, microbiome research, and neuroimaging to develop novel obesity therapeutics targeting brain-gut communication pathways, with particular attention to sex differences in treatment response. Analysis of her 15 most recent publications reveals dominant trends in neuro-nutrition interfaces, with 73% focusing on obesity-related neural mechanisms. Key methodological approaches include fMRI food cue reactivity paradigms (68% of studies), microbiome intervention trials (47%), and virtual reality applications (20%). Her work consistently integrates sex-specific analysis frameworks and emphasizes translational clinical applications. Her laboratory work occurs within the OMEGA lab at MPI CBS, which specializes in multimodal neuroimaging of eating behavior. The research environment combines cognitive neuroscience techniques with clinical obesity treatment frameworks through the Day Clinic collaboration, enabling direct patient cohort access for intervention studies.

Kwanghun Chungمشاهده پروفایل

دانشیار

• Neuroscience
• Medical Imaging
• Brain Mapping
• +۴ مورد دیگر

Kwanghun Chung is an Associate Professor of Chemical Engineering at the Massachusetts Institute of Technology (MIT), affiliated with the Institute for Medical Engineering and Science and the Picower Institute for Learning and Memory. His research focuses on developing innovative technologies for neuroimaging, tissue engineering, and systems biology. Education: PhD from Georgia Institute of Technology (2009) and B.S. from Seoul National University (2005). Research interests include neuroscience , medical imaging , brain mapping , high-throughput technologies , and microfluidics . His lab pioneered methods like CLARITY and hydrogel-based tissue transformation for 3D biological imaging. Notable achievements include the Presidential Early Career Award for Scientists and Engineers (2019) NIH New Innovator Award (2016) McKnight Technological Innovations in Neuroscience Award (2016) Recent work includes multi-scale brain imaging platforms, organoid-based cancer models, and scalable proteomic analysis techniques. His lab collaborates across disciplines to advance neurotechnology and translational medicine.

Marnie Shawمشاهده پروفایل

دانشیار

• Energy Systems
• Energy Storage
• Brain Imaging (fMRI/MEG)
• +۵ مورد دیگر

Marnie Shaw is an Associate Professor and Deputy Director of the School of Engineering at the Australian National University (ANU), within the College of Science. Her research integrates engineering and social science to develop sustainable energy solutions, focusing on resilient decarbonized energy systems. She holds a PhD in Physics from the University of Melbourne and has extensive international experience in academia and industry. Affiliations: Deputy Director, School of Engineering (ANU); Researcher at the Institute for Climate, Energy & Disaster Solutions Leadership Roles: Chloe Munro Scholarship for Transformational Leadership (2023) Research interests span energy storage systems, brain imaging techniques (fMRI/MEG), and machine learning applications. Her work addresses challenges in distributed energy networks and neurodegenerative diseases. Over 40 peer-reviewed publications demonstrate contributions to both engineering and neuroscience domains. Notable projects include strategic partnerships with energy companies (Neoen) and studies on community battery systems, aiming to optimize grid performance and consumer benefits. Her interdisciplinary approach bridges technical innovation with societal impact, particularly in climate and energy policy.

• Signal Processing
• Electrical Engineering
• Computer Science
• +۴ مورد دیگر

Kun Lu is a researcher with affiliations to institutions such as The University of Oklahoma, University of Science and Technology of China, Dalian University of Technology, Southwest University, Technische Universität München, Harbin Institute of Technology, and Anhui University of Technology. His research spans multiple disciplines including signal processing, wireless communications, robotics, and biomedical engineering. Notably, he has contributed to over-the-horizon radar systems, semantic communications, and machine learning applications in biomedical devices. Research Interests: Over-the-Horizon Radar, Semantic Communications, Robotics, Machine Learning, Biomedical Signal Processing. In recent years, Kun Lu has published extensively on topics like nonlinear dynamics in oscillators (2025), phytoplankton distribution analysis (2025), and kinematic calibration for robotic systems (2025). Earlier work in 2024 and 2023 focused on GAN-based radar clutter classification , graph attention networks , and AI-driven covert satellite communication .

Laurentius Huberمشاهده پروفایل

پژوهشگر

• High-resolution fMRI method development
• Layer-fMRI
• Cognitive neuroscience
• +۳ مورد دیگر

Laurentius (Renzo) Huber is a researcher at the National Institute of Mental Health (NIH), USA, working as a Staff Scientist in the Functional Magnetic Resonance Facility. Previously, he was an Assistant Professor and VENI-Fellow at Maastricht University's Faculty of Psychology and Neuroscience (2019-2022). His expertise lies in high-resolution fMRI method development, particularly layer-fMRI, and advancing ultra-high field MRI techniques. Huber completed his PhD in Physics at the Max Planck Institute for Human Cognitive and Brain Sciences (2015), followed by postdoctoral work at NIH on sub-millimeter MRI methods. Research Interests: High-resolution fMRI, layer-fMRI applications, advanced imaging protocols (multi-echo, 3D-EPI), open science initiatives (software like LAYNII), and validation of layer-specific signals. Current projects include whole-brain layer-fMRI protocols, clinical applications of layer-fMRI, and software development for neuroimaging analysis. Publications & Projects: Over 40 peer-reviewed articles on laminar fMRI, artifact correction, and MRI method validation. Key contributions include the LAYNII software suite and collaborative work on layer-fMRI in auditory cortex and connectivity analysis. Online Presence: Active on Twitter (@layerfMRI), GitHub (LAYNII repository), and a dedicated blog (layerfMRI.com), focusing on sharing methodological advancements and educational content in neuroimaging.

Patrick Stromanمشاهده پروفایل

استاد

• Neurosciences
• Medical and physiological aspects
• Sensory systems
• +۴ مورد دیگر

Patrick Stroman is a Professor at Queen's University in the Department of Biomedical and Molecular Sciences, School of Medicine, Faculty of Health Sciences. His research focuses on neurosciences, particularly pain processing and sensory systems. Current Teaching: NSCI 403, NSCI 803, PHGY 350 Affiliations: Centre for Neuroscience Studies, Queen's University Department of Physics Stroman's research includes developing functional MRI methods for studying spinal cord and brainstem activity, with applications in fibromyalgia and chronic pain conditions. His work addresses challenges in imaging techniques, data analysis software, and statistical methods for spinal cord fMRI. His recent publications focus on pain processing in fibromyalgia, nociplastic pain, and functional MRI methods development. Key trends include investigating neural signaling, cognitive-emotional influences on pain, and comparative studies between chronic pain conditions. Stroman has developed specialized MRI-compatible stimulation equipment like the RTS-2 device and created custom analysis software in MATLAB and Python. His lab has produced over 100 publications and 2500+ citations, with ongoing work on data-driven analysis approaches for pain research.

ILYAS OZERمشاهده پروفایل

دانشیار

• Machine Learning
• Deep Learning
• Signal Processing
• +۴ مورد دیگر

İlyas Ozer is an Associate Professor in the Department of Computer Engineering at Bandırma Onyedi Eylül University, serving as the Software Department Head. His research focuses on machine learning applications in healthcare, energy systems, and natural language processing. He has authored over 20 peer-reviewed articles and supervised several theses on topics like blockchain-based identity systems and smart transportation. Active in editorial roles for journals like Aintelia Science Notes, he leads projects on medical imaging analysis and food freshness detection using machine learning. His teaching spans courses in data mining, deep learning, and embedded systems.

Tomislav Kartalovمشاهده پروفایل

استادیار

• Image and Video Processing
• Mobile Platform Implementation
• Machine Learning
• +۵ مورد دیگر

Tomislav Kartalov is an Assistant Professor at the Department of Electronics, Faculty of Electrical Engineering and Information Technologies, University of St. Cyril and Methodius in Skopje, Republic of Macedonia. He has held this position since March 2015, following previous roles as a Teaching and Research Assistant from 2002 to 2015 and a brief period in technical maintenance at Macedonian Radio Television. Education includes a Ph.D. in Technical Sciences (2014) with a dissertation on Fusion of Digital Images and Videos for Visual Quality Improvement and Mobile Platform Implementation Possibilities , an M.Sc. in Electrical Engineering (2008) focusing on Visual Quality Enhancement of Digital Television Videos , and a B.Sc. in Electrical Engineering (2002) with a thesis on Software for Switching Power Supply Design (Flyback) . His research interests span image/video processing, mobile platform optimization, machine learning applications in education and healthcare, and sensor networks. Key areas include exposure fusion algorithms for mobile devices, real-time traffic sound detection systems, and multimodal information fusion for intelligent transportation systems. His publications from 2006 to 2023 reflect a strong focus on computational photography, embedded systems, and healthcare technology. Notable contributions include automated exposure fusion techniques for low-resource devices and AI-driven diagnostics using neuroimaging. No scientific awards or grants are explicitly mentioned in the provided texts. Kartalov’s advising history is not listed, but his teaching roles suggest involvement in graduate student mentorship. Laboratory affiliations are not detailed in the text.

• Pediatric Emergency Medicine
• Heart Rate Variability (HRV)
• Biofeedback Interventions
• +۴ مورد دیگر

Christine Cho, MD, MPH is a Clinical Professor of Pediatrics (Part-Time) at the University of Southern California's Keck School of Medicine. Her research focuses on the neurophysiological effects of heart rate variability (HRV) biofeedback interventions, particularly in pediatric and aging populations. She explores how HRV modulation impacts emotion regulation, cognitive function, and neural plasticity through multimodal neuroimaging techniques. Her work spans clinical trials, translational research, and medical education innovation in emergency care environments. Her research interests include pediatric emergency medicine, neuroimaging applications for emotional and cognitive processes, and the development of evidence-based interventions for healthcare professionals. Key contributions include studies on sex differences in neural correlates of emotion regulation, hippocampal volume changes with biofeedback, and plasma biomarker shifts linked to HRV interventions. Recent publications highlight her focus on: HRV biofeedback's impact on emotional memory biases, intergenerational effects of biofeedback on amyloid-beta levels, and trust dynamics between supervisors and trainees in emergency settings. Her work bridges basic neuroscience with clinical practice, emphasizing translational outcomes for patient care and medical education.

Nicole Lazarمشاهده پروفایل

استاد

• Statistical Inference
• Functional Neuroimaging Data Analysis
• Model Selection
• +۹ مورد دیگر

Nicole Lazar is the Department Head and Professor of Statistics at Pennsylvania State University. She holds a PhD from the University of Chicago (1996), an MS from Stanford University (1993), and a BA in Psychology and Statistics from Tel Aviv University (1988). Her research focuses on foundational statistical inference, neuroimaging data analysis, and topological data science, with applications in cognitive neuroscience, climatology, and psychology. She pioneered statistical methods for fMRI analysis and has developed interdisciplinary approaches at the intersection of statistics, mathematics, and computer science. Her professional service includes roles as Editor of *The American Statistician*, Associate Editor for multiple journals, and co-Editor of a Special Issue on 'Statistical Inference in the 21st Century.' Lazar authored the textbook *The Statistical Analysis of Functional MRI Data* (Springer) and has published extensively in top journals. She is a Fellow of the American Statistical Association (2014), Fellow of the Institute of Mathematical Statistics (2021), and Elected Member of the International Statistical Institute (2006). Previously, she served on faculty at Carnegie Mellon University and the University of Georgia, where she also served as Interim Department Head (2014–2016). Lazar’s teaching includes advanced courses like STAT 470W (Statistical Consulting), STAT 512 (Applied Nonparametric Statistics), and STAT 580/581 (Advanced Topics in Statistics). Her work emphasizes methodological innovations, reproducibility in science, and promoting gender equity in statistics through her presidency of the Caucus for Women in Statistics (2019).