جستجوی استاد راهنمای دانشگاهی

Ashley Mosemanمشاهده پروفایل

استادیار

• CNS immunity
• Olfactory barrier immunology
• Neuroimmunology
• +۵ مورد دیگر

Ashley Moseman serves as an Assistant Professor of Integrative Immunobiology and Assistant Professor of Cell Biology at Duke University School of Medicine. She holds significant affiliations as a Faculty Network Member of the Duke Institute for Brain Sciences and a Member of the Duke Cancer Institute. Her pioneering research examines the delicate balance between neuronal function and immune protection at the olfactory neuroepithelial barrier, where sensory neurons directly interface with the external environment while protecting the central nervous system from pathogens. Dr. Moseman completed her Ph.D. at Harvard University in 2011, establishing the foundation for her interdisciplinary career at the intersection of immunology and neuroscience. Her research program focuses on understanding how immunological surveillance operates at the unique olfactory barrier, where neurons must contact the external environment to perform chemosensory functions while preventing pathogens from entering the CNS. The Moseman Lab employs cutting-edge multiphoton intravital imaging to visualize immune responses in vivo, revealing dynamic cellular interactions during viral infections and responses to pathogens like Naegleria fowleri. Current projects investigate olfactory barrier mechanisms, neuroimmune crosstalk, host-pathogen dynamics, and immune responses to deadly neurotropic pathogens. Analysis of Dr. Moseman's publication record demonstrates a cohesive research trajectory centered on neuroimmunology and mucosal defense mechanisms. Her work spans fundamental immunological processes, host-pathogen interactions at neural interfaces, and translational applications for understanding neurological complications of infections. A significant portion of her recent research addresses SARS-CoV-2-related olfactory dysfunction and the immunological basis of pathogen invasion through the olfactory system into the central nervous system. Dr. Moseman has secured substantial research funding including 'Using tissue-specific Naegleria opportunism to dissect olfactory immunity' (2025-2030), 'Characterizing olfactory plasma cell dynamics and survival niche within the upper airway' (2024-2029), and the 'Advanced Immunobiology Training Program for Surgeons' (2019-2029). She actively contributes to graduate education through the Medical Scientist Training Program (2022-2027) and teaches advanced immunology courses including IMMUNOL 736 and IMMUNOL 494. The Moseman Lab represents a leading center for neuroimmunology research, utilizing in vivo imaging to visualize immune responses within the central nervous system. Their work has significant implications for understanding how pathogens breach neurological barriers and how the immune system protects the brain while preserving essential sensory functions, with potential applications for treating neurological infections and inflammatory conditions.

Pouya Bashivanمشاهده پروفایل

استادیار

• Computational Neuroscience
• Machine Learning
• Artificial Neural Networks
• +۶ مورد دیگر

Pouya Bashivan is an Assistant Professor in the Department of Physiology at McGill University's Faculty of Medicine. His research focuses on developing computational models to explain and regulate neural responses during visual tasks requiring memory, combining machine learning, neuroscience, and cognitive science. Education : Ph.D. in Computer Engineering (2016), Postdocs in Machine Learning (2020) and Computational Neuroscience (2016-2020) His lab investigates: Topographical neural networks for visual cortex simulation Massively-multitask models for prefrontal cortex Saccade-driven visual exploration models Predictive hippocampus models for episodic memory Recent publications explore adversarial robustness, memory-augmented networks, and brain-state decoding. Current projects emphasize causal models, brain-AI alignment, and translating computational neuroscience into therapeutic applications. The lab is located in the McIntyre Medical Sciences Building, Room 1117, Montreal, Quebec.

• Neuroscience
• Cognitive Science
• Visual Perception
• +۷ مورد دیگر

Dr. Ben Harvey is an Associate Professor (with Ius Promovendi) in the Perception Group of the Department of Experimental Psychology at Utrecht University, Netherlands, within the Faculty of Social and Behavioural Sciences. He is based at the Helmholtz Institute and can be contacted at b.m.harvey@uu.nl. Harvey completed his DPhil at Oxford University with Professor Oliver Braddick in 2009, followed by postdoctoral work with Professor Serge Dumoulin at Utrecht. In 2015, he moved to Coimbra on a starter grant from the Portuguese Foundation for Science and Technology before returning to Utrecht in 2016 as an Assistant Professor. He was promoted to Associate Professor in 2019 and has led his own research group since 2015. Harvey's research focuses on characterizing sensory and cognitive systems in the human brain, particularly neural responses and computations within these systems. His work combines cutting-edge neuroimaging approaches with computational modeling and behavioral experiments. Initially studying the early visual system as a model of neural processing, he extended invasive animal neurophysiological approaches to non-invasive human neuroimaging. His recent work investigates neural responses underlying cognition in the human association cortex, examining how visual space and number processing differs between cultures and in clinical disorders. His fingerprint reveals expertise in Functional Magnetic Resonance Imaging, Numerosity, Receptive Field, Visual Cortex, Population Receptive Field, Nerve Potential, Early Visual Cortex, and Topographic Maps. His publication record demonstrates significant impact, with works like 'Topographic representation of numerosity in the human parietal cortex' (2013) receiving over 360 citations. His research spans visual neuroscience, with emphasis on how the brain processes visual information, attention mechanisms, and numerical cognition, revealing generalized quantity processing systems in the human brain. Award for highest-rated abstract (2013) Brain Centre Rudolph Magnus Research Award (Best Paper of the Year) (2014) Causal link between cortical organization and conscious perception: human fMRI and electrophysiology (2009, 2010) Harvey has been actively engaged in knowledge dissemination, with multiple invited talks at institutions including INSERM in Paris (2016) and the University of Parma (2015). His research has received significant media attention, with interviews on National Public Radio (NPR) USA, Livescience.com, and Science Magazine in 2013. Beyond academic publications, he writes popular science articles exploring the relationship between visual neuroscience and visual arts. As part of the Helmholtz Institute Experimental Psychology research program, Harvey collaborates widely to investigate visual space and number processing across different populations, contributing to our understanding of how these cognitive functions vary between cultures and in clinical disorders.

• Topology of Complex Systems
• Higher-order Networks
• Topological Neuroscience
• +۷ مورد دیگر

Giovanni Petri is a Professor in the Network Science Institute at Northeastern University London, where he joined in June 2023. Previously, he held positions at CENTAI as a Principal Researcher and at IMT Lucca as a Guest Scholar, with earlier affiliations at ISI Foundation and Imperial College London. His educational background includes a PhD in Complex Networks from Imperial College London (2012), an MSc in Theoretical Physics from the University of Pisa (2008), and a BSc in Physics from the University of Pisa (2005). Petri's research spans the analysis of neuroimaging data and AI systems with topological techniques, the formalization of cognitive control models with tools of statistical mechanics and network theory, and the study of the predictability of socio-technical systems. His work in Topological Neuroscience explores brain architecture using algebraic topology, while his research in Cognitive Neuroscience focuses on neural mechanisms underlying human cognition. He is particularly known for his work on higher-order networks, using mathematical frameworks like hypergraphs and simplicial complexes to model systems with multi-way interactions. His recent publications (2023-2025) demonstrate a strong focus on higher-order network theory applied to neuroscience, with particular emphasis on topological approaches to brain connectivity, social contagion models, and the physics of complex systems. These works reveal consistent themes in understanding how multi-body interactions shape system dynamics across biological, social, and technological domains. European Research Council Consolidator Grant (RUNES: Reconstruction and unification of neural and ecological systems, 2024) As Principal Investigator of the NPLab, Petri advises numerous PhD and postdoctoral researchers including Marilyn Gatica, Andrea Santoro, and Simone Poetto. His RUNES project, funded by the ERC Consolidator Grant, represents a significant research initiative. The lab maintains active collaborations with CENTAI, Project CETI (Cetacean Translation Initiative), and various international institutions. The NPLab investigates the role of topology and geometry in the collective dynamics of complex systems, ranging from neuroscience to society, using statistical mechanics, algebraic topology, and innovative computational approaches. Current projects include Topological Neuroscience, Cognitive Neuroscience, Higher-order Networks, Project CETI, and RUNES.

Arnaud Bertschمشاهده پروفایل

مدرس

• Microfluidics
• Nanofluidics
• MEMS/NEMS
• +۵ مورد دیگر

Arnaud Bertsch is a Lecturer at the École Polytechnique Fédérale de Lausanne (EPFL) within the School of Engineering (STI) and the Department of Microengineering (IEM). He is affiliated with the Microsystems Laboratory 1 (LMIS1) and has been actively involved in teaching advanced microfabrication techniques and MEMS sensor/actuator practicals. His research spans microfluidics, nanofluidics, biomedical devices, and 3D microfabrication, with a focus on neural probes, drug delivery systems, and cell manipulation technologies. Microfluidic hydrodynamic and dielectrophoretic systems Nanovolcano microelectrode arrays for electrophysiology Thermal control of ionic transport in nanochannels 3D lipid microrobots for drug delivery MEMS-based intraocular pressure sensors Arnaud Bertsch has supervised PhD students including Torres Vila Pol, Zhang Tao, and past advisees like Clémentine Lipp, Nicolas Maïno, and Joan Teixidor. His work bridges fundamental research in nanofluidics with applied biomedical solutions, contributing to fields such as neuroscience, cancer therapy, and implantable medical devices. The articles listed demonstrate expertise in microsystem design, electrochemical sensing, and biofabrication technologies.

• Neuroscience
• Neurobiology
• Visual Neuroscience
• +۳ مورد دیگر

Vincent Bonin is a Senior Lecturer in the Department of Biology at KU Leuven's Faculty of Sciences. He is affiliated with the VIB-KU Leuven Center for Neuro Electronics Research Flanders (NERF) and the KU Leuven Brain Institute (LBI). His research focuses on neural circuits and visual neuroscience, with an emphasis on cortical and subcortical mechanisms of perception and plasticity. Research Interests: Vincent investigates visual coding, cortical connectivity, and brain circuit dynamics. His work spans topics like: Role of non-hierarchical visual pathways in perception Dendritic processing in the superior colliculus Cell type-specific connectivity in layer 2/3 visual cortex Astrocyte-mediated cortical plasticity Development of high-resolution intracortical visual prosthetics Recent Projects: • The contributions of non-hierarchical visual pathways to visual coding and perceptual behavior (2025-2028) • An investigation into cell type-specific connectivity rules in visual cortex (2024-2027) • Short- and long-term circuit mechanisms of motor rehabilitation after spinal cord injury (2024-2027)

Jennifer Somersمشاهده پروفایل

استادیار

• Developmental Psychology
• Clinical Psychology
• Psychophysiology
• +۷ مورد دیگر

Jennifer Somers is an Assistant Professor in the Department of Psychological Sciences at Auburn University , directing the FLOWER Laboratory (Families: Leveraging Opportunities for Wellbeing and Resilience). Her research examines biobehavioral processes in parent-child interactions that influence depression and anxiety risks. Education: PhD in Clinical Psychology (Arizona State University, 2021) MA in Clinical Psychology (Arizona State University) BA in Psychology & English (Pomona College) Her work focuses on dyadic resilience , emotion regulation , and physiological synchrony in families. She has secured funding from NIMH, NSF, and private foundations. Recent publications analyze parent-child interactions , RSA synchrony , and transdiagnostic biomarkers spanning developmental psychology, clinical research, and behavioral science. Labs & Teams: FLOWER Lab investigates mechanisms to promote family resilience across the lifespan, integrating biological and environmental factors in mental health outcomes.

Gabriel Koch Ockerمشاهده پروفایل

استادیار

• Theoretical Neuroscience
• Computational Neuroscience
• Neuronal Network Modeling
• +۵ مورد دیگر

Gabriel Koch Ocker is an Assistant Professor in the Department of Mathematics & Statistics at Boston University, specializing in theoretical and computational neuroscience. His research investigates how neural activity encodes sensory information, shapes behavior, and evolves through learning mechanisms. Research Focus: Structure-function relationships in neuronal networks Methodology: Dynamical systems, stochastic processes, statistical physics Collaborations: Experimental validation of computational models Recent publications analyze integrate-and-fire networks, dendritic calcium spiking, inhibition-stabilized circuits, and metastability in stochastic neuronal systems. His group combines mathematical rigor with biological relevance to explore neural coding, plasticity, and functional hierarchy in cortical structures. Key contributions include tensor decomposition approaches to correlation analysis, reconciling recording technique discrepancies, and developing field-theoretic frameworks for compartmental modeling. Work spans from molecular-level channel dynamics (Kv7 channels) to brain-area-level functional organization.

Maryam Ghahramaniمشاهده پروفایل

مدرس ارشد

• Human Motion Analysis
• Machine Learning
• Rehabilitation Engineering
• +۵ مورد دیگر

Dr. Maryam Ghahramani is a Senior Lecturer in AI & Robotics at the Faculty of Science & Technology, University of Canberra, Australia. She holds a BSc in Electrical Engineering from Shiraz University, Iran, and a PhD in Biometric Gait Analysis from the University of Wollongong, Australia. Biomedical Engineering Researcher Machine Learning Specialist Human Motion Analysis Expert Her research focuses on applying machine learning to human motion analysis for rehabilitation purposes, particularly in three key areas: Parkinson's Disease: Using fNIRS and machine learning for disease detection and motor function assessment Fall Prevention: Analyzing postural sway and risk of falls in older adults Spatial Disorientation: Studying balance in hypoxic aviation environments Recent publications demonstrate her work at the intersection of biomedical engineering, machine learning, and clinical rehabilitation. Current projects include: Young Onset Dementia Detection with 12-week Home-Based Exercise Programs Mild Hypoxia Analysis for Aviation Safety Balancing Mat Performance Evaluation

Ghazal Bargshadyمشاهده پروفایل

مدرس

• Affective Computing
• Artificial Intelligence
• Computer Vision
• +۷ مورد دیگر

Dr. Ghazal Bargshady is a Lecturer at the University of Canberra , with expertise in Affective Computing , Artificial Intelligence , and Healthcare Technology . Her roles include teaching units such as Computer Vision, Data Analytics, and Soft Computing, as well as supervising PhD and Master by Research students in AI-driven projects for healthcare and road safety. Education: She earned her PhD in Artificial Intelligence and Computer Vision from the University of Southern Queensland in 2020. Research Interests: Dr. Bargshady specializes in Computer Vision Deep Learning Biosignal Processing Facial Expression Analysis Human Factors in AI Wearable Sensors Multimodal Data Fusion Brain–Computer Interfaces Her work addresses real-world challenges in pain assessment, depression recognition, and driver safety using cutting-edge AI models. Article Trends: Her recent publications focus on Transformer architectures , fNIRS signal analysis , multimodal pain detection , and depression severity estimation via facial video data. These studies highlight her contributions to AI in healthcare , transportation safety , and biomedical signal processing . Teaching Activities: Dr. Bargshady has lectured units including Programming for Data Science , Computer Vision , and Soft Computing , emphasizing practical AI applications.

Hongmi Leeمشاهده پروفایل

استادیار

• Human Long-Term Memory
• Naturalistic Memory
• Functional Neuroimaging
• +۲ مورد دیگر

Hongmi Lee is an Assistant Professor in the Department of Psychological Sciences at Purdue University. Her research focuses on human long-term memory , naturalistic memory , and functional neuroimaging , using behavioral experiments and fMRI to explore how the brain encodes and retrieves complex real-world experiences. PhD, New York University (2018) Lee investigates how memories for naturalistic events are structured in the brain, emphasizing the roles of the posterior medial cortex and parietal cortex in memory reactivation. Her work examines semantic integration, contextual binding, and neural dynamics during spontaneous recall and future thinking. The 15 most recent articles highlight trends in episodic retrieval , event segmentation , and neural activity patterns during memory processing. Key methodologies include fMRI , naturalistic stimuli , and network science . Labs: Lee Memory and Cognition Lab

• Quantum Computing
• Artificial Intelligence
• Neuromorphic Computing
• +۵ مورد دیگر

Professor Frank Zhigang Wang is a faculty member at the School of Computing , University of Kent. His research focuses on Quantum Computing , Neuromorphic Computing , and Cloud Computing , with significant contributions to Memristor Technology and Green Computing . He has secured £5 million in research grants from EC/UK/industries and chaired/co-chaired over 10 international conferences, including IEEE and ACM events in Manchester, Delhi, Beijing, and Shanghai. Key research areas: Quantum Computing, Artificial Intelligence, Neuromorphic Systems, Cloud Security. Professional roles: Fellow of the British Computer Society, former IEEE Region 8 Area 2 Coordinator. His work explores Landauer Bound optimization in quantum systems, Spin-Encoded Quantum Computers , and Topological Electronics . Recent publications address post-quantum cryptography and memristor-based neuromorphic architectures . He has supervised 15 PhD students (14 completed) and 7 research fellows. Awards include Best Teacher Award nominations (2016, 2022) and ACM/IEEE Super Computing Challenge Finalist (2007).

Rafal Bogaczمشاهده پروفایل

استاد

• Computational Neuroscience
• Neural Networks
• Parkinson's Disease
• +۵ مورد دیگر

Professor Rafal Bogacz is a leading academic at the University of Oxford, affiliated with St Edmund Hall and the MRC Brain Network Dynamics Unit . He teaches computational neuroscience and statistics at both undergraduate and postgraduate levels, including the MSc in Neuroscience and BSc in Biomedical Science programs. MSc: Wroclaw University of Technology PhD: University of Bristol Postdoctoral Researcher: Princeton University His research focuses on computational neuroscience , particularly modeling brain networks involved in action selection , decision making , and Parkinson's disease pathophysiology. Key themes include: Developing predictive coding models of cortical computations Understanding basal ganglia neural circuits in healthy and diseased states Designing closed-loop deep brain stimulation paradigms Recent publications highlight work in neural plasticity , dopamine signaling , and computational psychiatry , with a notable Wellcome Discovery Award supporting research on learning in neurons . The Bogacz Group maintains strong collaborations with experimental neuroscientists and shares open datasets through the MRC BNDU Data Sharing Platform . Wellcome Discovery Award (2025): For learning in neurons Europe PMC Open Access (multiple): For numerous PLoS, Nat Neurosci, and J Neural Eng publications As a computational neuroscientist, Professor Bogacz supervises D.Phil. students and leads research programs that bridge theoretical neuroscience with clinical applications . The group actively participates in MRC BNDU training initiatives and public engagement activities like Schools Open Day demonstrations.

• Cerebrovascular Surgery
• Endovascular Neurosurgery
• Skull Base Surgery
• +۶ مورد دیگر

Karol Budohoski, MD, PhD, FRCS, is an Assistant Professor in the Department of Neurosurgery at the University of Utah , with additional Adjunct Assistant Professor status in Radiology & Imaging Sciences. He specializes in cerebrovascular , endovascular , and skull base neurosurgery , treating complex pathologies like brain aneurysms, arteriovenous malformations, and skull base tumors. Education: PhD in Neurosurgery (University of Cambridge), MD (Medical University of Warsaw), Clinical Fellowships at University of Utah and UCSF His academic focus on subarachnoid hemorrhage pathophysiology and cerebral vasospasm has led to innovations in brain monitoring tools. Recent publications (2023-2025) span neurovascular surgery , stroke interventions , global neurosurgery , and cerebral autoregulation studies. He practices at the Clinical Neurosciences Center in Salt Lake City, Utah, with a patient rating of 4.9/5 (125 reviews), praised for clarity, attentiveness, and technical expertise.

Pixu Shiمشاهده پروفایل

استادیار

• Microbiome Research
• Longitudinal/Temporal Omic Data
• Integration of Omic Data
• +۲ مورد دیگر

Pixu Shi is an Assistant Professor in the Department of Biostatistics and Bioinformatics at Duke University's School of Medicine. Previously, they served as a Visiting Assistant Professor in the Department of Statistics at the University of Wisconsin-Madison (2018-2020) and as a Postdoctoral Researcher in the Department of Biostatistics at the University of Wisconsin-Madison (2016-2018). Dr. Shi earned their PhD in Biostatistics from the University of Pennsylvania in 2016 under advisor Hongzhe Li. They also hold an MS in Biostatistics from the University of Pennsylvania (2015), an MS in Statistics from Rutgers University (2012), and a BS in Statistics from Peking University (2010). Dr. Shi's research focuses on developing statistical methods for Microbiome Research, Longitudinal/Temporal Omic Data analysis, Integration of Omic Data, Spatial Omics, and High-dimensional Statistical Inference. Their work bridges statistical theory with practical applications in biomedical research, particularly in microbiome studies where they've made significant contributions with the TEMPTED (TEMPoral TEnsor Decomposition) method. The article trends show a strong focus on microbiome analysis, statistical methodology development, and applications in obesity, infectious disease, and cancer research. Their most recent work (2024-2025) demonstrates expertise in tensor decomposition methods, longitudinal data analysis, and integrating microbiome data with clinical outcomes across diverse areas including adolescent obesity, viral infections, and cancer metastases. Dr. Shi has secured multiple substantial research grants from major institutions including the National Institutes of Health (NIMH, NIAID, NCI, NIDDK, NIA), totaling over a decade of continuous funding for projects related to microbiome research, HIV/AIDS, cancer biomarkers, and metabolic studies. They actively contribute to education through teaching courses such as BIOSTAT 905: Linear Models and Inference at Duke University and previously taught statistics courses at the University of Wisconsin-Madison. Dr. Shi has also organized specialized workshop series including Quantitative Methods for HIV/AIDS, Microbiome, Immunology, and Cancer Bioinformatics.