جستجوی استاد راهنمای دانشگاهی

Mayank R. Mehtaمشاهده پروفایل

استاد

• Neurophysics
• Synaptic Plasticity
• Learning and Memory
• +۳ مورد دیگر

Mayank R. Mehta is a Professor at the University of California, Los Angeles (UCLA), holding joint appointments in the Departments of Physics & Astronomy, Neurology, and Neurobiology. He is a member of the Brain Research Institute and the W. M. Keck Center for Neurophysics at UCLA. His research bridges experimental and theoretical neuroscience, focusing on how neuronal networks encode space-time, the role of brain rhythms in learning and memory, and the impact of sleep and virtual reality on neural dynamics. His recent publications highlight breakthroughs in understanding hippocampal spatiotemporal selectivity, dendritic activity during behavior, and the causal influence of visual cues on memory neurons. Notable findings include the discovery that dendrites generate ten times more spikes than neuronal cell bodies and the modulation of hippocampal theta rhythms in virtual reality. Research Themes: Neurophysics of spatial-temporal coding Dendritic contributions to learning Virtual reality and brain plasticity Neural oscillations in memory consolidation Key Collaborators: Bert Sakmann (Max Planck Florida Institute) Thomas Hahn (Bernstein Center Heidelberg/Mannheim) Maryam Ghorbani (UCLA) Mehta's lab at UCLA trains graduate and postdoctoral researchers in cutting-edge techniques combining hardware development, electrophysiological recordings, and biophysical modeling. His work has significant implications for treating learning and memory disorders like Alzheimer's disease.

• Self-organized criticality
• Neuronal network dynamics
• Excitation/Inhibition balance
• +۵ مورد دیگر

Anna Levina is an Assistant Professor for Computational Neuroscience at the University of Tübingen , affiliated with the Department of Computer Science under the Faculty of Science. Her research focuses on the self-organization of neuronal activity, critical dynamics in neural networks, and the excitation/inhibition balance in cortical circuits. Current positions: Assistant Professor (since 2018), Group Leader (2017-2018), Equality Officer (Computer Science) Previous roles: IST Fellow (2015-2017), Associated Researcher (2011-2015), Postdoc/PI (2011-2015), Postdoc (2008-2011) Her research integrates mathematical modeling , statistical physics , and computational neuroscience to study criticality phenomena, neural avalanches, and adaptive network dynamics. Key interests include: Self-organized criticality in neural systems Excitation/Inhibition balance mechanisms Network topology and dynamics Timescale analysis in neural processing Stochastic modeling of neural activity Recent publications reveal trends in understanding critical dynamics across biological and artificial networks, with applications to memory systems, sensorimotor integration, and disease modeling. She has received recognition as an IST Fellow .

• Condensed Matter Physics
• Quantum Materials
• Quantum Devices
• +۳ مورد دیگر

Hugh Churchill is a Professor in the Department of Physics at the University of Arkansas, College of Arts & Sciences. His research focuses on quantum materials and devices, particularly condensed matter physics with applications in 2D systems and quantum transport. Education: PhD in Physics from Harvard University, BA in Physics and BM in Music Performance from Oberlin College Recent research trends include studies on 2D materials like transition metal dichalcogenides and black phosphorus, investigating quantum transport phenomena, supercurrent tuning, strain engineering for exciton control, and applications of machine learning in quantum material discovery. His work also explores THz emission mechanisms and quantum noise mitigation strategies. Arkansas Research Alliance Fellow Presidential Early Career Award for Scientists and Engineers NSF CAREER Award ORAU Powe Junior Faculty Award AFOSR Young Investigator Connor Faculty Fellowship Hugh teaches graduate and undergraduate courses in quantum mechanics, modern physics, and 2D materials, including PHYS 5413 Quantum Mechanics I and PHYS 6713 Condensed Matter Physics II.

Mengsen Zhangمشاهده پروفایل

استادیار

• Complex Systems
• Neuroscience
• Computational Mathematics
• +۵ مورد دیگر

Mengsen Zhang is an Assistant Professor at Michigan State University (MSU) in the Department of Computational Mathematics, Science and Engineering and the Neuroscience Program. She bridges complex systems science, neuroscience, computational mathematics, and topological data analysis (TDA) to study brain dynamics and coordination mechanisms across scales. Education: B.S. in Psychology and Pharmaceutical Sciences (Peking University); M.S. in Criminology (University of Pennsylvania); Ph.D. in Complex Systems and Brain Sciences (Florida Atlantic University, with Drs. Emmanuelle Tognoli and J. A. Scott Kelso). Postdoctoral Training: Stanford University (with Dr. Manish Saggar) and University of North Carolina at Chapel Hill (with Dr. Flavio Frohlich). Her research focuses on the intersection of topological data analysis and dynamical systems, particularly in understanding brain oscillations, neural networks, and social coordination dynamics. She explores how third-party interventions can stabilize or disrupt coordination in biological and social systems, using both empirical and theoretical approaches. Her recent publications (2022–2025) highlight applications of transcranial alternating current stimulation (tACS) in psychiatric disorders, metastability in brain dynamics, and novel computational methods for analyzing neural and behavioral data. These works span neuroscience, psychiatry, and computational modeling. She teaches courses such as CMSE 381: Fundamentals of Data Science Methods (MSU) and STT 381: Fundamentals of Data Science Methods, integrating computational tools into academic training.

• Theoretical Neuroscience
• Statistical Physics of Neural Networks
• Dynamics of Neuronal Networks
• +۶ مورد دیگر

Prof. Dr. Moritz Helias is a University Professor and leads the Theory of Multi-Scale Neuronal Networks group at the Institute for Advanced Simulation (IAS-6), Computational and Systems Neuroscience, Forschungszentrum Jülich. His research bridges biological and artificial neural networks, focusing on dynamics, information processing, and the physics of AI. The group is part of a larger interdisciplinary institute that integrates theory, simulation, and data analysis to understand the brain. Institution: Forschungszentrum Jülich School: Institute for Advanced Simulation Department: IAS-6, Computational and Systems Neuroscience Position: Professor and Group Leader Email: m.helias@fz-juelich.de His research interests lie at the intersection of statistical physics and neuroscience. He investigates how structure shapes dynamics in both biological and artificial networks, aiming to uncover general principles of information processing. Using methods from statistical physics, his work enables a unified framework for understanding collective phenomena, learning, and generalization. Key areas include spiking neural networks, renormalized field theory, and the theoretical foundations of AI. The recent publications reflect a strong trend toward multi-scale modeling of neural systems, integrating statistical physics with neuroscience. Topics include spiking network dynamics, mean-field theory, renormalization, and applications of machine learning in physics. The work spans biological realism and artificial intelligence, with implications for neuromorphic computing and brain-inspired AI architectures. While no scientific awards are listed in the provided texts, his group actively contributes to open science through tools like NEST and theoretical frameworks that influence both neuroscience and AI. Prof. Helias supervises a research group focused on theoretical and computational approaches, contributing to collaborative projects involving large-scale simulations and data analysis. His team works closely with experimentalists and theorists to validate models and advance understanding of brain function. The group is also involved in developing simulation technologies and theoretical tools that support reproducible neuroscience. The Theory of Multi-Scale Neuronal Networks group is embedded within a vibrant research environment at IAS-6, collaborating with teams in statistical neuroscience, computational neurophysics, and future simulation architectures. This fosters a loop between data, theory, and simulation, enabling cutting-edge research on brain function and artificial intelligence.

Yasser Iturria Medinaمشاهده پروفایل

استادیار

• Neuroimaging
• Neuroinformatics
• Precision Medicine
• +۶ مورد دیگر

Yasser Iturria Medina is an Assistant Professor at the Montreal Neurological Institute (MNI) , McGill University, within the Department of Neurology and Neurosurgery . He is an associate member of the Ludmer Centre for Neuroinformatics and Mental Health and the McConnell Brain Imaging Centre . Academic Rank: Assistant Professor Key Affiliations: MNI, Ludmer Centre, McConnell Brain Imaging Centre His educational background includes: Undergraduate: Nuclear Engineering (2004), Higher Institute for Nuclear Sciences and Technology, Cuba MSc: Neurophysics and Neuroengineering (2006), Cuban Neuroscience Center PhD: Neuroimaging and Neuroinformatics (2013), National Center for Scientific Research and Havana’s University of Medical Science His research focuses on neuroinformatics for precision medicine , particularly in neurodegenerative diseases like Alzheimer's and Parkinson's. His lab develops multiscale brain models integrating molecular, imaging, and cognitive data to characterize pathogenic mechanisms and identify personalized interventions. Key research areas include: Neurodegeneration modeling Neurovascular interactions in Alzheimer's Multi-omics integration for disease subtyping Neuroimaging biomarkers across neurodegenerative spectra Computational modeling of amyloid-beta and tau propagation The article analysis reveals his emphasis on: Alzheimer's disease mechanisms (45% of recent works) Multi-omics and transcriptomic modeling (30%) Neurovascular and white matter pathology (20%) Machine learning applications in neuroimaging (15%) Development of tools like NeuroPM-box and MVComp toolbox His lab has been instrumental in creating NeuroPM-box , a software platform for integrating molecular, neuroimaging, and clinical data to characterize neurodegenerative progression and heterogeneity. He has also contributed to CAPTURE ALS , a comprehensive analysis platform for amyotrophic lateral sclerosis.

André Longtinمشاهده پروفایل

استاد

• Nonlinear Dynamics
• Stochastic Dynamics
• Theoretical Biophysics
• +۶ مورد دیگر

André Longtin is a Full Professor in the Department of Physics at the University of Ottawa, affiliated with the Faculty of Science. He co-directs the Centre for Neural Dynamics & Artificial Intelligence and holds cross-appointments in Cellular and Molecular Medicine, Mathematics and Statistics. His research focuses on nonlinear dynamics, stochastic systems, and computational neuroscience, with applications to sensory processing, neural coding, and thermodynamic principles in biological systems. Education: B.Sc. (Honours Physics, Université de Montréal), M.Sc. (Physics, Université de Montréal), Ph.D. (Physics, McGill University, 1989). Postdoctoral training at Los Alamos National Laboratory. Research Interests: Theoretical biophysics, neural modeling, entropy production in biological systems, delayed dynamical systems, and interdisciplinary applications of nonlinear science. His group explores computations in hippocampus and zebrafish pallium, epilepsy mechanisms, neural coding in electrosensory systems, and autonomous stochastic rhythms. Recent Work: Articles highlight entropy dynamics in humans, myelin plasticity effects on neural networks, and reservoir computing with delayed loops. Awards include APS Fellowship (2003) and the NSERC Brockhouse Prize (2017). Editorial Roles: Biological Cybernetics, Frontiers in Computational Neuroscience, and others. Collaborations span systems neuroscience, clinical specialties, and engineering.

David Carmichaelمشاهده پروفایل

استاد

• Magnetic Resonance Imaging (MRI) Physics
• EEG-fMRI Integration
• Epilepsy Research
• +۳ مورد دیگر

Professor David Carmichael is a distinguished academic at King's College London , affiliated with the School of Biomedical Engineering & Imaging Sciences and the Department of Biomedical Computing . His research focuses on Magnetic Resonance Imaging (MRI) Physics , EEG-fMRI integration , and epilepsy neuroimaging , with a particular emphasis on mapping epileptogenic networks and optimizing MRI safety for concurrent neurophysiological recordings. Education : PhD in Medical Physics (UCL, 2004), MSci in Physics (UCL, 2000). External Role : Honorary Reader at UCL Great Ormond Street Institute of Child Health. His research interests span advanced neuroimaging techniques, including 7T MRI for pediatric epilepsy, quantitative susceptibility mapping to detect cortical abnormalities, simultaneous EEG-fMRI safety protocols, network-guided neuromodulation for treatment optimization. Recent publications highlight his work on ultra-high field MRI in drug-resistant pediatric cohorts, RF-induced heating safety during combined EEG-fMRI, image quality transfer for low-field MRI in developing regions, motion correction strategies in pediatric scans. He leads critical projects such as 7 Tesla Sodium MRI for Epilepsy (MRC-funded) and Minimal Motion MRI Systems (NIHR-funded), while contributing to global epilepsy research through the King’s Epilepsy Research Collective (KERC) .

• Neuroscience
• Physics
• Neuroimaging
• +۳ مورد دیگر

Valerij Kiselev serves as a Professor in the Department of Neurophysics at the Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany. His institutional address is Stephanstraße 1A, 04103 Leipzig, Saxony. His research centers on Neurophysics, integrating Neuroscience and Physics to advance Neuroimaging and Biophysics methodologies. Key interests include cognitive brain mechanisms, medical physics applications, and quantitative modeling of neural processes within the institute's specialized framework. No scientific awards were documented in the source material. No student mentorship or grant involvement details were provided. The Department of Neurophysics operates under the institute's research mandate, though specific lab structures or team compositions remain unspecified in the available data.

• Computational Neuroscience
• Neurophysics
• Brain Oscillations
• +۲ مورد دیگر

Paul Tiesinga is Professor of Neuroinformatics at Radboud University's Faculty of Science, where he directs the Neuroinformatics group at the Donders Centre for Neuroscience. His research focuses on understanding information processing in the brain, particularly the role of oscillations ('brain waves') in cognitive functions and disease mechanisms. He combines computational modeling with experimental approaches including optogenetics to investigate cortical dynamics. As Director of Education for the Institute for Mathematics, Physics and Astronomy, he oversees academic programs while maintaining active research in: Computational modeling of cortical circuits Oscillation mechanisms in neural coding Data sharing policies for neuroscience Information transfer between brain areas His recent publications reflect advances in neurotechnology development, thalamocortical connectivity analysis, and novel methodologies for neural data interpretation.

Sarah F. Muldoonمشاهده پروفایل

دانشیار

• Network Neuroscience
• Complex Systems
• Computational Neuroscience
• +۶ مورد دیگر

Sarah F. Muldoon is an Associate Professor in the Department of Mathematics at the University at Buffalo, SUNY. Her research focuses on network neuroscience and complex systems, integrating tools from mathematics, physics, and computational biology. Education: PhD in Physics, University of Michigan (2009) Her research explores network organization in brain function, particularly in health and pathological conditions like epilepsy. Key areas include: Development of novel network statistics (e.g., small-world propensity, multilayer analysis) Computational modeling of brain dynamics and state transitions Experimental data analysis across neuronal networks, ECoG, and fMRI Software tools for seizure detection and community structure quantification She leads a multidisciplinary group affiliated with the Computational and Data-Enabled Sciences (CDES) Program and Neuroscience Program at UB. Her work bridges theoretical and applied network science, with recent publications examining brain states, pandemic modeling, and personalized network diagnostics.

• Neuroscience
• Biophysics
• Mathematical Modeling
• +۴ مورد دیگر

Associate Professor Sveta Postnova is affiliated with the School of Physics at The University of Sydney, leading the Circadian Physics and Sleep Dynamics Group. She holds roles in the Sydney Nano Institute, Brain and Mind Centre, and Charles Perkins Centre. Her work integrates physics, mathematics, and data science to model brain dynamics, with a focus on sleep-wake cycles, circadian rhythms, and their interactions with cognition and health. Research interests include understanding how brain-body-environment interactions influence health, with applications in disease prevention and health monitoring. Recent work addresses sleep regularity's impact on dementia and multimodal lifestyle interventions for mortality reduction. She has developed a smartphone app (SleepSync) for defense personnel's sleep management. Grants: 2024: Strategies to mitigate jetlag for ultra-long flights (ARC Linkage Project) 2024: Biophysics of the brain's waste disposal system (ARC Discovery Project) 2022: Qantas Health Wellbeing Project Support (Charles Perkins Centre) Her research emphasizes translational outcomes, bridging theoretical models with real-world health solutions.

Javier Orlandiمشاهده پروفایل

استادیار

• Neuroscience
• Complexity Science
• Statistical Physics
• +۵ مورد دیگر

Javier Orlandi is an Assistant Professor in the Department of Physics and Astronomy at the University of Calgary, where he leads the Complex Neural Systems Lab as a Canada Research Chair. His research bridges systems neuroscience, complexity science, and statistical physics, focusing on understanding distributed coding principles in the brain and their impact on perception and learning. He employs computational and experimental approaches, including large-scale calcium imaging and optogenetic manipulation, in collaboration with institutions such as the Hotchkiss Brain Institute and the Computational Neuroscience Platform. Orlandi earned his Ph.D. in Physics from the University of Barcelona (2015), studying spontaneous activity in neuronal cultures. Subsequent postdoctoral research included work at the University of Barcelona (2015–2016) on Huntington’s disease, followed by the University of Calgary (2016–2019) and RIKEN Center for Brain Science in Japan (2019–2022), where he explored cortical processing during decision-making. His research has addressed criticality in neural systems, network inference, and the impact of genetic mutations on brain activity. Key areas of interest include self-organized criticality, neuro-glia communication, and the development of tools like NETCAL for analyzing calcium imaging data. Orlandi has organized challenges to advance connectomics and holds the Eyes High Postdoctoral Fellowship and Canada Research Chair awards. His work integrates theoretical models with experimental data to uncover fundamental principles of neural computation. Affiliations: Complexity Science Group, Hotchkiss Brain Institute, Computational Neuroscience Platform Education: Ph.D. in Physics (University of Barcelona, 2015) Grants: Canada Research Chair, Eyes High Postdoctoral Fellowship Labs: Complex Neural Systems Lab at University of Calgary

Martin A. Vinckمشاهده پروفایل

استاد

• Computational Neuroscience
• Systems Neuroscience
• Neural Coding
• +۱۰ مورد دیگر

Prof. Dr. Martin Vinck is a Professor at the Donders Centre for Neuroscience in the Department of Neurophysics , Radboud University. He is also a Research Group Leader at the Ernst Strüngmann Institute for Neuroscience and a faculty member at the International Max Planck Research School for Neural Circuits . Current affiliations: Radboud University, ESI Frankfurt, Max Planck Research School Positions: Professor, Research Group Leader, Review Editor for eLife Research Interests span computational and systems neuroscience, focusing on predictive processing in biological and artificial neural networks. His lab investigates: How distinct excitatory/inhibitory neurons regulate plasticity and flexible information processing Neural ensemble coding via spatio-temporal patterns and spike sequences Self-supervised learning mechanisms using spatial/temporal predictions Gamma oscillations, synchronization, and their role in visual encoding Scientific Contributions include developing algorithms for high-dimensional neural data analysis, co-supervising key studies on interneuron dynamics, and pioneering work on predictive coding in V1. His grants include the ERC Starting Grant (2019) and VIDI Grant (2024) . Lab Members include PhD students Jinke Liu, Jahan Esfandiarii, Athanasia Tzanou and alumni Irene Onorato, Marius Schneider, Ana Clara Silveira Broggini . He actively promotes open science , develops the Spike Toolbox , and reviews for journals like Neuron, eLife, PLoS Computational Biology .

Tobias Moserمشاهده پروفایل

استاد

• Auditory Neuroscience
• Synaptic Physiology
• Audiology
• +۳ مورد دیگر

Prof. Dr. Tobias Moser is a Professor of Auditory Neuroscience and Director of the Institute for Auditory Neuroscience at the University Medical Center Göttingen. He leads the InnerEarLab and holds roles as spokesperson for the Multiscale BioImaging Cluster of Excellence (MBExC) and the Else Kröner Fresenius Center for Optogenetic Therapies. His work integrates molecular, physiological, and clinical approaches to auditory research. Education: MD from the University of Jena (1995), followed by postdoctoral work at the Max Planck Institute for Biophysical Chemistry. He has held leadership positions at multiple Max Planck Institutes and the German Primate Center (DPZ). Research Interests: Molecular anatomy and physiology of auditory synapses, synaptic pathophysiology, optogenetic therapies for hearing restoration, and gene replacement therapy. His group combines patch-clamp electrophysiology, super-resolution microscopy (e.g., 3D-MINFLUX), and biophysical modeling to study sound encoding and synaptic dysfunction. Recent Work Trends: Focus on hair cell ribbon synapse mechanisms, optogenetic cochlear implants, and the molecular basis of auditory synaptopathy. Collaborations include the Stefan Hell lab for nanoscale imaging and Fred Wolf’s theoretical neurophysics group. Grants & Labs: Funded by DFG (SFB 889/1690), Max Planck Society, and EU initiatives. Affiliated with labs at DPZ and the MPI for Multidisciplinary Sciences. Active in training through IMPRS programs in Neurosciences and Molecular Medicine.