جست‌وجوی استاد و پژوهشگر

Jelmer Borstمشاهده پروفایل

دانشیار

• Computational Cognitive Neuroscience
• Neuroimaging Analysis
• Cognitive Modeling
• +۵ مورد دیگر

Prof. Jelmer Borst is an Associate Professor in Computational Cognitive Neuroscience at the University of Groningen's Faculty of Science and Engineering, affiliated with the Artificial Intelligence department within the Bernoulli Institute. His research focuses on integrating computational models with neuroimaging data to understand cognitive processes like multitasking, working memory, and decision-making. He advises three PhD candidates and collaborates internationally on projects involving EEG/fMRI analysis and cognitive modeling frameworks such as ACT-R and Nengo. Research Interests: Neuroimaging analysis methods, cognitive bottlenecks in multitasking, memory retrieval localization, and adaptive learning systems. Key Projects: Developed the PREDICTOR tool for semi-automated driving response timing, and advanced models linking symbolic process stages to brain activity via MEG/EEG. Recent work includes large-scale evaluations of adaptive learning systems and interventions to mitigate mind-wandering in driving scenarios. He has received the Allen Newell Best Student-led Paper Award (2021) for contributions to cold-start adaptive learning research. His research group maintains active collaborations on datasets involving working memory, decision-making, and cognitive architecture validation through neuroimaging experiments. He also contributes to open-source tools for cognitive modeling and neuroimaging analysis.

Melika Payvandمشاهده پروفایل

استادیار

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

Melika Payvand is an Assistant Professor at the Institute of Neuroinformatics, University of Zurich and ETH Zurich, leading the Emerging Intelligent Substrates lab. She holds MSc and PhD degrees in Electrical and Computer Engineering from the University of California, Santa Barbara (2012 and 2016). Her research focuses on understanding natural intelligence and translating its principles into efficient artificial intelligence systems, particularly exploring hierarchical structures and memristive devices to reduce AI operational costs. She received the 2023 Swiss National Science Foundation Starting Grant and is actively involved in neuromorphic initiatives, including co-coordinating the NEUROTECH project and co-chairing the International Conference on Neuromorphic Systems (ICONS). Her work bridges neuroscience and engineering, emphasizing neuromorphic computing’s potential for scalable and energy-efficient AI. Key contributions include developing the Neurobench benchmarking framework and advancing 3D integration for neuromorphic systems. She also chairs the Neural Systems and Applications committee of the IEEE Circuits and Systems Society, reflecting her leadership in the field. Research interests span neuromorphic architectures, memristive technologies, and spiking neural networks. She has pioneered studies on temporal hierarchy, in-memory computing, and hardware-aware training methods. Her lab’s interdisciplinary approach integrates circuit design, machine learning, and neurobiology to create next-generation intelligent systems.

Melissa Kelleyمشاهده پروفایل

استادیار

• Neurodevelopmental Disorders
• Autism Spectrum Disorder
• Attention-Deficit/Hyperactivity Disorder (ADHD)
• +۳ مورد دیگر

Melissa Kelley is an Assistant Professor at Kingston Health Sciences Centre. Her research focuses on neurodevelopmental disorders, particularly autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and their intersections with mental health. She employs neuroimaging techniques and transdiagnostic approaches to explore phenotypic and neurobiological subtypes, sensory processing, and developmental trajectories in neurodivergent populations. Her work emphasizes understanding socio-cognitive and self-regulatory mechanisms influencing adaptive behavior, as well as the impact of environmental factors such as screen time and school context on mental health outcomes. Recent studies include subgroup classification using structural MRI, precision health models for medication management, and longitudinal analyses of depressive symptoms in autistic youth. Dr. Kelley’s research also addresses equity considerations in clinical interventions and explores pandemic-related mental health trends in neurodivergent children and families. She collaborates internationally, leveraging multi-cohort datasets to advance diagnostic and treatment strategies for neurodevelopmental conditions.

• Neuroscience
• Neuroimmunology
• Cellular Neuroscience
• +۴ مورد دیگر

Christopher A. Baker is an Associate Research Scientist at Yale School of Medicine, part of Yale University. His research focuses on understanding neural circuitry, ion channel physiology, and neuroimmune interactions in health and disease. He holds a PhD in Neuroscience from Yale University (2002) and a BS in Psychology from Bowling Green State University (1994). Dr. Baker's work combines optogenetic tools, live-cell imaging, and molecular biology to investigate mechanisms underlying pain, neurodegeneration, and long-term viral effects on the nervous system. Research Interests: Dr. Baker’s studies bridge cellular neuroscience with systems-level approaches. Key areas include: Optogenetic manipulation of neural circuits Role of Nav/Kv ion channels in pain signaling Neuroinflammatory responses in prion diseases and long-COVID Autoantibody-mediated neurotoxicity mechanisms Publications Highlight: His 2024 work in Nature Protocols describes real-time imaging techniques for axonal membrane protein dynamics. Recent studies in PNAS and Neuron explore inflammatory modulation of pain pathways and optimized voltage indicators. Early foundational work on Creutzfeldt-Jakob disease microglial profiles remains highly cited. Collaborations: Regular co-authorship with Stephen Waxman (Nav channel expert), Sulayman Dib-Hajj, and Akiko Iwasaki (viral immunity). Labs/Teams: Active in Yale’s Neuroscience department and affiliated with the Center for Neuroscience and Regeneration Research (CNRR).

Samuel Norman-Haignereمشاهده پروفایل

استادیار

• Computational Neuroscience
• Auditory Processing
• Neural Coding
• +۴ مورد دیگر

Samuel Norman-Haignere is an Assistant Professor holding joint appointments in the Department of Biostatistics and Computational Biology, Department of Neuroscience, and Department of Biomedical Engineering at the University of Rochester's School of Medicine and Dentistry (SMD). His research focuses on the computational and experimental mechanisms underlying human auditory perception, particularly speech and music processing. He earned his PhD in Neuroscience from MIT (2015) and completed postdoctoral training at MIT, École Normale Supérieure, and Columbia University. Education: BA in Cognitive Science from Yale University (2010), PhD in Neuroscience from MIT (2015). Postdoctoral positions included work with Josh McDermott/Nancy Kanwisher (MIT, 2015-2017), Shihab Shamma (École Normale Supérieure, 2017-2018), and Nima Mesgarani (Columbia, 2018-2021). Research interests emphasize developing statistical methods to analyze high-dimensional neuroimaging data and modeling neural responses in auditory cortex. His lab uses fMRI, intracranial recordings, and computational approaches to study hierarchical auditory processing and cross-species comparisons. Key findings include identifying speech/music-selective neural populations and demonstrating music-sensitive cortex independent of musical training. Selected awards include the NSF Graduate Research Fellowship (2010-2015) and multiple poster awards. Collaborations span neurology, neurosurgery, and animal physiology labs to bridge computational models with experimental insights. Labs/Teams: Computational Neuroscience of Audition Lab, affiliated with the Del Monte Institute for Neuroscience and UR Medicine's CABIN imaging facility. Active in training students through UR's Neurobiology & Anatomy and Neuroscience PhD programs.

Timothy W. Secombمشاهده پروفایل

استاد

• Theoretical Physiology
• Microcirculation
• Computational Modeling
• +۱۲ مورد دیگر

Timothy W. Secomb is a Professor at the University of Arizona with joint appointments in the Department of Physiology, Department of Mathematics, and the interdisciplinary programs in Applied Mathematics and Physiological Sciences. He is also affiliated with the BIO5 Institute and the Department of Biomedical Engineering, reflecting his highly interdisciplinary research approach. His research focuses on theoretical and computational modeling of physiological systems, particularly the microcirculation. Key areas include blood flow mechanics in microvessels, oxygen and nutrient transport to tissues, structural adaptation and angiogenesis in vascular networks, and regulation of blood flow through metabolic and mechanical feedback. His work integrates applied mathematics, physiology, and biomedical engineering to understand fundamental mechanisms in health and disease. The recent publications highlight a consistent focus on microvascular oxygen transport, neurovascular coupling, tumor angiogenesis, and computational hemodynamics. The modeling spans from cellular-level processes like red blood cell mechanics and ion diffusion to organ-level systems such as the cerebral cortex and pulmonary circulation. A strong trend is evident in using realistic 3D vascular geometries and developing fast, low-order models for complex physiological systems. Dr. Secomb has made significant contributions to understanding flow resistance, capillary perfusion, and the impact of vascular structure on tissue oxygenation. His models are instrumental in studying hypoxia in tumors and optimizing cancer therapies like thermoradiotherapy and antibody-drug conjugates. BSc in Mathematics, University of Melbourne (1975) MSc in Mathematics, University of Melbourne (1976) PhD in Applied Mathematics, University of Cambridge (1979) Post-Doctoral Training, Columbia University (1981) He has mentored students and researchers in mathematical physiology and continues to lead an active research program. His lab employs a hybrid discrete-continuum modeling framework and collaborates with experimental groups to validate theoretical predictions. Future work is likely to extend into immune-cell trafficking, multi-scale modeling of organ systems, and personalized models for precision medicine applications.

Enrico Dall'Araمشاهده پروفایل

استاد

• Biomechanics
• Computational Modeling in Medicine
• Musculoskeletal Tissue Mechanics
• +۶ مورد دیگر

Professor Enrico Dall'Ara is a leading figure in musculoskeletal biomechanics at the University of Sheffield , where he holds the Professorship of Musculoskeletal Biomechanics since 2024. He directs the Skelet.Al Laboratories , serves as Research Director for Insigneo's Computational Modelling in Medicine theme, and leads the Non-Clinical Task Force in the Avicenna Alliance. Education: PhD in Biomechanics (Vienna), MSc Mechanical Engineering (Bologna) Current Roles: President of European Society of Biomechanics, Deputy Head of IMSB Research Group Research Focus: Subject-specific computational models for bone strength prediction, fracture risk assessment, and mechanobiological studies in preclinical/clinical settings. Key applications include osteoporosis , osteoarthritis , and vertebral metastases , integrating imaging , experimental , and computational methods . Recent Article Trends: His computational work spans finite element modeling , digital volume correlation , machine learning in segmentation , and multi-scale adaptation studies , validated through microCT , synchrotron tomography , and MR imaging across mouse models and human specimens . Scientific Awards & Leadership: President, European Society of Biomechanics (2024) Director, Skelet.Al Laboratories (2020) Research Director, Insigneo (2021) Council Member, Avicenna Alliance (2023) Editorial roles in Journal of Mechanical Behaviour and Frontiers in Bioengineering Advising & Grants: Mentors 14+ PhD students across international institutions. Secured £2.6M+ in grants including EPSRC Virtual Human Twin (£1.74M), Horizon Europe METASTRA (£773k), and EUROSTARS projects. Collaborates with EPSRC, Horizon2020, and AO Spine.

Jean Philippe Thiviergeمشاهده پروفایل

استاد

• Neural Dynamics
• Neurosciences
• Systems Biology
• +۵ مورد دیگر

Jean Philippe Thivierge is a Professor in the Department of Psychology at the University of Ottawa, Faculty of Social Sciences. His research integrates experimental and computational approaches to study the dynamics of neuronal networks underlying memory and cognition. Research Interests: Dr. Thivierge's work centers on neural dynamics , neurosciences , and systems biology . He investigates how large-scale neuronal populations encode and maintain memories by combining multielectrode recordings with biologically realistic simulations. His lab explores principles of network organization across spatial and temporal scales, focusing on phenomena like neuronal avalanches, attractor dynamics, and functional connectivity. The analysis of his recent publications reveals a strong emphasis on computational modeling , statistical analysis of neural data , and network-level neuroscience . His work bridges experimental findings with theoretical frameworks, particularly in understanding scale-free dynamics, criticality, and information processing in cortical and hippocampal circuits. Scientific Contributions: While specific awards are not listed, his publication record in high-impact journals such as Neuron , PLoS Computational Biology , and Journal of Neurophysiology reflects significant contributions to computational and systems neuroscience. Advising and Research: Dr. Thivierge mentors several trainees, including graduate students and postdoctoral fellows, many of whom are co-authors on his publications. His lab employs multielectrode array technology and large-scale neural simulations to probe the mechanisms of memory formation and network stability. Although grant details are not provided, his sustained research output suggests active funding support. Laboratory Focus: The Thivierge Lab operates at the intersection of experimental neurophysiology and computational modeling, utilizing both in vitro recordings and in silico simulations to test hypotheses about brain network function. The lab's approach enables rigorous testing of biophysical mechanisms linking synaptic properties to emergent network behaviors.

• Diffusion MRI
• Neuroplasticity
• Brain Connectivity
• +۵ مورد دیگر

Dr. Alfred Anwander is a Senior Researcher in the Department of Neuropsychology at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig, Germany. His work focuses on diffusion MRI as a biomarker for brain development and plasticity, particularly in language-related pathways and neuroplasticity mechanisms during second language acquisition. He has held research positions at the institute since 2000, contributing to projects such as the DFG-funded "Human microstructural connectomics" and "Dynamic Connectome" initiatives. Education 1991–1996: Diploma in Electrical Engineering from the University of Karlsruhe 1995–2000: MSc (DEA) and PhD in Signal and Image Processing from INSA Lyon (France), with a thesis on model-based color image segmentation. Research Interests Anwander’s research integrates advanced neuroimaging techniques to study structural connectivity in the human brain. Key areas include: Diffusion MRI applications in developmental neuroscience and neuroplasticity Language-related white matter pathways Evolutionary comparisons of brain connectivity in primates Methodological advancements in high-resolution MRI and tractography Grants & Projects DFG project "Human microstructural connectomics: Computational modelling and validation with histology and CLARITY (MiCo-MRI)" DFG project "The dynamic connectome underlying language in the brain (DynaCon)" Evolution of Brain Connectivity (EBC) initiative Labs & Teams He collaborates within the institute’s Cortical Networks and Language Research groups, focusing on interdisciplinary approaches to connectomics and neuroimaging technology development.

Sonja Grünمشاهده پروفایل

استاد

• Neuroscience
• Computational Neuroscience
• Neural Networks
• +۳ مورد دیگر

Prof. Sonja Grün is a Professor and Director of the Computational and Systems Neuroscience division (IAS-6) and the JARA-Institute Brain structure-function relationships (INM-10) at Forschungszentrum Jülich. She leads the Statistical Neuroscience research group, focusing on cell assemblies, dynamical neuronal interactions in cortex, higher-order correlation analysis, and reproducible workflows. Her work bridges experimental and computational approaches to understand neural coding and network dynamics. Key contributions include methodologies for spike pattern detection (e.g., SPADE) and tools for data curation (UnitRefine). She actively develops neuroinformatics standards (e.g., Neuroelectrophysiology Analysis Ontology) and promotes reproducible research through provenance tracking initiatives like NFDI-Neuro. Her research spans motor cortex activity, visual processing, and model validation frameworks. Research interests emphasize spatio-temporal spike patterns, cortical network models, and artifact detection in high-density recordings. She collaborates on projects integrating electrophysiological data with computational simulations (e.g., NEST) and brain wave analysis (Cobrawap). Current efforts address challenges in data sharing, artifact removal, and scalable analysis pipelines for heterogeneous datasets.

Michael Denkerمشاهده پروفایل

پژوهشگر

• Neuroscience
• Reproducible Science
• Data Analytics
• +۴ مورد دیگر

Dr. Michael Denker is a Team Leader in the Computational and Systems Neuroscience department at the Institute for Advanced Simulation (IAS-6) , Forschungszentrum Jülich. His research focuses on data analytics for electrophysiology and optophysiology in behavioral neuroscience, emphasizing reproducible science practices and collaborative workflows. He leads the Data Science of Electro- and Optophysiology in Behavioural Neuroscience team, developing tools like Elephant , Neo , and Cobrawap to standardize data analysis across neuroscience experiments. His work addresses challenges in metadata management, provenance tracking, and interoperability between experimental and simulation datasets. Key contributions include the Neuroelectrophysiology Analysis Ontology (NEAO) for structured data sharing and frameworks for validating neural network simulations. Denker actively promotes open science through initiatives like the German National Research Data Infrastructure (NFDI-Neuro) and collaborates with the Human Brain Project (HBP) on EBRAINS services. His research integrates multi-scale data from electrophysiological recordings and computational models to study cortical waves and spike patterns, particularly in rodent and primate systems.

Rebecca Williamsمشاهده پروفایل

مدرس

• Functional Magnetic Resonance Imaging
• Structural Magnetic Resonance Imaging
• Cognition and Memory
• +۷ مورد دیگر

Dr. Rebecca Williams is a Lecturer in the School of Science and Technology at the University of New England (UNE), Australia. She joined UNE in 2024, bringing extensive expertise in functional and structural magnetic resonance imaging (MRI) and its applications in cognitive neuroscience and brain health. Her research investigates brain ageing, cognition, memory, anxiety, depression, and neurological disorders such as stroke and mild cognitive impairment. Ph.D. in Neuroscience – The University of Queensland Graduate Diploma in Magnetic Resonance Technology – The University of Queensland Bachelor of Psychological Science (Honours) – The University of Queensland Dr. Williams' research is centered on advancing neuroimaging techniques, particularly fMRI, to understand both healthy and pathological brain ageing. Her work integrates physiological measurements, machine learning, and advanced MRI methodologies to improve the accuracy and clinical relevance of brain imaging. She explores how cerebrovascular function, respiratory effects, and neural oscillations contribute to brain health and disease progression. Her recent publications highlight a strong focus on BOLD-fMRI signal interpretation, physiological confound correction, and the use of machine learning to extract meaningful data from neuroimaging. Themes across her work include neurovascular coupling, brain ageing, psychiatric disorders, and neurodegenerative conditions such as Alzheimer’s disease. She also contributes to innovative applications of MRI in space medicine and pediatric populations. Dr. Williams is a member of the following professional organizations: International Society for Magnetic Resonance in Medicine Organization for Human Brain Mapping She has previously held a Postdoctoral Research Fellowship at the University of Calgary, Canada, and served as a Lecturer in Psychology at Charles Darwin University. At UNE, she teaches in the areas of neurobiology of anxiety, research methods for neuroscience, and brain mapping with MRI. While no formal advisees are listed, her active research program suggests potential future supervision of graduate students. She does not currently hold any mentioned scientific awards or grants, though her publication record indicates ongoing collaborative and externally funded research. Dr. Williams is involved in interdisciplinary research teams focused on neuroimaging innovation, particularly in the development and validation of MRI-based biomarkers for brain health. Her work often involves collaboration with experts in neurology, psychiatry, biomedical engineering, and data science, contributing to both clinical and space-based applications of brain imaging.

Sarah Hughesمشاهده پروفایل

استاد مدعو

• Epithelial Cell Polarity and Adhesion
• Neural Stem Cells
• Regulation of Proliferation and Differentiation
• +۷ مورد دیگر

Sarah Hughes is an Adjunct Professor in the Department of Medical Genetics at the University of Alberta. Her research focuses on the molecular mechanisms linking cell polarity, proliferation, and differentiation in epithelial cells and neural stem cells, with implications for developmental disorders and cancers like Neurofibromatosis Type 2 and Atypical Rhabdoid Tumours. Education: Ph.D., University of Toronto Using Drosophila melanogaster as a genetic model, she investigates post-transcriptional regulation, tumour suppressor proteins, and signaling pathways. Her work employs molecular biology, proteomics, and advanced microscopy. Recent publications highlight studies on chromatin remodeling in neural stem cells, lipid droplet dynamics, and Merlin/Moesin regulation in cell polarity. Her lab members include Post-doctoral Fellow Sophie Keegan and Graduate Students Nguyen Cai and Maryam Khandani.

Brian N. Lundstromمشاهده پروفایل

دانشیار

• Neuronal Excitability
• Computational Neuroscience
• Neurostimulation
• +۳ مورد دیگر

Brian N. Lundstrom is an Associate Professor of Neurology and Biophysics at Mayo Clinic College of Medicine in Rochester, Minnesota. His research focuses on neuronal excitability, brain stimulation techniques, and computational modeling to improve neurological care for disorders like epilepsy. Education: MD/PhD from University of Washington, postdoctoral work at Instituto de Neurociencias de Alicante, and clinical training at Mayo Clinic. Dr. Lundstrom investigates neural adaptation and develops EEG/MEG biomarkers to guide epilepsy therapy. His lab combines invasive and noninvasive brain stimulation with multiscale neurophysiological analysis to optimize treatment protocols. Recent work spans neurostimulation for depression , deep brain stimulation targeting thalamic nuclei , and low-frequency stimulation approaches . These studies highlight his expertise in bridging computational neuroscience with clinical neurology. Certifications: Clinical Neurophysiology, Epilepsy, and Neurology by the American Board of Psychiatry and Neurology.

Linda Van Aelstمشاهده پروفایل

استاد

• Cancer Research
• Neuroscience
• Molecular Biology
• +۳ مورد دیگر

Linda Van Aelst is a Professor at Cold Spring Harbor Laboratory, holding the Harold and Florence & Ethel McNeill Professorship of Cancer Research. Her work bridges cancer biology and neuroscience, focusing on small GTPases like Ras and Rho in disease mechanisms. Education: PhD in Molecular Biology from Catholic University of Leuven (1991), BS in Biology (1985) Her research explores how mutations in genes like OPHN1 and DOCK7 disrupt synaptic plasticity and cortical neurogenesis, contributing to neurodevelopmental disorders and cancers. Recent work links chronic stress to metastasis via immune microenvironment changes. Her 15 most recent publications span Alzheimer's disease, neurofibromatosis, glioblastoma metabolism, and stress-cancer interactions, emphasizing GTPase signaling and synaptic regulation. Scientific Awards: CSHL WISE Mentorship, National Alliance for Autism Research/NARSAD, Dana Foundation, Sidney Kimmel Foundation, V Foundation Awards, McNeill Endowed Professorship Van Aelst mentors graduate students and postdoctoral fellows, contributing to understanding tumor suppressors, neuronal migration, and therapeutic strategies for NF1 and fragile X syndrome.