جستجوی استاد راهنمای دانشگاهی

Kent-Andre Mardalمشاهده پروفایل

استاد

• Computational Mechanics
• Biomechanical Applications in Medicine
• Brain Clearance During Sleep
• +۵ مورد دیگر

Kent-Andre Mardal is a Professor at the Department of Mathematics , University of Oslo . He specializes in computational mechanics with a strong focus on biomechanical applications in medicine , particularly in modeling brain clearance mechanisms during sleep. His work integrates multi-physics modeling , fluid-structure interaction , and poroelastic couplings to advance understanding of the glymphatic system and cerebrospinal fluid dynamics. Education: PhD (2002) – Simula Research Laboratory Research Interests: Mardal's research spans a wide range of disciplines including: Computational Mechanics – developing robust numerical algorithms for complex physical systems Biomechanical Applications – particularly in neuroscience and medical imaging Brain Clearance During Sleep – modeling the glymphatic system and CSF flow dynamics Multi-Physics Modeling – integrating fluid dynamics, elasticity, and neural networks Finite Element Methods – for accurate and efficient simulations Neural Networks in Scientific Computing – exploring physics-informed neural networks Research Trends from Publications: Mardal's recent publications (2022–2025) demonstrate a clear focus on brain fluid dynamics , particularly the glymphatic system , CSF circulation , and neurodegenerative disease modeling . He employs advanced numerical techniques such as isogeometric analysis , physics-informed neural networks , and parameter-robust preconditioning to solve complex multi-physics problems. His work bridges medical imaging (MRI) with computational modeling to provide insights into brain clearance mechanisms and their impairment in diseases like Alzheimer's. Scientific Awards: No specific awards are mentioned in the provided text. Grants and Projects: Currently, Mardal is the Principal Investigator (PI) of three active research projects: Alzheimer's Physics – exploring the role of fluid dynamics in neurodegeneration Scientific Machine Learning – advancing numerical methods with AI Computational Hydrology – modeling subsurface fluid flow Affiliations and Teams: Mardal was previously a group leader at the Centre of Excellence “Biomedical Computing” at the Simula Research Laboratory. He has authored over 100 papers and several books, and his research homepage is available at https://kent-and.github.io/ .

Justin Jeongمشاهده پروفایل

استاد

• Neuroimaging
• Diffusion MRI Tractography
• Pediatric Epilepsy Surgery
• +۴ مورد دیگر

Justin Jeong is a Professor of Pediatrics and Neurology at Wayne State University School of Medicine , where he serves as a principal investigator in the Translational Imaging Laboratory. With a background in Biomedical Engineering and Electrical Engineering from University of Southern California, Dr. Jeong combines technical expertise with clinical applications to improve outcomes for pediatric neurological patients. B.S. Biomedical Engineering - Yonsei University M.S. Electrical Engineering - University of Southern California Ph.D. Biomedical Engineering - University of Southern California His research focuses on advanced diffusion MRI tractography and multimodal neuroimaging to identify structural/functional biomarkers for epilepsy, developmental delays, and neurovascular disorders. Current NIH-funded work develops: Deep learning-based DWI methods Dynamic tractography with stereotopic rendering Integration with PET and electrocorticography Publications across Neuroimage , Epilepsia , and Clinical Neurophysiology demonstrate expertise in: Neural activation propagation High-resolution connectome mapping Postoperative brain reorganization Developmental neuroimaging Machine learning applications in MRI Neonatal brain abnormality detection Key collaborations include Eishi Asano , Csaba Juhasz , and Harry Chugani in developing clinical translation of these imaging methodologies.

Alberto De Lucaمشاهده پروفایل

استادیار

• Diffusion MRI
• Neurological Diseases
• Brain Connectivity
• +۳ مورد دیگر

Alberto De Luca is an Assistant Professor at the Image Sciences Institute, Division Imaging & Oncology, University Medical Center Utrecht. He holds a BSc in Biomedical Engineering (2011), MSc in Bioengineering (2013), and PhD (2017) from the University of Padova, Italy, where his thesis focused on non-Gaussian diffusion in the brain and skeletal muscle. His research specializes in diffusion MRI methodologies for neurological diseases and cancer, with key interests including: Fiber-specific quantification in grey/white matter Multi-center MRI data harmonization Physiological parameter estimation via inverse methods Response prediction modeling He leads projects in cerebral small vessel disease and pediatric oncology, utilizing advanced 7T MRI and AI techniques. Recent publications (2025) demonstrate strong focus on: AI-driven lesion-symptom mapping in vascular cognitive disorders Diffusion MRI harmonization across research sites Advanced tractography validation frameworks Pediatric cancer imaging biomarkers He contributes to the Translational Neuroimaging Group and International Society for Tractography, with external collaborations including Erasmus MC (Frontotemporal dementia research) and Hogeschool Utrecht (guest lecturing on brain networks).

Koen Vinckenمشاهده پروفایل

دانشیار

• Medical Image Analysis
• Medical Imaging
• Computer Science in Medicine
• +۲ مورد دیگر

Koen Vincken is an Associate Professor at the Image Sciences Institute (UMC Utrecht), a research unit of Utrecht University focused on advancing medical imaging technologies. He holds an MSc in Computer Science from Delft University of Technology (1989) and a PhD from Utrecht University (1995) for his thesis "Probabilistic Multiscale Image Segmentation by the Hyperstack". His career spans software development for clinical applications in radiology, neurology, and orthopedics, including the digital reconstruction of ancient skeletal remains like the Dutch Neolithic skull "Trijntje". Vincken's research integrates computer science with medical imaging, emphasizing: Algorithm development for image segmentation and analysis High-precision acquisition methods for brain cancer diagnostics AI-driven solutions for radiology and pathology workflows Quantitative imaging biomarkers for neurodegenerative and orthopedic disorders His recent publications (2020-2024) demonstrate cross-disciplinary work in surgical imaging, neuropathology, and medical education technology, reflecting a focus on translating computational innovations into clinical practice. No scientific awards, grants, or supervised students are mentioned in the source material. He leads projects within the Image Sciences Institute research group, which develops analytical methods for brain cancer, stroke, and image-guided interventions.

Dieter Baurechtمشاهده پروفایل

دانشیار

• Spectroscopy
• Biophysics
• Biosensors
• +۳ مورد دیگر

Dieter Baurecht is an Associate Professor at the Institute of Physical Chemistry , University of Vienna. His research focuses on Advanced FTIR Spectroscopy , with expertise in Time-Resolved FTIR , Modulation Spectroscopy , and Raman Microscopy . He investigates thin layers, multilayer assemblies, and biological interfaces using specialized Nanostructure Research Equipment . Academic Roles : Associate Professor (since 2005), Deputy Head of Nanostructure Research, IT Officer at Physical Chemistry Institute Teaching : Courses in Physical Chemistry , Quantum Theory , Mathematics for Chemists , and Spectroscopic Lab Work Research Focus Dr. Baurecht’s work bridges Spectroscopy , Biophysics , and Biosensor Development . He leads projects like Mathematical Models for BioFETs (FWF P20871-N13) and ASEA Uninet (2009-2023). His methods include: Quantitative FTIR-ATR for surface layers Raman microscopy for polymer and bacterial analysis Step-Scan and Rapid-Scan FTIR instrumentation Collaborations His research spans institutions such as: University of Vienna Nano Research Austrian Institute of Technology BOKU Vienna (Biologically Inspired Materials) University of Vienna Drug Delivery Platform International partners in Thailand (Ubon Ratchathani, Chiang Mai) Instrumentation BRUKER IFS-66 FTIR with Step-Scan BRUKER Tensor-37 FTIR Shared equipment at Vienna Nano Research Center

• Biophotonics
• Cancer Medicine
• Medical Imaging
• +۳ مورد دیگر

Katie Hanna is an Advanced Research Fellow at the Institute of Medical Sciences, University of Aberdeen, affiliated with the School of Medicine, Medical Sciences and Nutrition. Her research focuses on biomedical applications of advanced spectroscopic techniques and imaging technologies. Research Interests: Specializing in Biophotonics for cancer diagnostics Machine learning integration in medical imaging Low-field magnetic resonance applications Raman spectroscopy for oral and breast cancer characterization Publications Trends: Recent work demonstrates interdisciplinary collaboration between biomedical engineering, oncology, and computational sciences, with emphasis on non-invasive diagnostic methods and personalized treatment approaches across her 2024-2025 publications. Education: PhD in Cancer Medicine (2023), University of Aberdeen BSc Hons in Anatomy (2018), University of Glasgow

Gregory Anthonyمشاهده پروفایل

استادیار

• Medical Physics
• Cardiovascular Imaging
• MRI
• +۳ مورد دیگر

Gregory Anthony, PhD, serves as an Assistant Professor in the Department of Radiology & Imaging Sciences at the Indiana University School of Medicine in Indianapolis. As a diagnostic imaging medical physicist, he specializes in cardiovascular imaging with expertise in MRI and CT technologies. His primary role involves developing and advancing the cardiovascular imaging program at IU through clinical research, technical support, and protocol optimization. Dr. Anthony is an integral member of the diagnostic physics team, providing essential expertise for radiology services while fulfilling educational responsibilities for medical physics and radiology trainees. Research Focus: Dr. Anthony's work centers on cardiovascular imaging physics , specifically advancing MRI and CT applications for cardiac diagnostics. His research focuses on improving image acquisition techniques, optimizing scanning protocols for vascular studies, and enhancing quantitative analysis methods in cardiovascular radiology. This work directly supports clinical innovation in cardiac imaging at Indiana University. Educational & Clinical Integration: Through his dual role in research and clinical service, Dr. Anthony bridges physics principles with practical radiology applications. He trains residents and medical physics students in imaging physics fundamentals while mentoring them in cardiovascular-specific applications. His contributions strengthen both the academic mission and clinical capabilities of the Radiology Department.

• Cardiovascular Diseases
• Medical Imaging
• Coronary Artery Disease
• +۵ مورد دیگر

Professor Juhani Knuuti serves as Professor and Director of the Turku PET Centre at the University of Turku, Finland. His research integrates cardiovascular medicine with advanced imaging science, focusing on coronary artery disease, heart failure, and metabolic disorders through noninvasive diagnostic techniques including PET, SPECT, MRI, CT, and echocardiography. His research program targets disease pathophysiology, novel therapy development, and imaging innovation with three key thrusts: vulnerable plaque characterization in coronary disease, cardiac remodeling processes, and multimodality/hybrid imaging integration. Recent work increasingly incorporates machine learning for complexity reduction in cardiovascular modeling while maintaining clinical interpretability. Organ-heart interaction studies in metabolic disease represent another growing focus area. Analysis of Professor Knuuti's 2025 publications reveals a strong emphasis on technical innovation in quantification methods (total-body perfusion, pulmonary blood flow), AI-driven diagnostic tools (plaque burden cut-offs, COME-CCT calculator), and translational tracer development ([18F]SYN2 dosimetry). His work bridges molecular imaging (e.g., CD206-targeted macrophage imaging) with clinical applications in elderly populations and acute coronary syndrome. Information regarding specific grant funding and student advising load was not available in source materials. However, his leadership of the Turku PET Centre and extensive collaborative network indicate active research programs with substantial infrastructure support. The Turku PET Centre operates as a comprehensive imaging research facility under Professor Knuuti's direction, featuring cutting-edge PET/CT technology and multidisciplinary teams. Current activities include tracer development, quantitative imaging protocol validation, and international consortium leadership (e.g., COME-CCT), with strong emphasis on translating technical advances into clinical cardiovascular practice.

Juho Joutsaمشاهده پروفایل

استاد

• Neurology
• Movement Disorders
• Neuroimaging
• +۴ مورد دیگر

Juho Joutsa serves as Professor of Neurology at the University of Turku and Chief Neurologist at Turku University Hospital since 2023, while chairing the Turku Brain and Mind Center. His academic journey includes progression from Adjunct Professor (2015) through Assistant and Associate Professor roles in Neuroimaging at the Turku Brain and Mind Center, alongside clinical specialization in Neurology (2020). Professor of Neurology, Clinical Neurosciences, University of Turku (2023-present) Chief Neurologist, Neurocenter, Turku University Hospital (2023-present) Chair, Turku Brain and Mind Center (current) Adjunct Professor, Department of Neurology, University of Turku (2015-present) Professor Joutsa's research focuses on elucidating neurobiological mechanisms of brain disorders through innovative lesion network mapping combined with advanced neuroimaging and neuromodulation techniques. His work spans neurological movement disorders (dystonia, tremor), addiction neuroscience, and epilepsy, with particular emphasis on translating circuit discoveries into therapeutic interventions. The laboratory employs a multimodal approach integrating causal brain lesion analysis, state-of-the-art MRI/PET/SPECT imaging, and brain stimulation methods (TMS, DBS, MRgFUS) to identify and modulate pathological brain networks. Recent publication trends reveal a strong focus on lesion-based circuit mapping across diverse neurological conditions. High-impact 2022-2025 papers in Nature Medicine, Brain, and Neurology demonstrate consistent methodological innovation in identifying disease-specific brain networks for movement disorders, stuttering, and addiction. The research shows increasing international collaboration and translational emphasis, with recent work directly informing neuromodulation treatment targets. As Lead Teacher in Neurology for the M.D. curriculum, Professor Joutsa integrates clinical expertise with research insights. His laboratory leverages the Turku PET Centre's exceptional resources including multiple PET/CT scanners and hybrid MRI/PET systems, facilitating cutting-edge multimodal studies. The laboratory maintains close operational ties with Turku University Hospital's clinical neurology and neurophysiology departments, enabling direct patient-researcher collaboration. The Brain Stimulation and Neuroimaging Laboratory (Turku Brainlab), established in 2018, operates within the Turku Brain and Mind Center with access to neuronavigated TMS, transcranial electrical stimulation, and comprehensive electrophysiology systems. This environment supports interdisciplinary research bridging clinical neurology, neuroscience, and engineering to develop novel diagnostic and therapeutic approaches for brain disorders.

Philippe Delachartreمشاهده پروفایل

استاد

• Medical Imaging
• Signal Processing
• Image Processing
• +۷ مورد دیگر

Philippe Delachartre is a Professor at INSA Lyon (University of Lyon) in the Department of Electrical Engineering and researcher at CREATIS (Center for Research and Applications in Image and Signal Processing). He obtained his MS (1990) and PhD (1994) in Signal and Image Processing from INSA Lyon, joining the faculty in 1995 as Associate Professor before being promoted to Professor. His research focuses on medical image processing including: Advanced signal processing for ultrasound and MRI Motion estimation and segmentation algorithms Hypercomplex signal theory applications Deep learning for medical image analysis Real-time data acquisition systems With 30+ years of experience, he's contributed to over 100 publications. Recent publications (2018-2025) show strong focus on: Deep learning applications in medical signal classification Advanced segmentation methods (phase-field, CNN) Mathematical frameworks using hyperquaternions 3D ultrasound analysis for neurology and dermatology Cardiac motion estimation algorithms Research grants include: Regional project on emboli classification with deep learning (€170k) ANR LabCom project on Doppler ultrasound (€300k) Dermis characterization contract with Institut Pierre Fabre (€45k) Prostate segmentation project (€21k) Image denoising research (€100k) He has supervised 9 PhD students and leads research activities at CREATIS laboratory focusing on innovative medical imaging solutions.

Tufve Nyholmمشاهده پروفایل

استاد

• Radiotherapy
• Medical Imaging
• Artificial Intelligence
• +۵ مورد دیگر

Tufve Nyholm serves as Professor in Radiation Physics at Umeå University with a joint appointment as Medical Physicist at the University Hospital of Northern Sweden. He holds the position of Head of Department within the Department of Diagnostics and Intervention, specifically leading the Section of Biomedical Engineering and Radiation Physics under Oncology. His work bridges clinical radiotherapy applications with advanced imaging research, operating from Location 10C at Norrlands Universitetssjukhus in Umeå. His primary research focuses on medical imaging modalities including Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET), with strong emphasis on prostate cancer applications. The research integrates artificial intelligence for image analysis, segmentation, and uncertainty estimation to optimize radiotherapy treatment planning. Key initiatives explore correlations between clinical imaging, histopathology, and molecular risk markers to enable personalized radiotherapy solutions. The work spans both technical development of AI tools and clinical validation studies through multi-disciplinary collaboration. Publication trends reveal consistent focus on AI-driven solutions for radiotherapy challenges, particularly in prostate and cervical cancers. Recent work emphasizes resource-efficient AI segmentation, MR-only radiotherapy protocols, and quantitative imaging biomarkers. The research demonstrates strong clinical translation with frequent co-authorship from oncologists, radiologists, and pathologists, reflecting integrated team science approaches. Nyholm leads the Tufve Nyholm Lab research group comprising associate professors, medical physicists, and doctoral students. Current projects include AI-based delineation in radiotherapy (2024-2026), quantitative MRI for individualized radiotherapy (2023), pediatric radiotherapy automation (2022-2024), and the PAMP prostate cancer study. The group receives external funding from the Swedish Cancer Society, Cancerforskningsfonden Norrland, Region Västerbotten, and Prostatacancerförbundet. The lab maintains extensive collaborations across Umeå University including Oncology (Karin Söderkvist, Camilla Thellenberg Karlsson, Björn Zackrisson), Pathology (Anders Bergh), Radiology (Sara Strandberg, Katrine Riklund), Urology (Andreas Josefsson), and Computer Science (Tommy Löfstedt, Polina Kurtser). This multi-disciplinary network enables comprehensive research from molecular markers to clinical implementation.

• Clinical Neurophysiology
• Neonatal EEG Monitoring
• Epilepsy Surgery
• +۳ مورد دیگر

Päivi Nevalainen serves as Supervisor in the Doctoral Programme Brain & Mind at the University of Helsinki's Faculty of Medicine. She holds a docentship in Physiology, Genetics and Preanalytics at Helsinki University Hospital (HUS) and conducts research at the BioMag Laboratory within the Department of Neurosciences, specializing in clinical neurophysiological applications for neonatal and pediatric populations. Her research centers on advanced neurophysiological monitoring techniques, particularly EEG and magnetoencephalography (MEG), for neonatal brain assessment. Key focus areas include developing automated EEG analysis tools (e.g., Brain State of the Newborn, Sleep State Trend) to predict outcomes in perinatal asphyxia and neonatal encephalopathy, investigating epilepsy biomarkers through high-frequency oscillation analysis, and optimizing epilepsy surgery using stereo-EEG. Her work integrates transcranial magnetic stimulation to study motor cortex function in children and adolescents, with strong emphasis on translating neurophysiological markers into clinical decision support systems. Analysis of her 60+ publications (2023-2025) reveals a consistent trajectory toward multimodal neurophysiological monitoring for precision neonatal care. Her recent work demonstrates increasing multicenter collaboration in epilepsy surgery research, with significant contributions to seizure onset zone localization methods and quantitative EEG-based outcome prediction in hypoxic-ischemic encephalopathy. The publications show methodological evolution from basic neurophysiological characterization toward clinically implementable algorithms. Dr. Nevalainen actively supervises doctoral candidates through the Brain & Mind programme and contributes to clinical neurophysiology standardization at BioMag Laboratory. Her research program involves close collaboration with Helsinki University Hospital's neonatal intensive care and epilepsy surgery units, though specific grant details are not publicly documented. She maintains leadership in developing biomagnetic measurement protocols for neonatal applications within the BioMag team.

Maureen Hoodمشاهده پروفایل

دانشیار

• Imaging Science
• Cardiac MRI
• MR Safety
• +۴ مورد دیگر

Dr. Maureen Hood serves as Associate Professor of Radiology and Bioengineering at the Uniformed Services University of the Health Sciences (USU) and functions as a clinical scientist. She maintains dual affiliation with the Walter Reed National Military Medical Center (WRNMMC) as a cardiovascular MR imaging consultant and MR safety expert, driving translational research in military and veteran healthcare settings. Her educational foundation includes: Bachelor of Science in Biology, Minor in Mathematics, University of Puget Sound Associate of Technical Arts in Radiologic Technology, Tacoma Community College Bachelor of Science in Nursing, University of Maryland, School of Nursing Master of Science in Nursing Informatics, University of Maryland, School of Nursing Doctor of Philosophy in Nursing Research, Uniformed Services University of the Health Sciences Dr. Hood's research program bridges engineering and clinical medicine through advanced imaging techniques. Her cardiac MRI work establishes critical correlations between T1/T2 mapping sequences and histological markers in heart failure models, while her current focus on ultrasound-mediated drug delivery targets precision treatment for infections. This dual trajectory in diagnostic imaging innovation and therapeutic application defines her unique contribution to biomedical science. Publication analysis reveals consistent expertise in cardiac MRI physics and safety spanning two decades. Her work demonstrates progressive technical sophistication from foundational contrast agent research to advanced quantitative mapping techniques, with strong emphasis on preclinical validation and clinical translation. Key thematic threads include myocardial tissue characterization, vascular imaging optimization, and rigorous safety protocols for MR environments. Scientific recognition includes: Fellow of the American Heart Association (2015-present) Best Cardiac MR Poster at NASCI Annual Meeting (2011) Linda Strangio Editor’s Award from ARNA (2006) Dr. Hood directs significant research initiatives including the Early Career Scientist Award-funded project on ultrasound-enhanced antibiotic delivery for osteomyelitis. Her leadership extends to editorial responsibilities for Military Medicine and abstract grading for major cardiology/radiology societies, demonstrating commitment to scholarly advancement beyond direct research output. She actively shapes the field through leadership roles in the American Heart Association's Leadership Council on Cardiovascular Radiology, the ISMRM MR Safety Committee, and NASCI research committee, fostering collaborative networks that integrate military medical imaging with broader academic radiology communities.

Yuan-Chiao Luمشاهده پروفایل

استادیار

• Biomedical Imaging
• Biomechanics
• Biostatistics
• +۵ مورد دیگر

Dr. Yuan-Chiao Lu serves as an Assistant Professor in the Department of Radiology and Bioengineering at the Uniformed Services University of the Health Sciences (USU), with concurrent appointments as Scientist at the Henry M. Jackson Foundation and Instructor at the NIH's Foundation for Advanced Education in the Sciences. His multidisciplinary expertise bridges biomedical imaging, biomechanics, and biostatistics, focusing on military-relevant health challenges including traumatic brain injury and fetal development. His educational foundation includes: Ph.D. in Biomedical Engineering and Mechanics, Virginia Tech-Wake Forest University Ph.D. Candidate in Mechanical and Aerospace Engineering, University of Virginia M.S. in Biostatistics, University of Michigan M.S. in Biomedical Engineering, National Cheng Kung University (Taiwan) B.S. in Applied Mathematics (Minor: Biomedical Engineering), National Chung Hsing University (Taiwan) Dr. Lu pioneers the application of tagged MRI for biomechanical brain characterization, advancing understanding of injury mechanisms and medical imaging optimization. His work integrates computational modeling with epidemiological analysis to address traumatic brain injury prevention, maternal psychological distress impacts during the COVID-19 pandemic, and socioeconomic influences on fetal neurodevelopment. This translational approach bridges engineering principles with clinical applications in military medicine. Publication analysis reveals three dominant research trajectories: 1) Computational neurotrauma modeling using validated head impact simulations, 2) Maternal-fetal health investigations examining pandemic stressors on placental and fetal brain development, and 3) Biomechanical characterization of abdominal organs for injury prevention. His work consistently employs advanced statistical harmonization techniques across heterogeneous imaging datasets and demonstrates strong interdisciplinary collaboration with institutions including Children's National Hospital and Johns Hopkins University. Dr. Lu actively contributes to Dr. Pham's research laboratory at USU, participating in teams focused on neuroimaging biomarker development and biomechanical injury prediction. His prior positions at Children's National Hospital and Johns Hopkins University established expertise in pediatric imaging and brain deformation analysis, while his Henry M. Jackson Foundation role facilitates military medical research translation.

Christopher Steeleمشاهده پروفایل

دانشیار

• Cognitive Neuroscience
• Neuroimaging
• Motor Learning and Plasticity
• +۴ مورد دیگر

Dr. Christopher Steele serves as Associate Professor in the Department of Psychology at Concordia University, leading the Neural Architecture, Behaviour, and Connectivity (NeuralABC) Laboratory. His research bridges quantitative neuroimaging and clinical neuroscience to decode brain structure-function relationships. Research interests focus on: Training-related neuroplasticity and motor control electrophysiology Cerebellar-cortical connectivity architecture White matter disconnection in stroke and Alzheimer's disease Quantitative physiologically-specific MRI development Computational image segmentation and registration The lab employs multimodal MRI, diffusion imaging, longitudinal training designs, and Python-based computational tools. Professor Steele teaches advanced courses in neuroanatomy, sensation/perception, and computational neuroscience while leading international workshops. Active collaborations include Max Planck Institute for Human Cognitive and Brain Sciences and Montreal Neurological Institute, with open-source tools publicly available via GitHub. The lab regularly recruits honours students, graduate researchers, and post-doctoral fellows interested in computational neuroscience approaches to brain connectivity.