جست‌وجوی استاد و پژوهشگر

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.

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

Mariano Cabezas Grebol is a researcher affiliated with the Brain and Mind Centre at the University of Sydney . He earned a BSc in Computer Science (2009) and an MSc in Automation, Computation, and Systems (2010) from the University of Girona , followed by a PhD in Technology (2013) focused on atlas-based segmentation of multiple sclerosis lesions . His research bridges neuroimaging and AI models , with specific interests in image synthesis (GANs) , segmentation (cross-sectional/longitudinal) , classification (disease prediction) , uncertainty metrics , and model interpretability . His work has broad implications for Alzheimer's disease , multiple sclerosis , and brain tumor analysis. Scientific Awards : 2020: Understanding Alzheimer's disease with deep learning and neuroimaging grant from the Brain and Mind Centre. International Collaborations : University of Yamagata, Japan (with Dr. Yago in Data Science). VICOROB group, University of Girona, Spain (long-term relationships). His career spans postdoctoral work at VHIR (Hospital Vall d'Hebron) , a Juan de la Cierva-Incorporación fellowship at NIC-VICOROB, and current leadership in developing AI tools for brain image analysis alongside Prof. Michael Barnett in Sydney.

• Neurophysiology
• Electroencephalography (EEG)
• Epilepsy
• +۳ مورد دیگر

Michel J.A.M. van Putten is a Full Professor of Clinical Neurophysiology at the TechMed Centre, University of Twente , with an h-index of 52 and 9261 Scopus citations. His research focuses on: EEG-based outcome prediction in post-cardiac arrest coma Deep learning applications for seizure and interictal discharge detection Neurophysiological modeling of epilepsy and traumatic brain injury Cultured cortical neural networks for disease mechanism inference AI-driven analysis of brain connectivity and excitation-inhibition balance His work contributes to UN Sustainable Development Goals for Health and Well-being , Human-AI Interaction , and Economic Impact of AI . Recent research includes: 2025: Automated inference of disease mechanisms in patient-derived neuronal networks 2025: Expert-level deep neural network for interictal discharge detection 2024: Grassmann manifold methods for invariant EEG/MEG feature extraction Scientific recognition includes: 2011: NVvTG Congres Prize 2012: Tripartite prize for Near Infrared Spectroscopy and EEG research His datasets on EEG analysis and cortical network modeling are publicly available through Zenodo, and he has presented 17 oral presentations on topics including: Post-ictal brain recovery mechanisms Mathematical models of peripheral axons Ischemic cerebral damage pathways

Oliver Faustمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Medical Image Analysis
• +۴ مورد دیگر

Dr. Oliver Faust is an Associate Professor at Anglia Ruskin University's Faculty of Science and Engineering, within the Department of Computing and Information Science. An international expert in AI-driven medical diagnostics, he specializes in physiological signal processing, medical image analysis, and Internet of Medical Things applications. With over 140 publications, his research has significantly impacted computer-aided diagnosis methodologies. His academic credentials include: Doctor of Engineering in Biomedical Science, Chiba University PhD in Electronics, University of Aberdeen Diplom-Ingenieur in Communication Engineering, FH Dieburg Fellow of the Higher Education Academy, UK Chartered Engineer, Institution of Engineering and Technology Dr. Faust's research bridges artificial intelligence with clinical applications, particularly focusing on deep learning approaches for healthcare. His primary investigations involve developing diagnostic algorithms for medical imaging (ultrasound, fundoscopy, thermography) and physiological signal analysis (EEG, ECG). Secondary interests include eHealth systems and IoT-enabled medical devices, with strong emphasis on translational research impacting stroke risk assessment and chronic disease management. His publication portfolio demonstrates extensive work in nonlinear signal analysis, wavelet transformations, and deep learning architectures applied to neurological, cardiovascular, and oncological diagnostics. Recent trends show increasing focus on LSTM networks for arrhythmia detection and comprehensive AI diagnostic frameworks. Honors include: Fellow of the Higher Education Academy, UK Dr. Faust actively supervises PhD students with projects funded by international scholarships. His grants portfolio includes: £75,000 from Sheffield Hallam (2021-2022) £30,000 from Innovate UK (2021-2022) £40,000 from Grow MedTech (2019-2020) Multiple PhD scholarships totaling £99,600 He contributes to the Transformative Artificial Intelligence Applications research cluster and Computing, Informatics and Applications Research Group at ARU, fostering collaborations across 20+ international institutions.

Sukru Kitisمشاهده پروفایل

استادیار

• Medical Electronics
• Biomedical Signal Processing
• EEG and ECG Analysis
• +۵ مورد دیگر

Assistant Professor Sukru Kitis is a dedicated academic at Kütahya Dumlupınar University's Simav Faculty of Technology, Department of Electrical-Electronics Engineering. With over 15 years of academic experience, he has progressed from Instructor (2009-2019) to Doctor Lecturer (2019-present), currently serving as Deputy Head of Department since 2022. His academic journey includes a Bachelor's and Master's in Electrical-Electronics Engineering from Niğde University, followed by a PhD from Sakarya University. His educational background includes: 1999-2004: Bachelor's in Electrical-Electronics Engineering, Niğde University 2004-2007: Master's in Electrical-Electronics Engineering, Niğde University 2008-2019: PhD in Electrical-Electronics Engineering, Sakarya University Professor Kitis's research spans two primary domains with significant interdisciplinary connections: biomedical engineering and renewable energy systems. His biomedical work focuses on advanced signal processing techniques for EEG and ECG analysis, novel filter design for medical applications, and increasingly, machine learning approaches to medical diagnostics including thyroid cancer examination, obesity stage detection, and neurological disorder assessment. His energy research centers on geothermal heating system automation, solar energy applications, and innovative vehicle design using alternative energy sources. These research strands converge in his recent work on providing energy for biomedical devices using renewable resources. His publication record demonstrates strategic evolution from circuit design and biomedical instrumentation (2012-2017) toward data-driven healthcare solutions (2018-2025), while maintaining parallel expertise in sustainable energy systems. This dual focus creates unique opportunities for students interested in the intersection of healthcare technology and sustainable engineering. Professor Kitis has received recognition for his scholarly contributions, most notably the Best Paper award in 2017. His research impact extends through: 93 publications including journal articles and conference proceedings 3 major research projects related to forest fire monitoring, electric vehicle design, and geothermal system automation 2 scientific awards including Best Paper 2017 As an educator and mentor, Professor Kitis supervises numerous graduate students working on cutting-edge projects at the intersection of electrical engineering, biomedical applications, and renewable energy. His administrative roles as Department Head (2019-2021) and current Deputy Head of Department demonstrate leadership within his academic community while maintaining active research and teaching responsibilities. His lab environment emphasizes practical application of theoretical concepts, with students working on real-world problems in medical device development, energy system optimization, and data-driven healthcare solutions. The interdisciplinary nature of his research creates a dynamic environment where electrical engineering principles meet medical and environmental challenges.

Sarah-Beth Longمشاهده پروفایل

دانشیار

• Rhetoric
• Technical Communication
• Discourse Analysis
• +۴ مورد دیگر

Sarah-Beth Long is Associate Professor and Internship Director in the Department of English at Appalachian State University, where she has taught since 2015. Her academic specialty centers on Rhetoric & Technical Communications, with research bridging discourse analysis and data science methodologies. Prior to Appalachian State, she was a graduate teaching assistant at the University of South Florida, receiving the Provost’s 21st Century Teaching and Learning award. Dr. Long holds a Ph.D. in English from the University of South Florida (2012-2015) with certificates in Instructional Design and Technical Writing, an M.A. in Literature from Mercy College (2012), an M.A. in Creative Writing with distinction from Lancaster University (2001), and a B.A. in Journalism from Florida Southern College (2000). She was the 2000-2001 Rotary Ambassadorial scholar. Her research investigates public discourses on contentious scientific issues through computational rhetoric, focusing on climate change communication, sustainability practices, and Agent Orange legacy. She employs sentiment analysis and social network mapping to examine how social media platforms facilitate community engagement, as demonstrated in her work with the Roatan Marine Park and Vietnam Association for Victims of Agent Orange. Dr. Long's publication trajectory shows increasing integration of data science with rhetorical analysis, moving from traditional technical communication scholarship toward algorithmic text analysis and cross-cultural discourse studies. Her recent work emphasizes practical applications for social change through nonprofit partnerships and community-based research. Notable recognitions include the Alma Bryant Outstanding Graduate Student Award (2014) and the competitive USF 21st Century Teaching Fellowship ($20,000). She has secured over $10,000 in Appalachian State research funding and is pursuing a $150,000 NSF grant. Dr. Long actively mentors students through honors theses and master's committees, emphasizing real-world applications of technical communication. Her grant portfolio supports international fieldwork in Vietnam and computational social science projects examining stakeholder engagement in technical democracy. Though not leading a formal laboratory, Dr. Long collaborates with interdisciplinary teams through professional organizations including SIGDOC and CPTSC. Her consulting work with nonprofits on social media for social change extends her academic research into practical community impact through sarahbethhopton.com.

Frédéric Lesageمشاهده پروفایل

استاد

• Biomedical Engineering
• Neuroimaging
• Optical Imaging
• +۵ مورد دیگر

Frédéric Lesage is a Full Professor in the Department of Electrical Engineering at Polytechnique Montréal and holds a Tier 1 Canada Research Chair in Vascular Optical Imaging. His multidisciplinary research bridges biomedical engineering, neuroscience, and AI, with affiliations spanning the Functional Imaging Laboratory (INSERM), Montreal Heart Institute, and Centre for Mathematical Research. Research interests center on neuroimaging innovations for studying cerebral physiology. Key areas include: Neurovascular Coupling: Investigating blood flow dynamics in aging and Alzheimer's using optical coherence tomography and NIRS. Epilepsy Diagnostics: Developing AI models for seizure prediction via EEG/fNIRS fusion. Microvascular Pathologies: Mapping microstroke impacts using two-photon microscopy and adversarial learning. His 15 most recent publications (2020-2025) emphasize AI-driven neurology applications, showing trends in: Machine learning for epileptic EEG analysis Cerebral pulsatility in neurodegenerative diseases Translational vascular imaging (OCT/TPM) Awards include the Canada Research Chair (Tier 1) , renewed in 2022 for pioneering vascular imaging techniques. He has advised 57+ graduate students (27 PhD, 30 Master's) and secured grants from NSERC, CIHR, and CRC. Current projects focus on hypoxia effects, statin therapy in Alzheimer's, and catheter-based surgical simulators.

• Mitochondrial Dynamics
• Neurological Diseases
• 4D Microscopy
• +۳ مورد دیگر

Johannes Schöneberg serves as Assistant Professor of Pharmacology at the University of California San Diego's School of Medicine, holding joint appointments in Chemistry & Biochemistry. His research integrates cutting-edge microscopy, computational biology, and stem cell technologies to quantitatively analyze cellular behavior in native tissue environments. His laboratory focuses on mitochondrial dynamics and their role in neurological disorders including Parkinson's Disease and epilepsy. Key methodologies include stem cell-derived organoids, 4D adaptive optics lattice light-sheet microscopy, high-performance computing, and machine learning applications. Research spans computational modeling of cellular processes through tools like ReaDDy software to advanced image analysis techniques for tracking subcellular structures. The group's publication record demonstrates expertise across biophysics, computational biology, and neuropharmacology, with recent work emphasizing mitochondrial network tracking and 4D cellular imaging. Though newly established at UCSD, the lab shows strong interdisciplinary connections through collaborations with microscopy pioneers like Eric Betzig. No scientific awards are currently listed in available sources. The laboratory maintains active research in neurological disease mechanisms with emphasis on mitochondrial dysfunction pathways. As a newly formed research group, current activities focus on establishing organoid models and advanced imaging pipelines. The lab leverages UCSD's strong infrastructure in computational biology and neuroscience research, with potential for future grant development in mitochondrial disease mechanisms and imaging technology.

• 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.

Michael Yuchiمشاهده پروفایل

استاد

• Ion Channels
• Structural Biology
• Chemical Biology
• +۳ مورد دیگر

Michael Yuchi serves as Professor and Vice Dean at Tianjin University's School of Pharmaceutical Science and Technology, with additional affiliation as Affiliate Member of the Department of Biochemistry & Molecular Biology in the Faculty of Medicine. His research centers on ion channels—the second largest drug target class and primary insecticide target—with focus on: Structural & Chemical Biology : Elucidating molecular mechanisms of human and insect ion channels using X-ray crystallography and cryo-EM Therapeutic Development : Designing modulators for RyRs/Navs to treat arrhythmia, neuropathic pain, and epilepsy Insecticide Innovation : Creating selective compounds targeting agricultural pests and disease vectors AI Integration : Developing closed-loop systems combining machine learning, protein design, and synthetic biology Recent work demonstrates strong convergence of structural insights with practical applications, exemplified by the 2024 Nature Communications publication on RyR-diamide interactions for resistance management. No scientific awards are documented in the provided materials. Professor Yuchi leads the Yuchi Lab, which operates through integrated structural, computational, and chemical biology platforms utilizing Tianjin University's super-computing resources for high-throughput screening and protein modeling, with explicit goals of developing next-generation therapeutics and insecticides.

• Neural Networks
• Electroencephalography
• Epileptic Seizure Detection
• +۴ مورد دیگر

Dimitrios Liarokapis serves as a Senior Lecturer in Cyber Security and Networks at Glasgow Caledonian University, United Kingdom. His primary affiliation is with the Department of Cyber Security and Networks within the university's engineering or computing school structure, though the specific school name isn't explicitly stated in available materials. His research spans three interconnected domains: Biomedical AI applications using Random Neural Networks for epileptic seizure detection and fall prevention through EEG signal analysis Telecommunications innovation focusing on millimeter wave optimization for 5G cellular networks Sustainable logistics through data-intelligence-driven digital twin frameworks These areas demonstrate consistent application of neural network architectures to solve domain-specific problems with real-world impact. Analysis of his publication trends since 2011 reveals increasing focus on healthcare and logistics applications, with recent high-impact work in Applied Sciences (2024) and Sensors (2022). His eight research outputs show growing citation impact, particularly in medical AI applications. Dr. Liarokapis actively secures industry partnerships, currently leading the Advanced Logistics Data Integration project with JOHN G. RUSSELL (TRANSPORT) LIMITED. This Knowledge Exchange initiative develops bespoke data pipelines for logistics operations, demonstrating strong industry-academia collaboration. His supervision record includes at least one research student, with opportunities likely available in his interdisciplinary projects. His laboratory environment emphasizes practical AI implementation across healthcare monitoring systems and sustainable logistics solutions, leveraging neural network architectures to process complex datasets from EEG signals to supply chain operations.

• Pediatric Neurosurgery
• Epilepsy Surgery
• Spine Surgery
• +۵ مورد دیگر

Sean Lew, MD is an Associate Professor in the Department of Neurosurgery at the Medical College of Wisconsin, specializing in Pediatric Neurosurgery. He serves as the Program Director for the Neurosurgery Epilepsy Program at Children's Hospital of Wisconsin and maintains clinical privileges at multiple Milwaukee-area hospitals including Aurora St. Luke's Medical Center, Aurora Sinai Medical Center, Froedtert Memorial Lutheran Hospital, and Wheaton Franciscan Healthcare. Dr. Lew's research interests span pediatric epilepsy surgery, spinal deformities (particularly early-onset scoliosis), craniovertebral junction disorders, and neuro-oncology. His work has significantly contributed to the understanding of surgical outcomes in pediatric epilepsy and spinal deformity correction. He has published over 100 peer-reviewed articles, with recent work focusing on advanced epilepsy monitoring techniques, laser ablation therapies, and growth-friendly spinal instrumentation. His publication record shows consistent productivity with numerous 2025, 2024, and 2023 publications in high-impact journals such as Journal of Pediatric Orthopaedics, Scientific Reports, and Journal of Neurosurgery Pediatrics. Key research themes include functional connectivity in epilepsy networks, minimally invasive surgical approaches, and multicenter outcomes studies for complex pediatric neurosurgical conditions. Board Certified by American Board of Neurological Surgery (2007-2017) Board Certified by American Board of Pediatric Neurological Surgery (2008-2018) Best Doctors in America (2007-2012) Patient's Choice Award (2008, 2010) Donaghy Clinical Research Award Dr. Lew actively mentors medical students, residents, and fellows, with documented mentorship of numerous trainees including Joshua Larson, Jeffrey Kao, and Francis Seiler. He serves on the editorial boards of several journals including Child Nervous System and Advances in Orthopedics, and regularly reviews for multiple neurosurgical and neurological publications. He leads the Neurosurgery Epilepsy Program at Children's Hospital of Wisconsin, where he performs a comprehensive range of epilepsy procedures including invasive monitoring, resective surgery, corpus callosotomy, and hemispherectomy. His work with the Pediatric Spine Study Group has contributed significantly to the field of pediatric spinal deformity correction.

• Neuropsychology
• Cognitive Impairment
• Alzheimer's Disease
• +۵ مورد دیگر

Laura Umfleet, PsyD is an Associate Professor in the Department of Neurology, Division of Neuropsychology at the Medical College of Wisconsin. She also holds an appointment as Adjunct Assistant Professor in Psychology at the University of Wisconsin, Milwaukee. Dr. Umfleet is actively involved with multiple research centers including the Center for Microbiome Research, Neuroscience Research Center, and Wisconsin Institute of NeuroScience (WINS), reflecting her interdisciplinary approach to neurodegenerative research. Dr. Umfleet's research focuses on neuropsychological aspects of cognitive aging and neurodegeneration. Her work examines mild cognitive impairment (MCI) phenotypes, cerebrovascular reactivity in cognitive decline, and the emerging relationship between gut microbiome and brain health in Alzheimer's disease. She employs advanced neuroimaging techniques and quantitative analysis methods to identify cognitive subtypes and understand the neural correlates of cognitive performance. Her research program bridges clinical neuropsychology with translational neuroscience to develop more precise diagnostic and intervention approaches. Dr. Umfleet maintains an active grant portfolio as Principal Investigator on multiple studies funded by the National Institute on Aging (NIA), Advancing a Healthier Wisconsin Endowment, and other sources. Her current projects investigate neurovascular uncoupling in non-amnestic MCI, the intersection of GLP-1, gut microbiota, and brain connectivity in prodromal Alzheimer's disease, and initiatives to improve neurodegenerative research in Black American populations. She is also a Co-Investigator on NIH-funded studies examining cognitive outcomes in congenital heart disease and neuroimaging biomarkers in Alzheimer's disease. Her publication record demonstrates expertise in neuropsychological assessment across diverse populations including those with Alzheimer's disease, multiple sclerosis, and congenital heart disease. Recent publications highlight her work on cerebrovascular reactivity in MCI, cognitive subtyping using graph theory, and the relationship between cognitive reserve and brain structure in different MCI phenotypes. Dr. Umfleet is board certified by the American Board of Professional Psychology (ABPP) in Clinical Neuropsychology and maintains active clinical practice alongside her research and teaching responsibilities. She has contributed significantly to the development of neuropsychological assessment tools and methodologies, with numerous publications on test validity, reliability, and clinical application.

• Computational Neuroscience
• Neuroimaging
• Brain Connectivity
• +۷ مورد دیگر

Dr. Vahab Youssofzadeh is an Assistant Professor in the Department of Neurology at the Medical College of Wisconsin. He is a member of both the Neuroscience Research Center and the Wisconsin Institute of NeuroScience (WINS), reflecting his interdisciplinary approach to neuroscience research. Dr. Youssofzadeh's research focuses on computational neuroscience and neuroimaging, with particular emphasis on brain connectivity, language processing, and neural oscillations. His work utilizes advanced techniques including magnetoencephalography (MEG), functional MRI, and computational modeling to investigate both healthy brain function and neurological disorders. His research spans multiple domains including language networks, epilepsy, Alzheimer's disease, and motor adaptation. His publication record demonstrates significant contributions to the field, with numerous high-impact papers on brain connectivity analysis, language processing, and computational approaches to neurological disorders. His most recent work includes studies on transcranial stimulation for language disorders, intracortical stimulation for sensory restoration, and advanced methods for mapping brain networks. Dr. Youssofzadeh is actively involved in collaborative research, as evidenced by his extensive publication record with multiple co-authors from various institutions. His work bridges computational methods with clinical neuroscience applications, contributing to both theoretical understanding and potential clinical interventions. As a member of the Neuroscience Research Center and WINS, Dr. Youssofzadeh participates in the broader neuroscience community at the Medical College of Wisconsin, contributing to interdisciplinary research initiatives and training the next generation of neuroscientists.

• Neuropsychology
• Epilepsy
• Neuroimaging
• +۵ مورد دیگر

Carrie McDonald, Ph.D., is a Professor In Residence in the Department of Radiation Medicine and Applied Science at UC San Diego. She holds affiliations with the UCSD Multimodal Imaging Laboratory, UCSD Epilepsy Center, UCSD Neuropsychological Associates, and the UCSD Translational Brain Tumor Assessment Clinic. Dr. McDonald obtained her B.S. in Psychology from Eckerd College and her Ph.D. in Clinical and Health Psychology from the University of Florida, followed by specialized training in neuropsychology at UCSD and the V.A. San Diego Healthcare System. Her research examines neuropsychological deficits using advanced neuroimaging techniques, with focus areas including: Predicting postoperative cognitive outcomes in epilepsy surgery patients Language/memory reorganization using structural and functional MRI Neurodegeneration in Alzheimer's disease and aging populations with epilepsy Advanced diffusion imaging for brain tumor monitoring She actively leads NIH-funded projects on brain aging in epilepsy (BRACE study) and multi-site neuroimaging initiatives through ENIGMA-Epilepsy. Dr. McDonald's recent publications (2023-2025) demonstrate strong emphasis on artificial intelligence applications in epilepsy diagnostics, neuroplasticity in bilingual patients, radiation-induced cognitive changes, and international classifications of cognitive disorders. Her work integrates machine learning with clinical neuroimaging to develop predictive models for surgical outcomes. Honors include: NINDS K23 Career Development Award Epilepsy Foundation/American Epilepsy Society Fellowship UCSD Fellowship in Biological Psychiatry and Neuroscience She mentors graduate students and postdoctoral researchers in neuroimaging analysis and neuropsychological assessment methods. Current NIH R01 grants support investigations into cognitive resilience, brain network reorganization, and transdiagnostic biomarkers across epilepsy syndromes. Dr. McDonald directs the Lab of Cognitive Imaging, which focuses on developing novel imaging biomarkers for cognitive outcomes in neurological disorders. The lab collaborates extensively with the UCSD Epilepsy Center and international consortia to translate research findings into clinical practice.