جست‌وجوی استاد و پژوهشگر

Gary E. Christensenمشاهده پروفایل

استاد

• Medical Imaging
• Image and Signal Processing
• Lung Cancer Imaging
• +۳ مورد دیگر

Gary E. Christensen is a Professor of Electrical and Computer Engineering and Radiation Oncology at the University of Iowa's College of Engineering. He joined the college in 1997 and is affiliated with the Iowa Institute for Biomedical Imaging. His expertise spans medical imaging, signal processing, and biomedical engineering. Christensen holds degrees from Washington University: DSc (1994), MS (1989), and dual BS in Electrical Engineering and Computer Science (1988). He is a Fellow of IEEE, AIMBE, AIAA, and a lifetime member of SPIE. His research focuses on medical imaging technologies, including 4DCT ventilation analysis, radiation therapy optimization, and biomarker development for lung cancer and bipolar disorder. Notable areas include image registration, lung biomechanics, and AI-driven imaging solutions. His articles highlight advancements in CT-based ventilation assessment, radiation-induced lung changes, and vocal tract modeling. Awards include prestigious fellowships for contributions to biomedical imaging and engineering. Christensen's work integrates engineering principles with clinical applications, advancing personalized medicine and radiation oncology through innovative imaging techniques.

• Cognitive Neuroscience
• Attention
• Working Memory
• +۷ مورد دیگر

Anna Christina Nobre is the Wu Tsai Professor of Psychology at Yale University, with a primary appointment in the Department of Psychology at the Yale School of Medicine. She is also affiliated with the Interdepartmental Neuroscience Program, the Wu Tsai Institute, the Yale Biomedical Imaging Institute, and the Yale Combined Program in the Biological and Biomedical Sciences (BBS), reflecting her strong interdisciplinary research profile in cognitive neuroscience. Her research centers on the cognitive and neural mechanisms of attention, working memory, and long-term memory. She investigates how the brain uses spatiotemporal predictions to guide attention, how attention shapes memory processes, and how these systems interact dynamically. Her work often employs advanced neuroimaging techniques such as magnetoencephalography (MEG) and functional MRI to capture the fast neural dynamics of cognitive control. The recent publications highlight consistent themes in cognitive neuroscience, particularly in attentional prediction, memory reselection, neural dynamics in Alzheimer’s disease, and metacognitive aspects of memory. Her research spans healthy cognition and clinical populations, with implications for neurodegenerative and psychiatric disorders. While no specific scientific awards are listed in the provided text, her publication record in high-impact journals such as Nature Communications , Journal of Neuroscience , and Trends in Cognitive Sciences underscores her significant contributions to the field. She collaborates with prominent researchers including Dana Small, Todd Constable, and Elizabeth Roessler. Although no formal list of advisees is provided, her leadership in major research programs suggests active mentorship. She is deeply embedded in Yale’s neuroscience ecosystem and continues to lead cutting-edge research at the Wu Tsai Institute.

• Cardiovascular Imaging
• Interventional Radiology
• Cardiac CT/MR Imaging
• +۵ مورد دیگر

Hamid Mojibian, MD, is a Professor of Radiology and Biomedical Imaging at Yale School of Medicine and serves as Director of Cardiac CT/MR Imaging. He also holds the position of Associate Professor of Internal Medicine (Cardiology) and is Interim Chair of the Department of Radiology at Bridgeport Hospital. His work bridges radiology, cardiology, and interventional vascular therapy, with a focus on advanced cardiac imaging and minimally invasive procedures. Research Interests: Cardiovascular Imaging Interventional Radiology Cardiac CT/MR Imaging Artificial Intelligence in Radiology Pulmonary Embolism Management Vascular and Endovascular Therapy Dr. Mojibian's recent research explores the integration of artificial intelligence in diagnosing and managing cardiovascular conditions, particularly pulmonary embolism and abdominal aortic aneurysm. His publications highlight the use of machine learning for risk stratification, diagnostic validation, and improving clinical workflows in vascular imaging. Scientific Awards: RSNA Roentgen Resident/Fellow Research Award RSNA Roentgen Resident/Fellow Research Award Most Outstanding Surgical and Transitional Intern of the Year Dr. Mojibian is actively involved in clinical research and mentoring. He leads the DEFIANCE clinical trial, investigating the ClotTriever system versus anticoagulation in deep vein thrombosis. He collaborates extensively with cardiologists, radiologists, and vascular surgeons, emphasizing interdisciplinary teamwork in patient care and research. He also contributes to programs such as the Advanced Cardiovascular CT/MR Program, Preventive Cardiovascular Health Program, and Vascular & Interventional Radiology at Yale. His laboratory and clinical work are centered at Yale Medicine’s Department of Radiology & Biomedical Imaging, where he advances innovation in non-invasive vascular imaging and interventional techniques.

Erik Ullianمشاهده پروفایل

استاد

• Astrocyte Biology
• Neurodegenerative Diseases
• Synaptic Plasticity
• +۷ مورد دیگر

Erik Ullian is a Professor at the University of California San Francisco (UCSF), with a focus on neuroscience. His research spans astrocyte biology, synaptic plasticity, and neurodegenerative diseases, supported by prestigious awards such as the NIH New Innovator Award and Allen Distinguished Investigator Award. Education: BA in Biological Science (University of Chicago, 1991), PhD in Neuroscience (UCSF, 1997), Postdoc in Neurobiology (Stanford, 2004) His work explores astrocyte-neuron interactions, neuroinflammation, and mechanisms in Alzheimer's disease, ALS, and glioblastoma. Key methodologies include CRISPRi screening, brain organoids, and transcriptomic analysis. Recent publications highlight TDP-43 pathology in ALS, glucose metabolism restoration in Alzheimer's, and astrocyte roles in cancer suppression. Earlier contributions include neurodevelopmental studies on synaptic mapping and SARS-CoV-2 tropism for astrocytes. Scientific Awards Epilepsy training grant award (2001) Zaffaroni research fellowship in addiction research (2002) Sandler Award (2004) Alfred P. Sloan Fellowship (2005) March of Dimes Basil O’Connor Award (2006) Research to Prevent Blindness- New Investigator Award (2009) NIH New Innovator Award (2014) Walt and Lilly Disney Award for Amblyopia Research (2015) Allen Distinguished Investigator Award (2015)

Jan Henrik Ardenkjær-Larsenمشاهده پروفایل

استاد

• Biomedical Engineering
• Medical Imaging
• Magnetic Resonance Imaging (MRI)
• +۴ مورد دیگر

Jan Henrik Ardenkjær-Larsen is a Professor and Head of Department of Health Technology at the Technical University of Denmark (DTU), leading research in magnetic resonance hyperpolarization and metabolic imaging. His work focuses on enhancing MR sensitivity through unconventional methods in chemistry, physics, and engineering. Education M.Sc. in Electrical Engineering, DTU Ph.D., DTU Research Highlights He pioneered dissolution Dynamic Nuclear Polarization (DNP) in 2003, enabling hyperpolarized metabolic MR in real time. In 2013, his team conducted the first clinical study using hyperpolarized 13C-pyruvate for prostate cancer. Current research spans hyperpolarization techniques, electron paramagnetic resonance imaging (EPRI), and Overhauser MRI (OMRI), with applications in cancer diagnostics, cardiac imaging, and metabolic monitoring. Scientific Contributions His 298 publications and 15 projects reflect leadership in hyperpolarized contrast agents, bioreactor systems, and multinuclear MRI. Notable awards include the Günther Laukien Prize (2012) and ISMRM Fellowship (2020). Awards Günther Laukien Prize (2012) Gold Medal Award, World Molecular Imaging Society (2014) Fellow of International Society of Magnetic Resonance (2017) Fellow of ISMRM (2020) Advising & Collaborations Actively supervising PhD projects on hyperpolarized metabolic imaging, he collaborates across biomedical engineering, MR instrumentation, and clinical translation. His work aligns with UN SDGs through biomedical innovation.

Hosamadin S. Assadiمشاهده پروفایل

پژوهشگر

• Cardiovascular Magnetic Resonance Imaging
• Artificial Intelligence in Medical Diagnostics
• Heart Failure with Preserved Ejection Fraction (HFpEF)
• +۳ مورد دیگر

Dr. Hosamadin S. Assadi is a postgraduate researcher at the University of East Anglia (Norwich Medical School) and an Honorary Scientist at Norfolk & Norwich University Hospitals NHS Foundation Trust. With a medical background and an MRes in Cardiovascular Medicine from the University of Sheffield, he specializes in AI-driven cardiovascular magnetic resonance (CMR) imaging post-processing techniques. Focus areas: 4D flow CMR, scar/fibrosis quantification, and pressure-volume loop analysis Key collaborations: UEA, University of Sheffield, and NHS Trust External roles: Honorary Scientist (Cardiology) since 2022 His research develops AI-based CMR methodologies to improve diagnosis accuracy for cardiovascular diseases, particularly heart failure with preserved ejection fraction (HFpEF) and aortic stenosis. Publications demonstrate expertise in: Machine learning for cardiac segmentation Non-invasive hemodynamic monitoring Multi-center clinical validation studies Sex-specific prognostic models Scientific recognition includes: FMH Research Prize (2024) MRes Distinction (2020) Media engagement highlights: AI applications in cardiac MRI featured in 44+ outlets (2024) Development of rapid heart scan technology Public education about MRI-based pressure detection systems

Teppo Särkämöمشاهده پروفایل

دانشیار

• Neuropsychology
• Music perception
• Speech processing
• +۶ مورد دیگر

Teppo Särkämö is an Associate Professor of Neuropsychology at the Department of Psychology and Logopedics , Faculty of Medicine , University of Helsinki. He serves as a Senior Scientist at the Cognitive Brain Research Unit (CBRU) and leads the Music, Ageing and Rehabilitation Team (MART) . His research focuses on the neural mechanisms of music and speech perception , their deficits ( aphasia, amusia ), and music-based rehabilitation in neurological disorders like stroke and Alzheimer's disease. Key research areas: Neuropsychology, Cognitive neuroscience, Music therapy, Aging, Neuroplasticity, Neurology His ERC-funded projects investigate singing in normal aging, music-evoked emotions in dementia, and structural brain connectivity in aphasia. Recent publications highlight music's role in enhancing neural plasticity and rehabilitation outcomes through longitudinal and clinical studies. Scientific honors: Cortex Prize (2017) Doctoral Thesis Prizes (2011) Göttinger Innovatiospreis (2009) Publication of the Year (2008) He supervises doctoral and master's theses, including work by Nella Moisseinen , and actively engages in public outreach through lectures and media interviews.

• Neurosurgery
• Glioma
• Brain Imaging
• +۴ مورد دیگر

Djaina Satoer is a Researcher at Erasmus MC in the Neurosurgery department under the Erasmus School of Medicine. Her work focuses on neurosurgical outcomes, cognitive function in glioma patients, and advanced brain imaging techniques. Developed functional ultrasound methods for mobile brain imaging Investigated cognitive deterioration post-radiotherapy in glioma patients Studied awake craniotomy techniques for eloquent area tumors Her recent publications (2024-2025) examine longitudinal cognitive assessment in glioma patients and functional ultrasound monitoring. Collaborations include teams from neuroscience and oncology disciplines.

• Alzheimer's Disease
• Amyloid Protein Research
• Tau Pathology
• +۵ مورد دیگر

Julia Neitzel serves as Assistant Professor in the Department of Radiology & Nuclear Medicine at Erasmus MC, a leading academic medical center in the Netherlands. Her research sits at the intersection of neuroimaging, cardiovascular health, and neurodegenerative processes, with particular focus on Alzheimer's disease mechanisms. Dr. Neitzel's research spans multiple critical areas in neuroscience including Alzheimer's disease pathology, amyloid and tau protein dynamics, cognitive function assessment, and vascular contributions to brain health. Her work frequently examines how cardiovascular factors like hypertension and arterial calcification interact with neurological processes, utilizing advanced neuroimaging techniques such as PET and MRI to track biomarker changes over time. She actively investigates how social determinants, lifestyle factors, and metabolic profiles influence brain health trajectories across the lifespan. Analysis of her recent publication record (2024-2025) reveals a strong thematic focus on the heart-brain axis, with multiple studies examining how cardiovascular health metrics correlate with neurodegenerative processes. Her research consistently employs large cohort studies and sophisticated multi-modal imaging approaches to unravel complex interactions between vascular health, metabolic profiles, and cognitive outcomes. A significant portion of her work contributes to understanding modifiable risk factors for cognitive decline, with implications for preventive interventions targeting the vascular component of dementia. Dr. Neitzel actively participates in major collaborative research initiatives including the Cross-Cohort Collaboration Consortium and Alzheimer's Disease Metabolomics Consortium, indicating her role in large-scale, multi-institutional research efforts. Her supervised work includes mentoring early-career researchers in neuroimaging and dementia research methodologies.

Jessica Mariana Carlssonمشاهده پروفایل

عضو هیئت علمی

• Transcultural Psychiatry
• Trauma and PTSD
• Clinical Research
• +۷ مورد دیگر

Jessica Mariana Carlsson is a Research Associate Professor at the University of Copenhagen and Head of Research at the Competence Centre for Transcultural Psychiatry (CTP), Mental Health Services in the Capital Region of Denmark. She is also Co-PI of the CultMind project and leads a dynamic research group at both CTP and Trauma Research and Treatment (TREAT) at Mental Health Centre Ballerup. Her role integrates research leadership, clinical work, teaching, and supervision. Research Interests: Jessica's work centers on transcultural psychiatry and clinical research on trauma-affected populations, particularly refugees. Her primary focus includes PTSD, treatment development, cultural influences on mental health, and the integration of research with clinical practice through the Treatment and Research Integrated Model (TRIM). She employs both quantitative and qualitative methods and leads neurobiological studies using MRI and EEG. Research Trends: Her recent publications (2023–2025) show a strong emphasis on developing and validating assessment tools (e.g., ScoRE-SR), understanding sleep and pain in PTSD, refining diagnostic processes for migrants, and evaluating interprofessional care models. The studies often involve multidisciplinary collaboration and are published in high-impact journals in psychiatry, sleep research, and transcultural mental health. Scientific Awards: No specific awards mentioned in the provided text. Advising and Grants: Jessica supervises a growing research group and mentors junior researchers. While specific grant details are not listed, her leadership in multiple clinical trials and research initiatives (e.g., CultMind, TRIM) indicates substantial grant-funded work. She actively collaborates with national and international researchers and clinicians, contributing to a broad network in trauma and transcultural mental health. Labs and Teams: She leads research activities at the Competence Centre for Transcultural Psychiatry (CTP) and the Trauma Research and Treatment (TREAT) unit at Mental Health Centre Ballerup. These teams focus on clinical trials, diagnostic innovation, cultural assessment, and neurobiological research in trauma-affected refugees.

Noeska Smitمشاهده پروفایل

استاد

• Medical Visualization
• Computational Medicine
• Multimodal Imaging
• +۳ مورد دیگر

Noeska Smit is a Professor in Medical Visualization at the Department of Informatics, University of Bergen , where she has held a tenure-track position funded by the Trond Mohn Foundation since 2017. She is also a senior researcher and member of the leadership team at the Mohn Medical Imaging and Visualization (MMIV) Centre . Her research focuses on novel interactive visualization techniques for exploring and communicating multimodal medical imaging data , particularly in multi-parametric MR acquisitions . She leads projects in gynecologic cancer imaging , Multiple Sclerosis neuroimaging , and human anatomy education through collaborations with institutions like UGent (Belgium) and HVL. 2019: Dirk Bartz Prize for Visual Computing in Medicine 2016: PhD at Delft University of Technology , Netherlands 2012: MSc in Computer Science (Computer Graphics & Visualization) , Delft University Recent publications highlight her work in MRI radiomics , narrative visualization , open-source anatomy platforms , and interactive clustering tools for tumor analysis. Her methods are applied in oncological pelvic surgery planning , neurological disease monitoring , and 3D learning environments . She supervises PhD candidates Eric Mörth and Sherin Sugathan , and has contributed to open-source medical visualization tools like RegistrationShop and Online Anatomical Human (OAH) . Her work bridges clinical practice and computer science through collaborations with radiologists, surgeons, and ML researchers.

Benny Avelinمشاهده پروفایل

مدرس ارشد

• Partial Differential Equations
• Analysis
• Nonlinear Analysis
• +۱۲ مورد دیگر

Benny Avelin is a Senior Lecturer in the Department of Mathematics at Uppsala University, Sweden, with affiliations in the research groups on Analysis and Partial Differential Equations, and Statistics, AI and Data Science. Research Interests: His work spans a broad spectrum from pure mathematical analysis to applied machine learning. He specializes in partial differential equations, particularly those of p-Laplace and degenerate parabolic types, as well as stochastic partial differential equations. More recently, his research has expanded into mathematical aspects of deep learning, including neural ODEs, deep limits of networks, and uncertainty quantification in AI models. Publication Trends: A close analysis of his recent publications reveals a strong trajectory bridging classical analysis with modern data science. While maintaining a deep engagement with nonlinear PDEs and potential theory, he increasingly contributes to the mathematical foundations of AI, especially in understanding the behavior of deep neural networks through continuous limits and stochastic modeling. His recent work also includes interdisciplinary applications in medical imaging and extreme value statistics. Scientific Contributions: Author of the doctoral thesis Boundary Behavior of p-Laplace Type Equations (2013). Active collaborator with leading researchers such as Kaj Nyström, Tuomo Kuusi, and Vesa Julin. Contributor to high-impact journals including Journal of the European Mathematical Society , Communications in Mathematical Physics , and Journal of Machine Learning Research . Advising and Grants: While specific information about students, advising, or grants is not available in the provided texts, his extensive publication record and collaborative research suggest active involvement in academic mentoring and likely participation in research funding projects. Labs and Teams: Benny Avelin is a member of the Analysis, PDEs and Applications research group at Uppsala University, which organizes the PDE & Applications seminar. His work appears to be highly collaborative, involving both theoretical and computational components, though no dedicated lab or team name beyond the research group is mentioned.

• Biomedical Informatics
• Machine Learning
• Data Mining
• +۵ مورد دیگر

Dr. Yanqing Ji is a Professor in the Department of Electrical and Computer Engineering at Gonzaga University, specializing in biomedical informatics and high-performance computing. He serves as an editor for the Journal of Digital Signal Processing and a reviewer for 23 international journals. Education: Ph.D. in Computer Engineering, Wayne State University M.Sc. in Physical Electronics, University of Science & Technology of China B.E. in Industrial Automation, Qingdao University Dr. Ji's research focuses on biomedical association mining, adverse drug reaction detection, and parallel/cloud computing applications in healthcare. His work integrates machine learning, fuzzy logic, and multi-agent systems to enhance drug safety surveillance and biomedical literature search. His publications emphasize scalable MapReduce solutions for biomedical text mining, temporal association mining for drug interactions, and intelligent agent systems for pharmacovigilance. These span prestigious conferences like IEEE BIBM, ITNG, and NAFIPS, alongside journals such as BMC Bioinformatics and IEEE Transactions on Knowledge and Data Engineering . Scientific awards include NIH R21, AHRQ R18 grants, and NSF-funded projects (IGERT 9987598, MRI 9977815, ITR 0081696). He has led system design for distributed healthcare applications and optimized decision models using genetic algorithms.

Hélène Girouardمشاهده پروفایل

استاد

• Neurovascular Coupling
• Arterial Stiffness
• Hypertension
• +۵ مورد دیگر

Hélène Girouard is a full professor in the Department of Pharmacology and Physiology at the Faculty of Medicine, Université de Montréal, and directs the Cerebrovascular Pharmacology Laboratory at CRIUGM. Her research explores neurovascular coupling mechanisms, vascular contributions to cognitive decline, and sex/gender differences in neurodegenerative diseases. PhD in Cardiovascular Physiology (Université de Montréal, 2002) Postdoctoral Training: Cornell University (2003-2006), University of Vermont (2006-2008) Research Focus: Investigates how arterial stiffness , hypertension , and neuroinflammation disrupt neurovascular coupling , accelerating cognitive decline and Alzheimer's pathology . Special emphasis on sex differences and menopausal transitions in vascular brain health. Key Techniques: Multi-photon microscopy, laser Doppler flowmetry, MRI biomarkers, and in vivo / in vitro cerebrovascular pharmacology. Scientific Awards: 2002: Top 5% PhD Theses, Université de Montréal 2004: CIHR Recognition Award 2012: Jacques de Champlain Prize (Heart & Stroke Foundation) 2015: Fellow of the American Heart Association Training & Grants: Over 20 years of continuous funding from CIHR , FRQS , FMCC , NSERC , and Brain Canada . Supervises students in neurovascular imaging , vascular dementia , and sex-specific brain aging .

Caitlin Wardمشاهده پروفایل

استادیار

• Bayesian Statistics
• Infectious Disease Modeling
• Spatio-Temporal Modeling
• +۴ مورد دیگر

Caitlin Ward, PhD is an Assistant Professor at the University of Minnesota's Division of Biostatistics & Health Data Science. Her work bridges methodological development and interdisciplinary collaboration. Education : PhD/MSc in Biostatistics (University of Iowa), BS in Statistics (Iowa State) Methodologically, she specializes in Bayesian modeling for complex systems, particularly infectious disease dynamics , spatio-temporal analysis , and multiplex imaging data . Collaboratively, she engages with: Nursing (dementia care communication) Neuroradiology (brain tumor classification) Veterinary medicine (Mycoplasma bovis transmission) Public health (vaccine hesitancy) Education (open educational resources) Her 15 most recent publications span epidemiological modeling , healthcare communication , and machine learning applications . Key contributions include: Bayesian SEIR models for behavioral change Network analysis of care coalitions Evaluation of elderspeak communication impacts Development of open-source BayesSEIR R package Statistical methods for imperfect diagnostics Recognitions include the CANSSI Distinguished Postdoctoral Fellowship and Outstanding Teaching Assistant Award . Current projects focus on making biostatistics education more accessible through open resources.