جست‌وجوی استاد و پژوهشگر

Antonius F.W. van der Steenمشاهده پروفایل

استاد

• Biomedical Imaging
• Ultrasound
• Biomechanics
• +۷ مورد دیگر

Professor Antonius F.W. van der Steen is affiliated with Delft University of Technology (TU Delft) in the Faculty of Applied Sciences , specifically the ImPhys department. His career spans roles at Erasmus MC, including leadership in Biomedical Engineering and Experimental Echocardiography. Education: Master in Applied Physics (1989), PhD in Medical Sciences (1994) from Radboud University Medical Centre Research Interests : Focused on biomedical ultrasound, cardiovascular biomechanics, and advanced imaging technologies. Key areas include: Catheter-based imaging systems High frame rate ultrasound for real-time monitoring Ultrasound contrast agent development Biomechanical assessment of atherosclerosis Photoacoustic and intravascular ultrasound integration 2025 Research Trends : Recent publications emphasize computational imaging techniques, microbubble stability optimization, and multimodal diagnostic tools combining ultrasound with CT or photoacoustic modalities. Collaborations : Active in inter-institutional research networks, particularly with Erasmus MC and Delft University of Technology.

• Phonetics
• Speech Perception
• Speech Production
• +۷ مورد دیگر

Bryan Gick is a Professor in the Department of Linguistics at the University of British Columbia's Faculty of Arts, where he directs the UBC Integrated Speech Research Laboratory (ISRL) and co-directs UBC Language Sciences. He holds additional affiliations as a Senior Researcher at Haskins Laboratories in New Haven, CT, and as an Associate Member of the UBC Department of Psychology and UBC School of Audiology & Speech Sciences. His educational background includes a Ph.D. (1999), M.Phil. (1997), and M.A. (1995) from Yale University, and a B.A. (1992) from the University of Pennsylvania. Gick's research centers on understanding how the human body functions as a communication device, focusing on physical mechanisms of movement control and sensation in speech production, perception, and phonetics. His work spans normal and disordered speech, children's speech development, signed languages, singing, and emotional expression. He has pioneered techniques for applying ultrasound imaging to speech research and developed protocols for studying haptic and multimodal perception of speech. Analysis of his recent publications reveals a strong focus on tongue bracing phenomena, speech biomechanics, neurological bases of speech production, and applications to clinical conditions including Parkinson's Disease and Alzheimer's. His research increasingly incorporates cross-disciplinary approaches from neuroscience, biomechanics, and computer modeling. His significant scientific recognition includes: John Simon Guggenheim Memorial Foundation Fellow Fellow of the Royal Society of Canada (FRSC) Fellow of the American Association for the Advancement of Science Gick leads multiple research initiatives including the UBC Integrated Speech Research Laboratory and contributes to the ArtiSynth project for biomechanical simulation of speech. His work connects theoretical linguistics with practical applications in speech pathology, language learning, and human-computer interaction.

Kevin Dalyمشاهده پروفایل

استاد

• Neuroscience
• Sensory Processing
• Motor Neural Networks
• +۵ مورد دیگر

Kevin Daly is a Professor at West Virginia University School of Medicine with appointments in both the Department of Neuroscience and the Rockefeller Neuroscience Institute. He holds the Eberly Family Distinguished Professor in Biology position and maintains his laboratory in the 4200 Life Sciences Building. His research is supported by multiple funding sources including the National Institute on Deafness and Other Communication Disorders (NIDCD) and the National Science Foundation (NSF). Daly's research focuses on understanding how motor neural networks communicate with sensory networks through corollary discharges or predictive motor signals. His laboratory investigates how sensory networks disambiguate environmentally generated stimuli from motor-driven reafference, with particular relevance to understanding sensory-based hallucinations in human brain diseases such as schizophrenia and Parkinson's disease. His work has significant implications for understanding the neural basis of sensory processing disorders. Analyzing his publication record from 2010-2024 reveals a consistent focus on sensory-motor integration, particularly in insect models. His research demonstrates how behaviors like flight affect sensory processing, with numerous publications examining how wing beat frequencies interact with olfactory systems in Manduca sexta and Drosophila. His more recent work has expanded into connectomics using electron microscopy reconstructions to map neural circuits with unprecedented detail. Daly maintains active collaborations with leading neuroscience institutions including Harvard University (The Lee Lab), Columbia University (The Card Lab), and Case Western Reserve University (The Dacks Lab). His laboratory provides state-of-the-art research opportunities for students, featuring advanced techniques like GCaMP imaging, optogenetics, and AI-based behavioral analysis. The Daly lab emphasizes collaborative mentorship, with graduate students expected to train and mentor undergraduate researchers while pursuing their individual development plans. The Daly Laboratory specializes in studying ascending histamine immunoreactive neurons (AHNs) in Drosophila, which represent just 2 pairs among approximately 1,860 ascending neurons connecting the ventral nerve cord to the brain. His team utilizes cutting-edge approaches including 2-photon microscopy, super-resolution fluorescence imaging, and advanced genetic tools to investigate how these circuits process sensory information during behavior. The lab's research environment fosters collaboration both within the laboratory and across institutional boundaries.

Jan G. Bjålieمشاهده پروفایل

استاد

• Neuroinformatics
• Brain Architecture
• Digital Brain Atlases
• +۷ مورد دیگر

Jan G. Bjålie is a Professor and Vice Dean for Research and Innovation at the Faculty of Medicine, University of Oslo. He has led neuroinformatics development since the 1990s and held leadership roles including Head of the Department of Basic Medical Sciences (2009-2016) and Head of Infrastructure Development for EBRAINS. His research bridges neuroanatomy, computational neuroscience, and digital brain atlases. Doctor of Medicine, University of Oslo (1990) Associate Professor (1991), Professor (1997) in Basic Medical Sciences 2016-: First Leader, International Neuroinformatics Coordinating Facility 2017-: Coordinator, Human Brain Project Neuroinformatics 2019-2021: Head, International Brain Initiative Research Interests span neuroinformatics, brain architecture, and digital brain atlases. His work focuses on: Developing standardized frameworks for brain atlas utilization 3D spatial mapping of neural systems Neuroanatomical connectivity in rodent models Integration of multi-modal neuroscience data International collaboration in brain research Computational modeling of brain structure-activity relationships Recent Publications highlight advancements in automated brain imaging registration, developmental brain mapping, cross-cultural neuroscience perspectives, and genetic influences on brain composition. His neuroinformatics tools (e.g., DeepSlice, Waxholm Space, AtOM) enable global standardization of brain data analysis. Leadership Roles include: Vice Dean for Research and Innovation (2023-2026) Infrastructure Development Lead for EBRAINS (2019-) International Brain Initiative Head (2019-2021) Coordinating EU-funded Human Brain Project neuroinformatics Collaborations extend across major brain projects in the USA, Japan, and Europe through initiatives like the International Brain Initiative and ESFRI roadmap projects.

Patrick Brewickمشاهده پروفایل

استادیار

• Data Analytics
• System Identification
• Structural Health Monitoring
• +۱۰ مورد دیگر

Patrick Brewick is an Assistant Professor in the Department of Civil and Environmental Engineering and Earth Sciences at the University of Notre Dame. His research bridges data analytics, mechanics, and computational modeling to address challenges in structural resilience and material behavior under extreme conditions. Ph.D., Columbia University (2014) M.S., Civil Engineering and Engineering Mechanics, Columbia University (2010) B.S., Civil Engineering, University of Notre Dame (2009) Professor Brewick’s work focuses on transforming noisy or incomplete data into accurate predictive models. Key research areas include: System Identification : Uncovering physics of seismic protection systems. Uncertainty Quantification : Developing Bayesian frameworks for model calibration. Damage Detection : Identifying nonlinear structural transitions. Microstructural Modeling : Investigating corrosion and material heterogeneity. Hybrid Modeling : Balancing high- and low-fidelity simulations. Wind Energy Applications : Using distributed fiber optics for turbine monitoring. His publications span disciplines like structural mechanics, materials science, and biomedical engineering, emphasizing multi-fidelity approaches and probabilistic methods. Current projects address infrastructure resilience against climate change, naval structural reliability, and microstructural impacts on corrosion. The Brewick Group collaborates extensively, offering open-source tools and inviting partnerships. Students in his lab, such as Ph.D. candidates Reza Farzad and Jichuan Tang , explore cutting-edge applications in structural dynamics and material modeling. Before Notre Dame, Prof. Brewick conducted research at the U.S. Naval Research Laboratory, focusing on predictive modeling for heterogeneous systems, including marine structures and brain tissue mechanics.

• Bone Density
• Bone Strength
• Quantitative Computed Tomography
• +۳ مورد دیگر

Vikram Vinod Shanbhogue is a Clinical Associate Professor at the University of Southern Denmark, affiliated with the Department of Regional Health Research and the Research Unit of Endocrinology at Esbjerg and Grindsted Hospital. His research focuses on metabolic bone disorders using advanced imaging techniques. Primary research interests include: Assessment of bone density, strength, and microarchitecture Clinical applications of quantitative computed tomography (QCT) and dual-energy X-ray absorptiometry (DXA) Bone health in genetic disorders (Marfan syndrome), diabetes, and metabolic conditions Bone remodeling biomarkers and turnover mechanisms His recent publications (2019-2024) demonstrate consistent focus on bone pathology in special populations, employing methodologies ranging from randomized controlled trials to cross-sectional biomarker studies. Research frequently incorporates advanced imaging modalities and explores clinical applications for mobility-limited, pediatric, and genetically predisposed patients.

Lauren Ellmanمشاهده پروفایل

استاد

• Schizophrenia
• Psychosis
• Depression
• +۷ مورد دیگر

Lauren Ellman is a Professor in the Clinical area of the Psychology and Neuroscience Department at Temple University's College of Liberal Arts. Her research focuses on pre- and perinatal influences on neurodevelopment and risk for major mental disorders like schizophrenia and depression, integrating gene-environment interactions, psychoneuroimmunology, and multimodal imaging. Education : B.A. in Philosophy and Psychology (Tulane University); Ph.D. in Clinical Psychology with Health Psychology minor (UCLA) Her ongoing studies include NIMH-funded projects examining prenatal stress, inflammation, and hypoxia effects on neurodevelopmental trajectories, collaborations with U.S. and Finnish birth cohorts, and tools for early psychosis risk detection. Current research also addresses adolescent risk factors using clinical and neuroimaging methods. Scientific Awards : NIMH-funded predoctoral fellowship (UCLA) NIMH-funded National Research Service Award (NRSA) postdoctoral fellowship (Columbia University) Editorial board member, Schizophrenia Bulletin Dr. Ellman's work emphasizes a lifespan approach to psychopathology, aiming to identify at-risk individuals and develop early interventions. She supervises students in therapy modalities and neurodevelopmental research.

Yihao Liuمشاهده پروفایل

استادیار

• Medical Image Analysis
• Image Registration
• Deep Learning
• +۳ مورد دیگر

Yihao Liu serves as Research Assistant Professor in Vanderbilt University's School of Engineering, Department of Electrical and Computer Engineering, focusing on clinically relevant image analysis for personalized treatment strategies and large-scale medical data interpretation. His work bridges engineering and clinical applications through advanced computational methodologies. Education: PhD in Electrical and Computer Engineering, Johns Hopkins University (May 2024) Dr. Liu's research spans medical image analysis, deformable registration, deep learning, and computer vision with applications in CT, MRI, and OCT imaging. He develops AI-driven tools for pulmonary nodule diagnosis, MS lesion analysis, body composition assessment, and dermatological imaging, emphasizing clinical translation and multi-modal data fusion. His 2024-2025 publications reveal concentrated innovation in diffusion models for field-of-view extension, bi-directional lesion synthesis, and unsupervised registration techniques, demonstrating leadership in foundational registration models and longitudinal analysis for precision medicine. Dr. Liu directs the Vanderbilt Lab for Immersive AI Translation (VALIANT) and collaborates with the Medical-image Analysis and Statistical Interpretation Lab (MASI) under VISE Affiliate Bennett Landman, PhD. He holds the Stevenson Chair in Electrical and Computer Engineering and participates in NIH grant writing initiatives through Vanderbilt's medical partnerships.

Mohammad Amir Owrangiمشاهده پروفایل

دانشیار

• Radiation Oncology
• Medical Physics
• Brachytherapy
• +۳ مورد دیگر

Mohammad Amir Owrangi serves as Associate Professor in Radiation Oncology at Baylor College of Medicine (Houston) and University of Texas Southwestern (Dallas), with prior appointments as Assistant Professor at both institutions and the University of Toronto. His expertise bridges medical physics and clinical radiation oncology, focusing on advancing precision radiotherapy through technological innovation. His academic foundation includes a BSc and MSc in Physics and Radiation-Medicine Engineering from Shiraz University (Iran), followed by a PhD in Biomedical Engineering from The University of Western Ontario (Canada), and a CAMPEP-accredited residency in Therapeutic Radiologic Medical Physics at University of Michigan Health System. Dr. Owrangi's research centers on solving critical challenges in image-guided radiotherapy, particularly MRI-based treatment planning for gynecological cancers. His work pioneers synthetic CT generation using deep learning to eliminate CT simulation needs, optimizes brachytherapy applicators for cervical cancer, and develops metal artifact reduction techniques. Recent publications demonstrate increasing integration of AI methods to improve dosimetric accuracy and workflow efficiency in radiation therapy. Analysis of his 15 most recent publications (2017-2024) reveals three dominant research thrusts: (1) MRI-only radiotherapy workflows with synthetic CT generation using deep learning/GANs, (2) brachytherapy optimization for cervical cancer through applicator design and dosimetry, and (3) artifact reduction in multi-modal imaging. His work consistently targets clinical translation, with 70% of recent publications focusing on gynecological applications. Scientific Awards: No awards explicitly mentioned in source materials Academic advising and research grant details were not provided in available documentation. His collaborative network spans Baylor College of Medicine, UT Southwestern, University of Toronto, and international institutions including Shiraz University and University of Western Ontario, with frequent co-authorship among medical physicists and radiation oncologists. While specific laboratory infrastructure isn't detailed, his research requires advanced capabilities in MRI/CT image processing, Monte Carlo simulation, and deep learning development, suggesting access to high-performance computing resources and clinical imaging datasets at his affiliated institutions.

Alessandra Ainsworthمشاهده پروفایل

استادیار

• Reproductive Endocrinology
• Infertility
• Fertility Preservation
• +۵ مورد دیگر

Dr. Alessandra (Ali) Ainsworth is an Assistant Professor in the Department of Obstetrics and Gynecology at Mayo Clinic , specializing in Reproductive Endocrinology and Infertility . She serves as the IVF Director for the Mayo Clinic Division of Reproductive Endocrinology and Infertility. Medical School: University of Kansas Residency: Mayo Clinic (Obstetrics and Gynecology) Fellowship: Mayo Clinic (Reproductive Endocrinology and Infertility) Master's Degree: Biomedical Science (Mayo Clinic) Her research program focuses on long-term health outcomes after infertility and novel approaches to fertility care , particularly emphasizing patient experience improvement and expanded access to reproductive technologies . Clinical expertise spans Infertility , Fertility Preservation , and Complex Fertility Treatments . Recent publications analyze: Medical implications of ART in comorbid populations (pulmonary disease, epilepsy) Embryo development dynamics and attrition rates Reproductive immunology and hormonal biomarkers Societal fertility trends and pandemic impacts Imaging protocols for ovarian assessment Patient anxiety reduction techniques in fertility procedures Scientific contributions recognized through: Mayo Brothers Distinguished Fellowship Award (2021) Ann Harris Research Award (2018) Best Resident Educator in OB/GYN (2017) Daniel K Roberts Medical Student Award (2014) Membership in Alpha Omega Alpha and Arnold P. Gold Humanism in Medicine Society Professional leadership includes: Scientific Advisory Board (Flo Health) Institutional Review Board member OB/GYN Innovation Task Force participation Thesis Advisory Committee at Mayo Clinic Graduate School

• Structural Engineering
• Seismic Engineering
• Hazard Mitigation
• +۴ مورد دیگر

James M. LaFave is a Professor of Civil Engineering at the University of Illinois Urbana-Champaign (UIUC), affiliated with the Grainger College of Engineering and the Department of Civil & Environmental Engineering (CEE). He holds the title of CEE Excellence Faculty Scholar and currently serves as Co-Chair of the Illinois CEE Structures Group (since 2023). Prior roles include Associate Dean for Facilities & Capital Planning (2020-21), Director of CEE Education Programs for the Zhejiang University-UIUC Joint Institute (2018-20), and CEE Associate Head (2016-20). He has also held visiting professorships at the University of Washington (2007-08) and served as a NIST Associate (2015). Education: B.S. (1986) and M.S. (1987) in Civil Engineering from UIUC; Ph.D. (1997) in Civil (Structural) Engineering from the University of Michigan. Professional experience includes consulting roles at Wiss, Janney, Elstner Associates and Sargent & Lundy Engineers, and licensure as a Professional Engineer in Michigan. Research focuses on structural connections/joints, seismic and wind hazard mitigation, bridge engineering, and high-performance concrete. Notable projects include studies on integral abutment bridges, concrete connection behavior, and machine learning applications in structural assessment. Research Highlights: Integral abutment bridge dynamics, seismic retrofit strategies, and masonry system performance. Editorial Roles: Founding Co-Editor-in-Chief of Journal of Building Engineering ; Editorial Board member of Engineering Structures . Awards: ACI Wason Medal (2009), Martin P. Korn Award (2023), and multiple teaching honors. Teaching responsibilities include structural design courses for undergraduate and graduate students, alongside advising the UIUC CEE Steel Bridge Team. Professional service includes leadership roles in ACI committees (e.g., Joint Committee 352 on concrete joints) and editorial judging for engineering awards.

• Neuroscience
• Pharmacology
• Toxicology
• +۱۱ مورد دیگر

Assoc.-Prof. Dr. Marietta Zille is an Associate Professor at the University of Vienna , Faculty of Life Sciences, Department of Pharmaceutical Sciences. She leads the Cerebrovascular Pharmacology research group, focusing on novel therapies for stroke, brain hemorrhage, vascular dementia, and brain aging. Her work integrates advanced technologies like deep learning and in vitro models to study neuronal and vascular cell death mechanisms. University of Vienna, Faculty of Life Sciences Department of Pharmaceutical Sciences Cerebrovascular Pharmacology & Toxicology Research Interests include: Neurodegenerative disease etiology Stroke and hemorrhage pathophysiology Blood-brain barrier aging Ferroptosis and necroptosis Marine bioactives for neuroprotection Her recent publications span axonal degeneration (2025), blood-brain barrier aging (2025), microglial activation (2025), and SARS-CoV-2 vascular pathology (2024). She supervises Master’s thesis projects in cell culture, in silico modeling, and cerebrovascular research. Grants include Austrian Academy of Sciences (2024-2027), Hochschuljubiläumsfonds (2023), and BMBF projects (2018-2019).

Andreas K. Engelمشاهده پروفایل

استاد

• Neuroscience
• Neurophysiology
• Brain-Computer Interfaces
• +۴ مورد دیگر

Prof. Dr. med. Andreas K. Engel serves as Director of the Institute of Neurophysiology and Pathophysiology at the Center for Experimental Medicine, University Medical Center Hamburg-Eppendorf (UKE). His research focuses on neural oscillations, brain dynamics, and neurophysiological mechanisms in health and disease, particularly employing EEG, MEG, and brain stimulation techniques like tACS to study cognitive processes, motor control, and multisensory integration. Current affiliation: Institute of Neurophysiology and Pathophysiology, UKE Academic rank: Professor Email: ak.engel@uke.de Key research areas include: Neural oscillations and synchronization Neurodegenerative disease mechanisms (Parkinson's) Brain-computer interface development Neural coupling during social interactions Cortical network dynamics Neuromodulation techniques Recent publications demonstrate expertise in analyzing multisensory integration, phase-amplitude coupling, and applying stimulation methods to modulate cortical activity patterns. His work bridges computational neuroscience with clinical applications in movement disorders and cognitive impairments.

Guy Emersonمشاهده پروفایل

پژوهشگر ارشد

• Natural Language Processing
• Machine Learning
• Computational Linguistics
• +۳ مورد دیگر

Dr Guy Emerson is a Departmental Early-Career Academic Fellow and Affiliated Lecturer in the Department of Computer Science and Technology at the University of Cambridge. He also serves as a College Lecturer at Gonville & Caius College and Executive Director of Cambridge Language Sciences. His research focuses on computational linguistics, particularly functional distributional semantics, probabilistic models, and machine learning applications in natural language processing. He explores how computational models can illuminate linguistic knowledge and advance artificial intelligence. His work integrates formal linguistic theory with data-driven methods, addressing challenges like hypernymy detection, cross-linguistic syntax, and semantic representation. Recent projects include probing lexical semantics limitations, developing scalable distributional models, and leveraging visual data for semantic analysis. Key themes include natural language processing, machine learning, and cross-linguistic studies, with publications in top venues like SemEval workshops and computational linguistics journals. His contributions bridge formal syntax, probabilistic semantics, and scalable computational techniques, emphasizing both theoretical and applied outcomes. Emerson collaborates extensively on interdisciplinary initiatives through Cambridge Language Sciences, fostering connections between linguistics, computer science, and cognitive science. His research has implications for improving NLP systems, semantic modeling, and cross-linguistic computational frameworks.

Mike Mamalakisمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Deep Learning
• Medical Imaging
• +۴ مورد دیگر

Mike Mamalakis is a Senior Research Associate at the University of Cambridge, affiliated with the School of Clinical Medicine and Department of Computer Science and Technology . His research focuses on applied and theoretical AI, particularly in Deep Learning , Multi-Modal AI , and eXplainable AI for biomedical and healthcare applications. Research Themes : Medical imaging, neuroscience, brain tumors, Alzheimer's disease, and foundation models. Collaborations : University of Sheffield (Richard Clayton, Andriew Shift, George Panoutsos), University of Cambridge (Pietro Lio, Murray Graham, John Suckling), and Cancer Research UK Cambridge Centre. His recent work involves developing predictive models for neuroscience using multimodal data (text, imaging, phenotyping, genomics) and applying gradient-based explainability methods to study brain tumors. Publications highlight AI-driven biomarker discovery in COVID-19 , pulmonary hypertension , and cardiac arrhythmias . Current affiliations include the School of Clinical Medicine and CRUK Cambridge Centre. Contact : mm2703@cam.ac.uk | Room GC01, William Gates Building, University of Cambridge.