جست‌وجوی استاد و پژوهشگر

Jason K. Molitorisمشاهده پروفایل

دانشیار

• Radiation Oncology
• Genitourinary Cancers
• Gastrointestinal Cancers
• +۵ مورد دیگر

Dr. Jason K. Molitoris serves as Associate Professor and UMMC Medical Director in the Department of Radiation Oncology at the University of Maryland, based at the Marlene and Stewart Greenebaum Comprehensive Cancer Center. His clinical expertise spans genitourinary, gastrointestinal, central nervous system, and hematologic malignancies, with a focus on implementing advanced radiation technologies to optimize treatment efficacy and minimize side effects. His educational background includes: Bachelor of Science in Biology, Summa cum laude, Phi Beta Kappa, The College of William and Mary MD/PhD through Medical Scientist Training Program, Case Western Reserve University School of Medicine (Alpha Omega Alpha) Internal Medicine Internship, Greater Baltimore Medical Center Radiation Oncology Residency and Chief Residency, University of Maryland Medical Center Dr. Molitoris' research integrates basic science (cell death mechanisms in leukemia/lymphoma) with clinical applications of proton therapy, brachytherapy, and hyperthermia. His work emphasizes novel radiosensitization approaches, clinical trial development, and translational studies to improve outcomes in prostate, gastrointestinal, and CNS cancers while reducing treatment toxicity. Analysis of his 15 most recent publications reveals a strong clinical outcomes focus across brain metastases, lung, breast, and prostate cancers. His work frequently utilizes multi-institutional collaborations and national databases to evaluate prognostic factors, treatment patterns, and advanced technologies like proton therapy, with consistent emphasis on balancing efficacy with quality-of-life preservation. His awards include: Lynn Sage Breast Cancer Symposium Scholar Award RSNA Roentgen Resident/Fellow Research Award International Congress for Hyperthermic Oncology New Investigator Travel Award ASCO/AACR Research Fellow designation American Radium Society Travel Grant Award ASTRO Advocacy Day Travel Grant H.E.R.O. Award nomination University of Maryland Chief Resident distinction Dr. Molitoris actively develops clinical trials through AACR/ASCO workshops and mentors residents, though specific grant details and student advisees aren't documented. His national presentations reflect leadership in radiation oncology innovation, particularly in thermal therapy and proton applications. He operates within the Marlene and Stewart Greenebaum Comprehensive Cancer Center ecosystem, collaborating with multidisciplinary teams across the Maryland Proton Treatment Center and leveraging institutional resources for translational research in advanced radiation modalities.

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.

Daniel T. Kawakyu-O'Connorمشاهده پروفایل

دانشیار

• Emergency Radiology
• Neuroimaging
• Breast Cancer Imaging
• +۳ مورد دیگر

Daniel T. Kawakyu-O'Connor, M.D. is an Associate Professor in the Department of Imaging Sciences at the University of Rochester Medical Center (URMC), where he serves as Chief of the Division of Emergency Imaging since 2017. His clinical expertise spans emergency radiology, trauma imaging, and advanced stroke imaging modalities. Education: Dartmouth College (Biophysical Chemistry & Studio Art), Tulane University School of Medicine (MD) Certifications: American Board of Radiology Training: Residency and Fellowship at URMC, Internal Medicine Internship at Ochsner Medical Foundation His research focuses on advanced imaging techniques for acute stroke, spinal trauma, and breast cancer diagnostics, particularly cone-beam breast CT . Institutional work includes physician wellness, antiracism initiatives, and medical education reform. He has expanded the emergency imaging division from 1 to 8 faculty members with diverse subspecialties. Recent publications analyze vascular trauma imaging , spinal cord compression , and medical device complications . Collaborative work with institutions across radiology subspecialties demonstrates his interdisciplinary approach. He actively participates in university governance through the Faculty Senate and Medical Faculty Council.

• Monte Carlo Methods
• Parallel Computing
• Statistical Analysis
• +۳ مورد دیگر

Kari Heine is a Lecturer in the Department of Mathematical Sciences at the University of Bath. Their research focuses on computational methods, parallel algorithms, and statistical analysis, contributing to the UN Sustainable Development Goals. Key affiliations include the EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa) and the Centre for Mathematics and Algorithms for Data (MAD). Research interests include Monte Carlo methods, parallel computing, and algorithm development for data science applications. Recent work involves particle filtering techniques, multi-modal likelihood inference, and environmental noise analysis using machine learning. Heine leads the active project 'On-line drill system parameter estimation and hazardous event detection' funded by UK industry. Their research outputs span statistical computing, computational biology, and environmental signal processing.

Yang Zhangمشاهده پروفایل

عضو هیئت علمی

• Aerospace Engineering
• Fluid Dynamics
• Noise Reduction
• +۳ مورد دیگر

Yang Zhang is a Research Assistant Professor at the Illinois Institute of Technology (Illinois Tech), affiliated with the Department of Mechanical, Materials, and Aerospace Engineering within the Armour College of Engineering. His research focuses on experimental and computational aerodynamics, particularly in noise reduction mechanisms, flow control, and advanced measurement techniques such as particle image velocimetry (PIV). Key research interests include slat noise mitigation in aircraft systems, turbulent flow dynamics, and the application of smart materials and spectral analysis methods. Zhang’s work addresses challenges in high-lift systems, supersonic cavity flows, and aerodynamic efficiency optimization. His publications highlight contributions to noise prediction, flow visualization techniques, and passive/active control strategies for aerodynamic systems. Recent studies emphasize the integration of porous materials and dielectric elastomers for acoustic liner design, alongside advancements in data assimilation frameworks for turbulent boundary layer analysis.

Ali Abdollahzadehمشاهده پروفایل

پژوهشگر ارشد

• Medical Image Analysis
• Biophysics
• Diffusion MRI
• +۶ مورد دیگر

Ali Abdollahzadeh is an Academy Research Fellow at the A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, within the Faculty of Health Sciences. His research focuses on medical image analysis and biophysics, particularly in neuroimaging techniques like diffusion MRI and electron microscopy. He develops advanced computational tools for analyzing white matter ultrastructures and neurovascular interactions. Key projects include studying the role of meningeal lymphatics in neuroinflammation and migraine mechanisms, as well as creating open-source software like SproutAngio and gACSON for bioimage informatics. His work bridges biophysics, computational neuroscience, and clinical applications. Recent studies explore axonal remodeling under stress, neurovascular dynamics, and deep learning applications in neurological disease analysis. He collaborates with the Computational Neuroanatomy Lab and Multiscale Imaging Group, advancing interdisciplinary research in brain imaging and neurodegenerative disorders. Publications highlight innovations in segmentation algorithms, 3D imaging techniques, and translational studies linking microscopic findings to clinical outcomes. His research aims to enhance understanding of CNS structure-function relationships and improve diagnostic tools through advanced imaging methodologies.

Ghislain Fournyمشاهده پروفایل

مدرس

• Quantum Mechanics
• Game Theory
• Database Systems
• +۶ مورد دیگر

Ghislain Fourny is a Lecturer and senior scientist in the Department of Computer Science at ETH Zurich. His research spans quantum foundations, game theory, and database systems. He develops deterministic models merging game theory into quantum physics, proposing non-Nashian solution concepts to address quantum paradoxes. He co-designed the JSONiq query language and leads the RumbleDB project for large-scale data querying. A recipient of multiple teaching awards including the Golden Owl and ETH Medal, he advises numerous students on topics ranging from quantum theory to database systems. His work bridges theoretical physics, computer science, and mathematics, aiming to reconcile determinism with quantum mechanics through game-theoretic models. Education : Holds a Master's in Quantum Information (2007) and a PhD in Computer Science (2011). His early career included pioneering work on XBRL standards and XQuery implementations. Research Themes : Non-Nashian game theory: Fixpoint equilibria avoiding Grandfather paradoxes, Pareto optimality. Quantum foundations: Deterministic models challenging free-choice assumption, spacetime games integrating special relativity. Database systems: JSONiq language design, RumbleDB for scalable querying of heterogeneous data. Teaching Contributions : Courses include Big Data for Engineers, Information Retrieval, and Information Systems for Engineers. His open-access Big Data textbook is widely used in universities. Recognition : Over 20 awards including the 2023 VIS Teaching Award, ETH Medal (2000), and multiple top ranks in international mathematics competitions since 1993.

Christian Schroerمشاهده پروفایل

استاد

• X-ray Microscopy
• X-ray Optics
• Synchrotron Radiation
• +۵ مورد دیگر

Christian Schroer is a Professor at the University of Hamburg and Leading Scientist at DESY, Germany's national laboratory for particle physics and photon science. He serves as Co-Spokesperson of the Cluster of Excellence 'Understanding Written Artefacts' (UWA) and Head of the High Performance Lab. His research focuses on X-ray microscopy, X-ray optics, and synchrotron radiation applications across physics, chemistry, and cultural heritage preservation. He holds a doctoral degree in mathematical physics and has held academic positions at TU Dresden and RWTH Aachen University. Education & Career: PhD in Physics (1995), University of Cologne Postdoctoral Fellowships: University of Maryland (USA), Research Center Jülich Professor at TU Dresden (2006–2014), University of Hamburg (since 2014) Research Interests: X-ray imaging techniques, synchrotron and free-electron laser applications, nanotechnology, and cultural heritage projects like tomographic analysis of enclosed cuneiform tablets. His work bridges physics, materials science, and interdisciplinary collaborations. Key Projects: Leadership of PETRA III scientific programme and conceptual design of PETRA IV Development of X-ray ptychography and multi-beam imaging Cultural heritage projects involving high-resolution tomography Labs & Teams: Directs the High Performance Lab at DESY and co-founded Helmholtz Imaging, a platform for advanced imaging strategies in data science.

• Magnetic Resonance Imaging
• Biophysics
• Medical Imaging Technology
• +۳ مورد دیگر

Prof. Axel Haase is a Senior Professor at the University of Würzburg, affiliated with the Faculty of Physics and Astronomy and the Department of Experimental Physics V . He leads the Chair of Experimental Physics (Biophysics) and is a member of the Magnetic Resonance Imaging research group within Experimental Physics 5. His work focuses on advanced imaging technologies, including Magnetic Particle Imaging (MPI) and Traveling Wave MPI, with applications in biophysical and medical research. He is also involved in projects like Rotational Drift Spectroscopy and Nano-Optics. Research interests span experimental physics, biophysics, and medical engineering, with a strong emphasis on developing imaging modalities for biomedical applications. His team collaborates on interdisciplinary projects, such as the 18th International Conference on Magnetic Resonance Microscopy (ICMRM 2025) . Contact details include his office at Building P1, Room F-077a and phone number +49 931 31-84780 . No specific scientific awards or grants are listed in the provided text. Advising details are not explicitly mentioned, though the group hosts PhD and graduate students. The laboratory environment emphasizes cutting-edge experimental setups for magnetic resonance and particle imaging technologies.

Marcel Greuterمشاهده پروفایل

استاد

• Medical Physics
• Computed Tomography
• Radiation Safety
• +۳ مورد دیگر

Dr. Marcel Greuter is a Professor and Head of Medical Physics at the Faculty of Medical Sciences, University of Groningen. He holds additional roles including Visiting Scientific Staff Member at University Twente's Robotics and Mechatronics department, Medical Physicist at OZG Scheemda, and Radiation Protection Expert. He actively participates in multiple committees such as the Radiation Safety Committee of the Dutch Association of Medical Physics (NVKF) and the Dutch Society of Radiology's Imaging Techniques Committee. His research focuses on Medical Physics applications in Computed Tomography (CT), Radiation Safety, Cancer Screening Modelling, and Biomedical Engineering. Key projects include optimizing CT protocols for pediatric imaging and evaluating cost-effectiveness of screening strategies in cervical and breast cancers. His work spans both technical advancements in imaging technology and their clinical implications. Recent publications emphasize innovations in photon-counting CT for iodine detection, development of cerebral perfusion phantoms, and intraoperative CT applications in urology. His articles reflect a balance between methodological advancements and translational research impacting healthcare economics and patient outcomes. Marcel Greuter is deeply engaged in academic governance, leading educational programs as Chair of the Biomedical Engineering Program Committee at the Faculty of Science and Engineering. He also contributes to ethical and regulatory oversight through roles on the Medical Ethics Committee (METc) and Radiation Safety bodies.

• Medical Imaging
• Computer Vision
• Deep Learning
• +۴ مورد دیگر

Dr Abdullah Nazib is a Research Fellow at Queensland University of Technology (QUT) in the Faculty of Engineering, School of Electrical Engineering & Robotics. His research focuses on applying advanced computational techniques to medical imaging challenges, particularly in cancer detection and treatment planning. His research interests include: Medical image registration and segmentation Deep learning architectures for healthcare applications 3D medical image analysis Prostate cancer detection and grading Organ segmentation for radiation therapy Radiomics-based diagnostic systems Analysis of Dr Nazib's publication history reveals a clear evolution from general computer vision research toward specialized medical applications. His recent work demonstrates significant contributions to uncertainty quantification in medical image segmentation and multimodal learning approaches for diagnostic imaging. The 2024 publications particularly highlight his focus on clinically relevant applications with immediate potential impact on cancer diagnosis and treatment planning. His collaborative research network includes strong partnerships with Dr Fookes, Dr Perrin, and other members of QUT's biomedical imaging group, reflecting an interdisciplinary approach that bridges computer science, engineering, and clinical medicine to develop practical AI solutions for healthcare challenges.

Jose Manuel Dominguez Alonsoمشاهده پروفایل

پژوهشگر

• Earth Physics
• Computational Fluid Dynamics
• Marine Engineering
• +۴ مورد دیگر

Jose Manuel Dominguez Alonso is a researcher at the University of Vigo , affiliated with the Faculty of Sciences and the Marine Research Center . His work focuses on Earth Physics and Smoothed Particle Hydrodynamics (SPH) applications in marine and renewable energy systems. He is part of the FA9 EphysLab research group at the Ourense campus. Education: PhD in Applied Physics from the University of Vigo (2014) under advisors Dr. Moncho Gómez Gesteira and Dr. Alejandro Jacobo Cabrera Crespo. His research explores fluid dynamics , off-shore wind turbines , wave energy converters , and fluid-structure interaction . He has developed DualSPHPhysics for high-performance computing in marine environments. His recent articles (2024-2025) emphasize teaching numerical modeling to students, 3D hydrodynamic analysis , and coupled simulation techniques . His work bridges computational methods with real-world marine engineering challenges like coastal protection and renewable energy optimization.

Erica Ribeiro Polycarpo Macedoمشاهده پروفایل

دانشیار

• Elementary Particle Physics
• Experimental High Energy Physics
• Instrumentation in High Energy Physics

Erica Ribeiro Polycarpo Macedo serves as an Associate Professor at the Institute of Physics, Federal University of Rio de Janeiro (UFRJ) since 2004, holding a CNPq Research Productivity Scholarship Level 2. Her office is located in room A-310 with contact via poly@if.ufrj.br and +55 (21) 3938-7733. Education: Bachelor's Degree in Physics, UFRJ Master's Degree in Physics, UFRJ PhD in Physics, UFRJ/CERN (sandwich modality) Her research focuses on Elementary Particle Physics , Experimental High Energy Physics , and Instrumentation in High Energy Physics , building on early work at the Brazilian Center for Physics Research (2002-2004). She contributes to fundamental particle research through experimental methodologies and detector development. Scientific Awards: CNPq Research Productivity Scholarship Level 2 Dr. Macedo maintains active research supported by CNPq funding, though specific grants and student advisement details are not publicly documented in the source materials. Her career demonstrates sustained commitment to advancing high-energy physics within Brazil's academic infrastructure.

Jin Woo Songمشاهده پروفایل

دانشیار

• Navigation and Sensor Systems
• Control Theory
• Estimation Theory
• +۷ مورد دیگر

Jin Woo Song is an Associate Professor in the Department of Artificial Intelligence and Robotics at Sejong University's School of Intelligent Mechatronics Engineering. He has held academic positions at Seoul National University and Hoseo University prior to joining Sejong University in 2017. His professional experience also includes serving as CTO/COO at Microinfinity Co., Ltd. from 2004-2014. Currently, he holds multiple leadership roles including Director of Sejong Enterprise Support Foundation, Director of SW-AI Convergence Center, and Provost of Sejong University. Dr. Song received his B.S., M.S., and Ph.D. in Control and Instrumentation Engineering/Electrical Engineering from Seoul National University. His educational background laid the foundation for his expertise in navigation systems and control theory. Dr. Song's research focuses on navigation and sensor systems, control theory, and estimation theory with applications in unmanned systems. His work spans MEMS inertial sensor technologies, Kalman filtering techniques, optimal and robust control theories, and fault detection algorithms. His research has significant applications in unmanned aircraft systems, autonomous vehicles, robotics, and military intelligence systems. His recent publications (2023-2025) demonstrate continued innovation in navigation systems, with emphasis on fault tolerance, sensor fusion, and improved positioning accuracy in challenging environments. His work shows strong trends toward integrating multiple sensor modalities and developing robust algorithms for real-world navigation challenges. Best student paper award, NAECON2000 (IEEE, National Aerospace and Electronics Conference), USA, 2000 Ministry Award, 'IT R&D Engineer of the Year', Ministry of Information and Communication, Republic of Korea, 2005 Best Presentation Award, ICASS 2015, 2015 Best Paper Award, KIEE Conference, 2019 Distinguished Teaching Award, Sejong University, 2021 Distinguished Research Award, Sejong University, 2022 Distinguished Professor, Sejong University, 2024 Dr. Song has served as Editor-in-Chief for ICROS journal and holds editorial positions for multiple prestigious journals including the International Journal of Aeronautical and Space Sciences. He has been actively involved in numerous research grants and industry collaborations, including a recent academic-industrial partnership with Hanwha Systems. As Vice-President of The Institute of Control, Robotics and Systems (ICROS) and various other professional organizations, he plays a significant role in shaping research directions in his field. He leads the Intelligent Navigation and Control Systems Lab at Sejong University, where his team develops cutting-edge navigation sensors and systems, optimal controllers for autonomous systems, and embedded systems for reliable navigation and control. The lab's work has direct applications in unmanned aircraft systems, autonomous vehicles, robotics, and military intelligence systems.

Shuo Zhouمشاهده پروفایل

مدرس

• Interpretable Machine Learning
• Medical Image Analysis
• Statistical Learning Theory

Dr. Shuo Zhou is a Lecturer in Machine Learning at the University of Sheffield's School of Computer Science, holding dual roles as Deputy Head of AI Research Engineering. He specializes in interpretable machine learning for medical imaging and neuroimaging analysis, with contributions to open-source tools like PyKale. Education: MSc Advanced Computer Science (2017), University of Sheffield PhD in Machine Learning (2022), University of Sheffield Research Interests: Interpretable ML methods for clinical decision-making Medical image analysis (cardiac MRI, fMRI) Statistical learning theory with domain adaptation Grants & Leadership: Co-PI: EPSRC grant (£445k) for neuroimaging biomarkers in chronic pain (2023-2025) PI: Turing 2.0 project (£20k) for machine learning infrastructure (2022-2023) Labs & Teams: Core developer of PyKale open-source library Member of Machine Learning research group