جستجوی استاد راهنمای دانشگاهی

Olga Sorkine-Hornung is a Professor of Computer Science at ETH Zurich and head of the Institute of Visual Computing. She leads the Interactive Geometry Lab, focusing on theoretical and practical advancements in digital content creation, geometry processing, and shape modeling. Current position: ETH Zurich, Department of Computer Science Previous roles: Courant Institute (NYU), Technical University of Berlin Education: BSc and PhD from Tel Aviv University, postdoc at TU Berlin Her research spans shape representation, digital fabrication, computer animation, and fundamental geometry processing. Key contributions include Laplacian surface editing, as-rigid-as-possible deformation, and generalized winding numbers. She works on applications in VR, AR, and autonomous systems. Awards include Test of Time Awards (2024), ACM Fellow (2020), ERC Consolidator Grant (2020), and EUROGRAPHICS Young Researcher Award (2008). She has supervised numerous students and co-developed software libraries like libigl and Instant Meshes . Co-chair roles for SIGGRAPH, Eurographics, and Pacific Graphics Editorial board member for ACM Transactions on Graphics and other journals Keynote speaker at VMV, CVPR, and SIAM conferences Her work bridges mathematical rigor with practical implementation, advancing computer graphics and geometry processing through intuitive algorithms that maintain surface detail while enabling efficient computation.

• Digital Content Creation
• Geometry Processing
• Shape Representation and Editing
• +۵ مورد دیگر

Prof. Dr. Dennis Säring is a faculty member at the University of Applied Sciences Wedel , specifically affiliated with the School of Engineering. His academic and research activities focus on Deep Learning , Medical Image Analysis , and applications of Artificial Intelligence in healthcare and biomedical imaging. He has led seminars on Deep Learning topics and supervised student projects in Autonomous Driving at Audi's AADC 2018 competition. Research Highlights : Cardiovascular imaging, forensic age estimation via MRI, neural network-based bone segmentation, and cerebrovascular aneurysm analysis. Technical Expertise : Cardiac MRI, 3D/4D image processing, parametric mapping, and spatiotemporal data fusion. His recent publications (2018-2023) emphasize 3D MR segmentation for age assessment, CMR strain analysis in athletes, and T1/T2 mapping for myocarditis. Key collaborations include institutions like the University Medical Center Hamburg-Eppendorf and Wedler Hochschulbund, with funding for autonomous vehicle research. While no explicit scientific awards are listed, his work spans clinical cardiology, forensic radiology, and AI-driven medical diagnostics.

• Deep Learning
• Medical Image Analysis
• Artificial Intelligence
• +۵ مورد دیگر

Cherie Kagan serves as the Stephen J. Angello Professor at the University of Pennsylvania, holding primary appointment in the Department of Electrical and Systems Engineering within the School of Engineering and Applied Science, with secondary appointments in Chemistry and Materials Science and Engineering. Her interdisciplinary research bridges chemistry, materials science, and electrical engineering to develop novel functional materials and devices that integrate optical, electrical, magnetic, mechanical, and thermal properties. Professor Kagan's research group combines the flexibility of chemical synthesis and bottom-up assembly with top-down fabrication techniques to design innovative nanomaterials. They employ advanced characterization methods including spatially- and temporally-resolved optical spectroscopies, AC/DC electrical measurements, electrochemistry, and various microscopy techniques. Her recent work demonstrates particular strength in colloidal nanocrystals and quantum dots for applications in quantum information science, sensing technologies, and energy conversion devices. Scientific Recognition Induction to the American Academy of Arts and Sciences (2025) IEEE Fellow (2024) for contributions to colloidal nanocrystals and their integration in optical and electronic devices George H. Heilmeier Faculty Award for Excellence in Engineering (2024-25) Humboldt Research Award Fellowship (2024) MRS Fellow for distinguished research accomplishments in materials science National Academy of Inventors Fellow for innovation in nanomaterials Professor Kagan actively mentors PhD students across multiple departments, with recent graduates including Gary Chen, Chavez Lawrence, and Shobhita Kramadhati. Her research is supported by significant grants including the IoT4Ag project focused on precision agriculture sensing systems. She maintains active collaborations with Nobel Laureate Moungi Bawendi, her former PhD advisor at MIT, and works with institutions including the Max-Planck Institute for Chemical Physics of Solids through her Humboldt Fellowship. The Kagan Research Group operates comprehensive facilities for nanomaterials synthesis, characterization, and device fabrication, combining expertise across chemistry, physics, and engineering disciplines. Current team members include PhD students from Electrical and Systems Engineering and Chemistry departments, postdoctoral researchers like Anamika Singh and Akhila Mallavarapu, and undergraduate researchers supported through programs like CURF.

• Nanostructured materials
• Colloidal nanocrystals
• Quantum dots
• +۷ مورد دیگر

Professor Guy Williams is a leading academic at the University of Cambridge with a focus on imaging science and clinical neurosciences, affiliated with Downing College and the Wolfson Brain Imaging Centre . Holding a PhD in Physics from his initial Natural Sciences degree, he specializes in nuclear magnetic resonance (NMR) and MRI techniques for brain imaging. Education: BA, PhD in Physics His research centers on non-invasive imaging of brain structure and function, particularly in traumatic brain injury (TBI) and dementia. His work involves developing novel MRI pulse sequences and advanced data analysis algorithms, including AI-based diagnostic tools. He leads studies on white matter integrity post-trauma, longitudinal dementia assessment, and applications of MRI in disorders of consciousness and addiction. Recent publications highlight collaborations in traumatic brain injury outcomes, AI-guided dementia prediction, and neuroimaging of post-COVID cognitive deficits. His team's work on ultra-high field laminar fMRI and distortion correction methods has advanced clinical neuroscience applications. Key techniques include diffusion tensor imaging (DTI), 7 Tesla MRI, and positron emission tomography (PET/MR). His research spans from basic NMR physics to clinical translation, with a strong emphasis on multi-site studies and real-world diagnostic implementation.

• Nuclear Magnetic Resonance (NMR)
• In vivo imaging
• MRI pulse sequence development
• +۷ مورد دیگر

Professor Hala Zreiqat AM is a leading biomedical engineer at The University of Sydney , serving as the Director of the ARC Training Centre for Innovative BioEngineering . A Fellow of all major Australian academies (AAS, ATSE, FAHMS, FRSN), she develops 3D printed bioceramics for bone regeneration while championing diversity through initiatives like the IDEAL Society and BIOTech Futures mentorship program. Her work bridges academia, clinical practice, and industry in musculoskeletal research . Research Focus: Her lab creates synthetic bone scaffolds that mimic natural bone architecture, strength, and porosity, enabling non-rejected bone regeneration via patient-matched implants. Key applications include orthopaedic, dental, and maxillofacial repair , with over $18M in competitive funding and multiple patents. Current projects explore AI-driven scaffold performance prediction and anti-senescence strategies for aging-related bone loss. Scientific Trends: Recent publications highlight 3D printed nanovoxelated ceramics , antisenescence biomaterials , and multifunctional theranostic platforms . Her team integrates machine learning for scaffold design, atom probe tomography for interface analysis, and two-photon imaging for cellular monitoring in 3D environments. 2021-2022 Fulbright Senior Scholar 2018 NSW Premier's Woman of the Year 2019 Eureka Prize for Innovative Use of Technology Fellow of Australian Academy of Science (2021) Over $18M in research funding Teaching & Leadership: She designed core courses like Tissue Engineering and Nanomaterials in Medicine , mentoring 158 students in 2020 alone. As Chair of CAAR (2020-2023), she strengthens Australia-Arab collaborations. Her lab trains early-career researchers , with alumni now in academia and industry.

• Biomaterials
• Tissue Engineering
• Regenerative Medicine
• +۱۲ مورد دیگر

Zion Zibly, MD, MBA is an Associate Professor in the Department of Neurosurgery at Yale School of Medicine . He holds multiple leadership roles including Director of the Center of Neuromodulation , Director of the Center of Neurosurgical Cancer Pain , and Head of Stereotactic & Functional Neurosurgery and the Focused Ultrasound Institute . Previously served as Chair of Neurosurgery at Sheba Medical Center after graduating from Technion’s Faculty of Medicine (MD) and Coller School of Management (MBA). Research Interests: Specializes in Neuromodulation for movement disorders (Parkinson’s, tremors, dystonia), Deep Brain Stimulation , Gene Therapy for pediatric neurodegenerative conditions, Oncological Neurosurgery , and Neurological Pain Management . Combines Functional Neurosurgery with Focused Ultrasound technology. Scientific Contributions: Participated in pioneering Alzheimer’s brain stimulator procedures and Gene Therapy applications. Active member of the North American Association of Functional Neurosurgery and Israeli Neurosurgical Society . Clinical Expertise: Implantation of electrostimulators for Parkinson’s and essential tremor, treatment of Benign/Malignant CNS Tumors , and management of Neurological Pain Conditions . Affiliated with Yale Cancer Center and Center for Brain & Mind Health .

• Neurosurgery
• Functional Neurosurgery
• Neuromodulation
• +۳ مورد دیگر

Xenophon Papademetris is a Professor of Biomedical Informatics & Data Science and Radiology & Biomedical Imaging at Yale School of Medicine. He serves as Associate Director of Biomedical Imaging Data Sciences at Yale Biomedical Imaging Institute and directs the Medical Software and Medical Artificial Intelligence Certificate Program. PhD in Electrical and Information Sciences from Yale University (2000) BA from Cambridge University (1994) Postdoctoral Fellowship at Yale University (2002) His research focuses on medical image analysis, machine learning, and biomedical software development. He has developed tools like BioImage Suite Web and contributed to standards committees at the Association for the Advancement of Medical Instrumentation (AAMI). His work spans modalities including MRI, CT, PET, and optical imaging. Recent publications emphasize neuroimaging analysis, explainable AI in healthcare, and multimodal data integration across species. He leads NIH-funded research under the BRAIN Initiative (R24 MH114805) and has authored a textbook on Medical Software published by Cambridge University Press. IEEE Senior Member Yale Brown-Coxe Postdoctoral Fellowship Harding Bliss Prize for Excellence in Engineering He directs the BioImage Suite Project, creating web-based image analysis tools using JavaScript and WebAssembly. His teaching includes both academic courses and a Coursera program on Medical Software with over 14,000 enrollments.

• Medical Image Analysis
• Machine Learning
• Biomedical Software Development
• +۷ مورد دیگر

Thomas Grenier is an Associate Professor in the Department of Electrical Engineering at INSA Lyon and a member of the CREATIS laboratory (CNRS UMR 5220, INSERM U1294). He obtained his HDR (Habilitation à Diriger des Recherches) in 2023 and his Ph.D. in Image Processing from INSA Lyon in 2005. His research focuses on medical image segmentation, clustering, and filtering using feature space, scale-space, and deep learning approaches. Doctoral School: EEA (Electronics, Energy, and Automatics) Research Affiliation: CREATIS Lab (CNRS/INSERM/INSA Lyon/Université Lyon 1/Université Jean Monnet Saint-Etienne) He has contributed to 20 papers and co-supervised 5 PhD students, including Léo Dumortier and Florent Guépin. Grenier leads the annual Deep Learning for Medical Imaging (DLMI) school, which he co-founded, and has organized five editions across Lyon and Montreal since 2019. The school emphasizes practical deep learning applications in medical imaging for participants of all expertise levels. His work spans interdisciplinary domains such as medical imaging , deep learning , and image processing , with recent publications on generative AI for MRI synthesis, explainable networks, and segmentation of neurological pathologies in preclinical models. He manages pedagogical platforms, coordinates LabEx PRIMES project activities, and oversees lab room infrastructure for 200 hours/year across 10 training programs. Grenier also leads the MUSIC transversal project on Multiple Sclerosis since 2019.

• Medical Image Segmentation
• Clustering
• Filtering
• +۳ مورد دیگر

Kyle McCall is an Assistant Professor in the Department of Materials Science and Engineering at the University of Texas at Dallas, within the Erik Jonsson School of Engineering and Computer Science. He holds a PhD in Applied Physics from Northwestern University (2019) and a B.S. in Physics and Mathematics from the University of Notre Dame (2014). He served as a Postdoctoral Research Fellow at ETH Zurich, Switzerland, from 2019 to 2021. Research Interests: Dr. McCall's research lies at the intersection of materials science, chemistry, and physics, focusing on the synthesis and characterization of complex semiconductors for energy and radiation detection applications. His group employs a materials-by-design approach to develop novel functional optoelectronic materials, particularly halide perovskites and related compounds. Key areas include crystal growth (via Bridgman method), X-ray crystallography, and the development of materials for solar cells, light-emitting devices, X-ray photodetectors, and neutron/gamma-ray scintillators. Publication Trends: His recent publications (all from 2021) highlight a strong focus on halide perovskite materials for radiation detection and optoelectronics. Themes include room-temperature gamma-ray detection, neutron imaging using luminescent materials, structural instabilities in perovskites, and optical behavior tuning via cation engineering. The work combines fundamental structure-property studies with device-relevant performance metrics. Scientific Awards and Memberships: Member, American Chemical Society (ACS) Member, Materials Research Society (MRS) Advising and Grants: As a tenure-track faculty member, Dr. McCall leads the McCall Research Group at UT Dallas, mentoring students in interdisciplinary materials research. He was part of the 2021 cohort of new tenured/tenure-track faculty at UT Dallas. While specific grants are not listed, his research program is clearly supported by institutional funding and infrastructure, including crystal growth and characterization facilities. Laboratories and Teams: He founded the crystal growth component of the ETH+ SynMatLab facility during his postdoc at ETH Zurich. At UT Dallas, he leads his own research group focused on materials chemistry and functional device integration, continuing his work on single crystal growth and optoelectronic characterization.

• Materials Science and Engineering
• Inorganic Chemistry
• Physics
• +۱۳ مورد دیگر

Mark Jenkinson is a Professor of NeuroImaging at the University of Oxford's Nuffield Department of Clinical Neurosciences and also holds positions at the University of Adelaide's Australian Institute for Machine Learning and the South Australian Health and Medical Research Institute (SAHMRI). He heads the Structural Modelling and Analysis Group at the FMRIB Centre, where his research focuses on multimodal population modeling and structural brain segmentation. Education: DPhil in Robotics Research (University of Oxford, 1999) BSc (Hons I) in Mathematical Physics (University of Adelaide, 1994) BE (Hons I) in Electrical and Electronic Engineering (University of Adelaide, 1993) Professor Jenkinson's research spans two major themes: multimodal modeling of populations to describe disease processes and apply to individual patient diagnoses, and structural segmentation and analysis of brain anatomy and pathology, particularly focusing on sub-cortical structures and lesions. His work integrates advanced computational methods with neuroimaging to develop tools for understanding neurological disorders. As the developer of key components of the FMRIB Software Library (FSL), he has significantly contributed to standard neuroimaging analysis pipelines used worldwide. His recent publications demonstrate a strong focus on deep learning applications in neuroimaging, uncertainty quantification in medical AI, and advanced segmentation techniques. There's a clear trend toward developing more robust, anatomically plausible models that preserve topological structures while improving diagnostic capabilities for conditions like multiple sclerosis, Huntington's, and Parkinson's diseases. Scientific Awards: Highly Cited Researcher (Clarivate Analytics 2018-2021, Thomson Reuters 2014-2016) ISMRM Outstanding Teacher Award (2009, 2014) Teaching Excellence Award, University of Oxford (2012) David Phillips Fellowship from BBSRC (2005-2010) Professor Jenkinson has supervised over 25 doctoral students whose work spans brain segmentation, connectivity analysis, and clinical applications of neuroimaging. His research is supported by significant grants including the Medical Research Future Fund (AU$2m), Wellcome Trust Centre for Integrative Neuroimaging (£11m), and NIH Human Connectome Project (US$30m), reflecting the high impact and translational potential of his work. As head of the Structural Modelling and Analysis Group at FMRIB, Jenkinson leads a team developing the FSL (FMRIB Software Library), one of the most widely used neuroimaging analysis packages globally. His group collaborates extensively with clinical researchers on applications ranging from multiple sclerosis to traumatic brain injury, translating computational advances into clinical practice.

• Neuroimaging
• Structural brain segmentation
• Multimodal population modeling
• +۶ مورد دیگر

Ian Greenhouse serves as an Assistant Professor in the Department of Human Physiology within the College of Arts and Sciences at the University of Oregon. He directs the Action Control Laboratory, where he investigates the neurophysiological mechanisms underlying human movement initiation and cancellation using multimodal approaches including electrophysiology, neuroimaging, and brain stimulation. Education: Undergraduate degree in Psychology from Tufts University Ph.D. from the University of California, San Diego Postdoctoral training at the University of California, Berkeley Research Focus: Dr. Greenhouse's work centers on action control neurophysiology , specifically examining motor inhibition processes during response stopping and preparation. His lab employs electromyography (EMG) , transcranial magnetic stimulation (TMS) , and magnetic resonance spectroscopy (MRS) to probe corticospinal excitability in healthy and clinical populations. Key investigations include neural computations for action preparation, biomarkers of stopping failure, and relationships between motor performance and brain chemistry (e.g., GABA). Publication Trends: Analysis of Dr. Greenhouse's 2022-2025 publications reveals intensified focus on subcomponents of response inhibition (pause vs. cancel processes) and neurochemical modulation of motor control. His work increasingly integrates menstrual cycle effects on GABA with action stopping metrics, while maintaining core investigations of corticospinal dynamics during unimanual/bimanual preparation. Recent studies show growing clinical applications in stroke rehabilitation. Scientific Awards: No awards were documented in the source materials. Advising and Research: As laboratory director, Dr. Greenhouse mentors students in the Action Control Laboratory's research program. Although specific grants aren't detailed, his high-output publication record spanning neuroimaging, electrophysiology, and clinical applications suggests sustained external funding for equipment-intensive neuroscience research. Laboratory Operations: The Action Control Laboratory (https://actioncontrollab.uoregon.edu) operates from Gerlinger Hall (Room 348), utilizing TMS-EMG integration, MRS, and behavioral paradigms to study action control. Current projects examine preparatory inhibition in stroke recovery, interhemispheric dynamics during movement preparation, and individual differences in stopping processes using the stop-signal task framework.

• Motor Control
• Action Stopping
• Neurophysiology
• +۳ مورد دیگر

Tan Yu Jun is an Assistant Professor at the National University of Singapore (NUS), joining in January 2021. She earned her BEng and PhD from Nanyang Technological University (NTU), focusing on additive manufacturing and biomaterials, followed by postdoctoral work on stretchable and self-healing electronics. Her research lies at the intersection of manufacturing technologies and functional materials , with a focus on developing soft machines and electronics using 3D printing, self-healing materials, and bio-inspired designs. She leads the YJ Laboratory , which emphasizes eco-friendly and smart materials. Her lab has produced high-impact publications in journals like Nature Materials , Nature Electronics , Science Robotics , and Advanced Materials , with recent work on transparent, conductive, self-healing magnetic rubber published in Science Advances (2025). This aligns with her expertise in materials engineering and soft robotics. Scientific Awards & Recognition Student-led teams from her lab won gold, silver, and healthcare special awards at the 25th Singapore Science & Engineering Fair. Her postdoc Zhang Xuan and student Eddy Pang received Best Poster Awards at MRS Fall 2024 and ICMAT 2025, respectively. Her student Max Ang Yi Neng was awarded the NUS-JTC Medal for Sustainability (2021). Advising & Collaborations Advised MSc students Zhou Jinrun and Zhang Biteng to achieve A+ in ME5001. Mentored high school students from Hwa Chong Institution (HCI) and Anglo Chinese School (Independent) through research projects. Participated in organizing RoboSoft 2023 and served as a mentor in student publicity efforts.

• Additive Manufacturing
• Biomaterials
• Self-Healing Materials
• +۴ مورد دیگر

Brad Sutton is a Professor of Bioengineering at the University of Illinois Urbana-Champaign and Technical Director of the Biomedical Imaging Center at Beckman Institute. He holds affiliate roles in the Neuroscience Program, Department of Electrical and Computer Engineering, and is a Health Innovation Professor at the Carle Illinois College of Medicine. His roles also include fellowship positions with the National Center for Supercomputing Applications and the CZ Biohub Chicago. Education: Ph.D. in Biomedical Engineering from the University of Michigan (2003). Research Interests: Focus on advanced MRI techniques for structural and functional brain imaging, including diffusion-weighted imaging, dynamic imaging, and neuromuscular coupling studies. His work emphasizes multi-scale bioimaging to understand brain function across interventions, aging, and disease. Publications: Over 180 peer-reviewed articles in 2025-2024 highlight innovations in MRI technology and applications in neuroscience, including breakthroughs in laminar fMRI specificity, myelin development modeling, and Alzheimer’s biomarker studies. Recent work extends to clinical applications like aortic imaging automation and mixed reality training tools. Awards: AIMBE and ISMRM Fellowships (2017/2024), Abel Bliss Scholar (2014-), and over 9 patents in imaging techniques. Labs & Teams: Leads the Magnetic Resonance Functional Imaging Lab. Collaborates with interdisciplinary teams across engineering, medicine, and computational science to advance imaging technologies and their clinical translation.

• Biomedical imaging
• Diffusion weighted imaging
• Dynamic imaging
• +۷ مورد دیگر

Justin P. Haldar is a Professor in the Ming Hsieh Department of Electrical and Computer Engineering at the University of Southern California (USC), with a joint appointment in the Department of Biomedical Engineering. He co-directs the Biomedical Imaging Group and serves as Director of the Signal and Image Processing Institute. His affiliations include the Dornsife Cognitive Neuroscience Imaging Center, the Brain and Creativity Institute, and the Dynamic Imaging Science Center. Education : B.S. and M.S. in Electrical Engineering (2004, 2005), Ph.D. in Electrical and Computer Engineering (2011) from the University of Illinois at Urbana-Champaign. His research focuses on computational imaging, inverse problems, and magnetic resonance imaging (MRI), with an emphasis on constrained image reconstruction, parameter estimation, and novel data acquisition strategies. His work combines physical modeling, high-dimensional signal structures, and fast computational algorithms to address MRI's limitations in speed, noise, and cost. Recent publications analyze challenges like the 'hidden noise' problem in MR reconstruction (2025) and innovations in dynamic imaging. His research has enabled faster MRI exams and next-generation imaging techniques by exploiting dimensionality's 'blessings' while mitigating its 'curses.' Scientific awards : NSF CAREER Award (2014) IEEE ISBI Best Paper Award (2010) IEEE EMBC First-Place Student Paper Award Haldar's leadership roles include Chair of the IEEE Signal Processing Society's Technical Committee on Computational Imaging and editorial positions at IEEE Transactions on Computational Imaging and Magnetic Resonance in Medicine . He actively mentors students and develops novel MRI approaches at USC's Michelson Center for Convergent Bioscience.

• Computational Imaging
• Inverse Problems
• Magnetic Resonance Imaging (MRI)
• +۳ مورد دیگر

Andrea Falini is a Full Professor of Neuroradiology at the Vita-Salute San Raffaele University (School of Medicine). He holds leadership roles including Head of the Neuroradiology Department at the Scientific Institute S. Raffaele Hospital and Head of the Advanced Diagnostic in Neuro-oncology Unit. His career spans clinical, academic, and administrative roles since 1991, with extensive experience in neuroradiology, neuro-oncology, and neuroimaging research. Education: MD (1986, University of Milan), PhD in Neurological Sciences (1989), and specialized training in Neurology and Radiology at leading institutions, including a visiting scholar position at UCSF (1996). Research interests focus on advanced MRI techniques, neuro-oncology, neurodegenerative diseases, and cognitive neuroscience. His work emphasizes functional MRI, diffusion tensor imaging, and clinical applications in glioma management and neurodegenerative disorders. Awarded the 1989 'De Visart' Prize and grants supporting his international collaborations. He has authored 218+ peer-reviewed articles, with an H-index of 40+, and actively contributes to academic committees and international conferences. Leadership roles include Vice-Director of the Neuroscience Division (2014–present) and coordination of the BraiMap Research Program. His academic teaching spans neuroradiology, biomedical engineering, and cognitive neuroscience courses.

• Advanced MR Techniques
• Neuro-oncology
• Degenerative Diseases
• +۳ مورد دیگر