جستجوی استاد راهنمای دانشگاهی

• Quantum optics
• Condensed matter physics
• Quantum electrodynamics
• +۵ مورد دیگر

Cristiano Ciuti is a Professor at the University of Paris Cité and Director of the MPQ (Matter and Complex Quantum Systems) laboratory since April 2018. He also leads the THEORY team within the same institution. His academic journey includes an Associate Professor position at ENS Paris (2003-2006), a postdoc at UCSD (2001-2003), and doctoral work at EPFL Switzerland (1997-2001). Habilitation HDR (Univ. Paris 6) - 2005 Doctorate of Science, EPFL - 2001 Diploma di Licenza cum laude, Scuola Normale Superiore & Laurea, Università di Pisa, Italy - 1997 Professor Ciuti's research focuses on quantum physics phenomena, particularly in the areas of quantum optics and transport in condensed matter systems, cavity and circuit quantum electrodynamics in the strong coupling regime, theory of open quantum multi-body systems, and non-equilibrium quantum critical phenomena. His work increasingly intersects with complex systems and machine learning approaches, exploring applications of neural networks to quantum dynamics and quantum technologies. His research has evolved to incorporate cutting-edge computational methods including variational approaches and neural quantum states. His recent publications demonstrate a strong trend toward integrating machine learning techniques with quantum physics, particularly in developing neural network approaches for quantum dynamics simulation, quantum state representation, and quantum computing applications. The research spans fundamental quantum phenomena while addressing practical computational challenges in simulating complex quantum systems. Fellow of the American Physical Society (2021) Friedel-Volterra Prize (2019) ERC Consolidator Fellowship (2013) Junior Member of the Institut Universitaire de France (IUF) (2010) Marie Curie Fellowship (2003) Professor Ciuti has supervised an extensive number of doctoral students since 2007, with 17 completed theses as of 2023. His mentoring extends to numerous postdoctoral researchers, with current and past appointments including L. Giacomelli, G. Arwas, Z. Denis, and others. His research group appears well-funded through prestigious grants including ERC funding. The MPQ laboratory he directs serves as a hub for quantum physics research, particularly focusing on theoretical approaches to complex quantum phenomena with connections to experimental implementations.

• Traumatic Brain Injury (TBI)
• Prion Diseases
• Neurodegenerative Disorders
• +۴ مورد دیگر

Kimbra Kenney, MD, is a Clinical Professor in the Department of Neurology at the Uniformed Services University of the Health Sciences (USUHS) School of Medicine. Her research focuses on traumatic brain injury (TBI), prion diseases, and biomarkers of neurological disorders, with a particular emphasis on military and veteran populations. She has held roles including Clinical Associate at the NIH, Medical Officer, and clinical researcher in programs such as the Comprehensive Neuroscience Program (CNP) and the National Intrepid Center of Excellence (NICoE). Dr. Kenney's work spans neuroimaging, cerebrovascular function, and neurodegenerative mechanisms in TBI, with a focus on translational research and clinical outcomes. Education B.A., The Johns Hopkins University (1980) M.D., University of Virginia School of Medicine (1984) Internship: Internal Medicine, Harbor-UCLA (1985) Residency: Neurology, Oregon Health Sciences University (1988) Fellowship: Neuropathology, University of Washington (1989) Research Interests Dr. Kenney's work addresses biomarkers of TBI, prion disease pathogenesis, and cerebrovascular dysfunction. She investigates links between TBI and chronic conditions such as dementia, headaches, and neurological inflammation. Her studies employ neuroimaging (e.g., MRI, fNIRS), blood-based biomarkers (e.g., neurofilament light, GFAP), and exosomal microRNA analysis to assess injury mechanisms and treatment efficacy. Grants & Collaboration Her research has been supported through collaborations with the NIH, Chronic Effects of Neurotrauma Consortium (CENC), and the ENIGMA Military Brain Injury Working Group. Key projects include the LIMBIC-CENC study on TBI epidemiology and the NICoE’s clinical trials for cerebrovascular therapies. Labs & Teams Dr. Kenney contributes to interdisciplinary teams at USUHS, NICoE, and the Department of Neurology, focusing on military-relevant neurological disorders and translational research initiatives.

• Magnetoencephalography (MEG)
• Traumatic Brain Injury
• Concussion
• +۵ مورد دیگر

Elizabeth Moody Davenport, Ph.D., is an Assistant Professor of Radiology at UT Southwestern Medical Center, where she serves as the Technical Director for the Magnetoencephalography Center of Excellence. She holds secondary appointments in the Department of Biomedical Engineering and the Advanced Imaging Research Center (AIRC), and a tertiary appointment in the Department of Neurology. Her educational background includes a bachelor's degree in biomedical engineering from North Carolina State University and a doctorate in biomedical engineering from Virginia Tech-Wake Forest University. She completed postdoctoral training in clinical Magnetoencephalography (MEG) at UT Southwestern in the Advanced NeuroScience Imaging Research (ANSIR) Lab under Joseph Maldjian. Dr. Davenport's research focuses on magnetoencephalography (MEG) and advanced imaging techniques to study traumatic brain injury, concussion, Alzheimer's disease, dementia, and epilepsy. Her work examines subconcussive head impacts in contact sports and their effects on brain function/structure, aiming to develop imaging biomarkers for clinical diagnosis and prognosis. Her recent publications reveal strong trends in MEG-based investigation of brain connectivity changes following head impacts in youth football, with expanding applications in epilepsy surgery planning, Alzheimer's disease progression, and novel tool development for neural signal analysis. Scientific recognition includes: Patent for developing a system that allows for rapid intraosseous delivery of fluids from a fluid reservoir via an intraosseous port having a tip disposed within a patient's bone marrow Dr. Davenport actively mentors Ph.D. candidates and postdoctoral researchers in the Davenport Lab, securing research funding and extending her scientific expertise to nonprofit canine rescue grants. Her leadership in the ANSIR Lab fosters multidisciplinary collaboration across radiology, neurology, and biomedical engineering. The Davenport Lab specializes in quantitative brain imaging methods, developing MEG spectral analysis algorithms and advanced MRI structural analytics for concussion biomarkers, early dementia detection, and epilepsy localization, directly supporting clinical applications at UT Southwestern.

Brian Woodمشاهده پروفایل

استاد

• Transport Phenomena
• Multiscale Analysis
• Environmental Engineering
• +۳ مورد دیگر

Brian Wood is a Professor in the Department of Chemical, Biological, and Environmental Engineering at Oregon State University (OSU), part of the College of Engineering. His research focuses on multiscale systems analysis, particularly in transport phenomena, tissue modeling, and environmental engineering applications. He holds a Ph.D. in Civil and Environmental Engineering from the University of California, Davis (1999), an M.S. in Environmental Engineering from Washington State University (1990), and a B.S. in Civil Engineering from Washington State University (1988). Wood’s research interests span transport of mass, momentum, and energy in natural and engineered systems, including multiscale tissue analysis and cancer biology modeling. His work integrates computational methods with experimental data to address challenges in porous media dynamics, biofilm growth, and environmental remediation. Notable contributions include studies on non-equilibrium transport, chemotaxis in granular media, and biofilm architecture visualization using synchrotron-based X-ray tomography. His recent publications (2020–2025) emphasize advancements in upscaling techniques for porous media flow, machine learning applications in biomedical modeling, and regulatory frameworks for end-user control systems. He leads the Computation and Simulation research group at OSU, fostering interdisciplinary approaches to multiscale hydrogeologic modeling. Wood’s research has been supported by collaborative grants focusing on bacterial transport in heterogeneous environments and hybrid multiscale methods. His work bridges theoretical developments in continuum mechanics with practical applications in environmental engineering and biomedical systems.

Grant Gullbergمشاهده پروفایل

استاد مدعو

• Cardiac Imaging
• Medical Imaging
• Nuclear Medicine
• +۳ مورد دیگر

Grant Gullberg, PhD, is an Adjunct Professor in the School of Medicine at the University of California, San Francisco (UCSF). His primary affiliation is with the Department of Radiology, where he focuses on advanced imaging technologies. He holds significant expertise in dynamic cardiac SPECT and PET imaging, myocardial blood flow quantification, and novel hardware designs for medical imaging systems. Research Interests: His work spans biomedical engineering, nuclear medicine, and radiology, with a focus on developing and optimizing imaging techniques for cardiovascular applications. Key areas include: Dynamic PET/SPECT imaging methodologies Quantitative myocardial perfusion analysis Advanced reconstruction algorithms (e.g., MLEM, factorization methods) Hardware innovations like CZT detectors and collimatorless systems Grants & Funding: Dr. Gullberg has led or co-led multiple NIH-funded projects, including: Dynamic Cardiac SPECT Imaging (R01HL050663, 1995–2015) Molecular Imaging of Cardiac Hypertrophy (R01EB007219, 2008–2013) PET imaging of glucose and fatty acid metabolism (R01HL135490, 2017–2021) Labs/Teams: Collaborates actively with multidisciplinary teams in UCSF’s Radiology department, focusing on translational research in cardiac imaging and medical physics. His work integrates computational methods, deep learning, and clinical validation for diagnostic advancements.

Yubin Zhangمشاهده پروفایل

پژوهشگر

• Microstructure Engineering
• Materials Science
• Tomography
• +۶ مورد دیگر

Yubin Zhang serves as a Senior Researcher at the Department of Civil and Mechanical Engineering, Technical University of Denmark (DTU), with expertise in advanced materials characterization. His primary affiliation is with DTU Mechanical Engineering (MEK), where he contributes to the 3D Imaging Center (3DIM) project and conducts research on microstructure engineering of metallic materials. His research focuses on Microstructure Engineering, Materials Science, and Tomography, with specialized expertise in aluminum alloys, recrystallization phenomena, nucleation mechanisms, and grain boundary dynamics. He integrates experimental techniques like X-ray microscopy with computational approaches including deep learning for microstructural analysis, enabling precise characterization of deformation and phase transformations in complex materials. Recent publications demonstrate a clear trend toward multimodal 3D/4D imaging techniques combined with machine learning for microstructure quantification. His work bridges fundamental materials science with industrial applications, particularly in additive manufacturing and aluminum processing, where advanced imaging provides critical insights into material behavior during thermo-mechanical treatments. As a dedicated supervisor, Dr. Zhang mentors PhD candidates including Defer, M. C. on additive manufactured AlSiMg alloys, Knipschildt-Okkels, E. F. F. on recrystallization nucleation, and Lindkvist, A. A. on residual stresses in multiphase steels. His research is supported through major grants including the 3DIM project (2016-2029) and Microstructural Engineering of Additive Manufactured AlSiMg (2023-2026), where he serves as Principal Investigator and supervisor respectively. Dr. Zhang operates within DTU's 3D Imaging Center, a state-of-the-art facility utilizing synchrotron radiation and laboratory X-ray sources for non-destructive 3D characterization. His team specializes in diffraction contrast tomography, dark field X-ray microscopy, and machine learning applications for microstructure analysis, with strong collaborations across European research institutions.

Nam Buiمشاهده پروفایل

استادیار

• Mobile/Wearable Health Sensing
• Embedded Intelligent Systems
• Artificial Intelligence
• +۲ مورد دیگر

Nam Bui is an Assistant Professor in the Department of Electrical Engineering at the University of Colorado Denver, where he founded and directs the Intelligent Networked Systems and Cybernetics Laboratory (InsCy Lab). His research focuses on developing intelligent cybernetic systems at the intersection of AI, machine learning, and embedded systems, with applications in mobile/wearable health monitoring and physiological sensing. His research interests span: Innovative sensing techniques for health monitoring Embedded intelligent systems leveraging AI/ML Wearable technology for physiological measurement Multidisciplinary approaches to medical cybernetics Analysis of recent publications reveals consistent themes in wearable health technology development, particularly focusing on non-invasive monitoring techniques for vital signs (blood pressure, respiration, glucose) using ear-worn and behind-ear devices. Key technical innovations include compressed sensing frameworks, closed-loop acoustic stimulation systems, and novel sensing modalities like polarization-based optical detection. Awards and Honors: Best Paper Awards at ACM MobiCom (2019, 2017) ACM SigMobile Research Highlights (2020) Communication of ACM Research Highlights (2021) Colorado OEDIT Award (2024) NASA MUREP Program Award (2024) NSF Sense Award (2024) DoD STTR Grant (2024) Teaching Innovation Award (2023) Dr. Bui actively advises graduate students including Anh-Huy Dinh and undergraduate researchers including Luis Carlos Gutierrez and Alejandro Cordova. His laboratory has secured multiple grants from NSF, NASA, DoD, and Colorado economic development programs. He directs the Intelligent Networked Systems and Cybernetics Laboratory (InsCy Lab), which focuses on practical intelligent systems for health monitoring. The lab emphasizes multidisciplinary collaboration and has developed technologies like in-ear blood pressure monitors and closed-loop sleep aid devices.

Sanket Tavarageriمشاهده پروفایل

استادیار

• Big Data
• Machine Learning
• High Performance Computing
• +۲ مورد دیگر

Sanket Tavarageri is an Assistant Professor in the Computer Engineering Department at San José State University. He holds a Ph.D. in Computer Science and Engineering from The Ohio State University and a B.Tech from National Institute of Technology Karnataka. His research encompasses big data systems, machine learning infrastructure, and high-performance compiler technologies. Research areas include: Polyhedral compilation techniques for deep learning workloads Automatic parallelization and optimization frameworks Hardware-software co-design for computational efficiency Scalable machine learning systems His publication portfolio demonstrates consistent innovation in compiler architecture and parallel systems from 2013-2021. Recent work focuses on AI-enhanced compilation, automatic parallelism for deep learning models, and hardware-aware optimizations. Publications appear in ACM TACO, IEEE Big Data, IPDPS, and PLDI conferences. Tavarageri maintains an active industry connection as a researcher at Google. Tools developed through his BRIGHT laboratory are available on GitHub and Bitbucket. His teaching covers compiler technology, parallel computing, and systems design with emphasis on practical implementation.

William Lionheartمشاهده پروفایل

استاد

• Inverse Problems
• Imaging Techniques
• Medical Imaging
• +۳ مورد دیگر

William Lionheart is a Professor of Applied Mathematics at the University of Manchester, specializing in inverse problems with applications in imaging across industry, security, medicine, and non-destructive testing. He leads research collaborations including the Henry Mosley Centre for X-ray Imaging and the Land Mine Research Centre. His work integrates theoretical, numerical, and practical methods to advance imaging technologies. Education: BSc, PhD in Applied Mathematics. Key research areas include electrical impedance tomography, X-ray imaging, and polarizability tensor-based object characterization. He has pioneered techniques for metallic object detection and medical imaging applications. Research highlights include developing algorithms for synthetic aperture radar, elastic strain reconstruction, and proton therapy verification systems. Awards include the Wolfson Research Merit Award (2015) and a 2013 recognition. He has contributed to 193+ research outputs, led 11 projects (e.g., RASTER, SEMIS Phase III), and organized conferences like the 2023 'Rich and Nonlinear Tomography' event. His work impacts airport security, land mine detection, and medical diagnostics, generating over USD215M in industrial applications.

HO Wen Weiمشاهده پروفایل

استادیار

• Quantum Many-Body Systems
• Quantum Information Science
• Condensed Matter Physics
• +۳ مورد دیگر

Dr. HO Wen Wei is an Assistant Professor of Physics at the National University of Singapore (NUS) and a recipient of the NUS Presidential Young Professorship. He holds a PhD from the University of Geneva (2017), an MS from the University of Waterloo (2014), and an AB from Princeton University (2013). His research focuses on novel nonequilibrium quantum many-body phenomena, quantum information science, and collaborations with experimental groups using Rydberg atoms and ultracold atoms. He explores topics like prethermalization, quantum many-body scars, and quantum state designs in chaotic dynamics. Education: PhD in Physics, University of Geneva (2017) MS in Theoretical Physics, University of Waterloo (2014) AB in Physics (Magna cum Laude), Princeton University (2013) Research Interests: Quantum many-body dynamics and thermalization Quantum information protocols for NISQ devices Quantum simulation with Rydberg and ultracold atoms Exact solutions and numerical methods (e.g., tensor networks) Applications in quantum state tomography and error mitigation Scientific Awards: NUS Presidential Young Professorship (2022–present) Advising & Collaborations: Dr. Ho leads the quantum many-body dynamics group at NUS, recruiting graduate students and postdocs. He collaborates with experimental teams on analog quantum simulators and has prior postdoctoral experience at Harvard and Stanford. His lab focuses on bridging theoretical models with experimental implementations. Labs & Teams: His research group at NUS integrates theoretical physics with cutting-edge quantum technologies, emphasizing interdisciplinary collaborations. Recent work includes studies on deep thermalization and quantum ergodicity in driven systems.

Kevin Weinerمشاهده پروفایل

دانشیار

• Cognitive Neuroscience
• Visual Perception
• Face Processing
• +۵ مورد دیگر

Kevin Weiner is an Associate Professor at the University of California, Berkeley, joining the department in January 2018. He leads the Cognitive Neuroanatomy Lab and focuses on the structural and functional basis of visual perception, particularly face processing in high-level visual cortex. His research employs multi-modal methodologies combining functional measurements (high-resolution fMRI, electrocorticography) with anatomical analyses in vivo (diffusion imaging, cortical folding) and post-mortem (cytoarchitecture, myeloarchitecture). Core interests include visual perception mechanisms, domain-specific brain regions, comparative neuroanatomy across species, developmental neuroscience, and translational applications for neurological patient populations. Analysis of his publication record reveals consistent expertise in fusiform gyrus organization and face-processing networks. His work demonstrates increasing integration of histological validation with neuroimaging, alongside growing emphasis on open science practices and translational clinical applications in recent years. Dr. Weiner mentors graduate students and directs the Cognitive Neuroanatomy Lab, which prioritizes collaborative research, data sharing initiatives, and science communication efforts while advancing mechanistic models of brain structure-function relationships.

Volker Deringerمشاهده پروفایل

دانشیار

• Theoretical Chemistry
• Computational Materials Science
• Machine Learning in Chemistry
• +۳ مورد دیگر

Volker Deringer is an Associate Professor of Theoretical and Computational Inorganic Chemistry at the University of Oxford's Department of Chemistry. He holds a Tutorial Fellowship at St Anne's College and teaches Inorganic Chemistry to first- and second-year students at St Anne's and Oriel Colleges. His research focuses on combining quantum mechanics with machine learning to model materials at the atomic scale, with emphasis on amorphous solids, functional materials design, and interatomic potential development. Education: He earned his diploma (2010) and doctorate (summa cum laude, 2014) in Chemistry from RWTH Aachen University, Germany, under Prof. Richard Dronskowski. Postdoctoral positions included a Humboldt Fellowship at the University of Cambridge (2015) and a Leverhulme Early Career Fellowship (2017). Research Interests: Machine learning interatomic potentials, structural chemistry of amorphous solids, functional materials for energy storage and electronics. His work bridges theoretical/computational methods with experimental collaborations, emphasizing practical applications like phase-change memory materials and graphene oxide systems. Publications: Over 100 articles since 2017, including high-impact journals like Nature, Nature Chemistry, and Nature Communications. Recent work explores AI-driven materials discovery, amorphous silicon dynamics, and battery anode design. Key themes include accelerating simulations via ML, understanding disorder in materials, and developing transferable interatomic potentials. Grants/Awards: Recipient of Alexander von Humboldt and Leverhulme Fellowships. Active in cross-disciplinary projects combining AI and materials science. Labs/Teams: Leads a research group focused on computational materials design, collaborating with experimentalists globally. Involved in developing open-source tools like LOBSTER for chemical bonding analysis.

Davide Rattacasoمشاهده پروفایل

پژوهشگر ارشد

• Quantum Information
• Quantum Many-Body Systems
• Adiabatic Quantum Computation
• +۳ مورد دیگر

Davide Rattacaso is a Research Fellow at the University of Padua's Department of Physics and Astronomy, funded by the European Project EuRyQa. His research focuses on quantum information, quantum many-body systems, and developing hardware-aware quantum compilers using tensor network techniques. Current projects include adiabatic quantum computation, inverse problems in quantum systems, resource theory, and information geometry. His work integrates advanced computational methods with theoretical frameworks to address challenges in quantum hardware optimization and quantum dynamics. Key themes across his research include understanding non-equilibrium quantum phenomena and leveraging geometric approaches to analyze quantum complexity and chaos. His contributions span foundational studies on Hamiltonian reconstruction, stabilizer entropy dynamics, and delocalized quantum state evolutions. The research is supported by grants emphasizing practical applications of quantum algorithms and architectures.

R. (Ro) Jeffersonمشاهده پروفایل

استادیار

• Physics
• Machine Learning
• Quantum Field Theory
• +۷ مورد دیگر

Dr. R. (Ro) Jefferson is an Assistant Professor at Utrecht University with a dual 50/50 appointment between the Institute for Theoretical Physics (ITP) and the Department of Information and Computing Sciences (ICS). Their research focuses on interdisciplinary applications of physics and information theory to deep learning and neuro-inspired AI, including mathematical connections between neural networks and renormalization group flows. Additionally, they study holography, black holes, quantum gravity, and quantum information theory's role in fundamental physics. They actively contribute to EDI efforts through committee memberships and public advocacy for marginalized groups in academia. Education background: PhD (Theoretical Physics, University of Amsterdam, 2017), MSc (Physics, McGill University, 2013). Former roles include Nordita Fellow (2020–2022) and postdoctoral researcher at the Max Planck Institute for Gravitational Physics (2017–2020). Courses taught include Advanced Quantum Field Theory and Research Methods for Computer Science. Research interests include: quantum field theory applications in AI, modular theory's implications for black hole interiors, and statistical field theory methods for deep network analysis. Their work bridges theoretical physics with machine learning through frameworks like the NN/QFT correspondence. Recent publications explore traversable wormholes, entanglement entropy, and critical phenomena in neural networks. Outreach activities include speaking at I, Scientist 2019, Berlin Museum für Naturkunde, and LGBTQIA+ science showcases. Advocacy focuses on combating pseudoscience affecting trans healthcare access and climate misinformation.

Lars Fritzمشاهده پروفایل

دانشیار

• Condensed Matter Theory
• Statistical Physics
• Computational Physics
• +۴ مورد دیگر

Dr. Lars Fritz is an Associate Professor in Theoretical Physics at Utrecht University's Faculty of Science, affiliated with the Theoretical Physics (ITF) department. His research focuses on condensed matter theory, statistical physics, and computational methods, with a particular emphasis on topological phases, quantum transport, and strongly correlated systems. He holds a Ph.D. and has been active in publishing influential papers on topics such as Kondo effects, Dirac/Weyl semimetals, and topological insulators. His work often explores the interplay between disorder, interactions, and topology in materials. Key research areas include hydrodynamic behavior in 2D electronic systems, quantum critical phenomena in Kondo systems, and the role of symmetry in topological materials. Notable contributions include studies on graphene's hydrodynamics, Sachdev-Ye-Kitaev models, and fractal lattices. Dr. Fritz has authored over 48 publications, including reviews in the Annual Review of Condensed Matter Physics and high-impact journals like Physical Review B and Physical Review Letters. His teaching includes advanced theoretical physics courses, and he actively contributes to research groups exploring emerging quantum materials. While no specific grants or awards are listed in the provided texts, his extensive publication record underscores his significant academic contributions.