جست‌وجوی استاد و پژوهشگر

• Topological phases of matter
• Fractional Quantum Hall effect
• High temperature superconductors
• +۶ مورد دیگر

Eduardo H. Fradkin is the Donald Biggar Willett Professor of Physics and Engineering at the University of Illinois at Urbana-Champaign, where he also serves as Director of the Institute for Condensed Matter Theory (ICMT). A Center for Advanced Study Professor, Fradkin has been a faculty member at Illinois since 1979, progressing from postdoctoral researcher to assistant professor (1981), associate professor (1984), and full professor (1989). His research spans the interface between quantum field theory and condensed matter physics, with particular focus on topological phases of matter, fractional quantum Hall effect, high-temperature superconductors, and strongly correlated systems. Fradkin pioneered the application of quantum field theory methods to condensed matter problems, including his groundbreaking work showing the smooth connection between Higgs and confinement phases in gauge theories, which remains fundamental to understanding gauge theory phases. His research has significantly advanced our understanding of electronic liquid crystal phases, pair density wave superconductivity, and intertwined orders in quantum materials. His recent publications reveal continued leadership in theoretical condensed matter physics, with 2023-2025 works exploring intertwined orders in high-temperature superconductors, topological aspects of pair density waves, quantum Hall nematics, and the physics of UTe 2 as a potential topological superconductor. These works demonstrate his ongoing contributions to understanding complex quantum phases and their experimental signatures. Fellow of the American Physical Society Member of the National Academy of Sciences Fellow of the American Academy of Arts and Sciences Eugene Feenberg Memorial Medal (2024) Simon Guggenheim Memorial Foundation Fellowship Donald Biggar Willett Professor of Physics Fradkin has mentored numerous graduate students who have become prominent physicists, including Matthew Fisher and Ana López. His theoretical frameworks have guided extensive experimental work in condensed matter physics worldwide. He directs the Institute for Condensed Matter Theory, fostering interdisciplinary research at the frontier of quantum materials. His influential textbooks, including "Quantum Field Theory, An Integrated Approach" (2021) and "Field Theories of Condensed Matter Systems" (2013), have shaped the education of generations of theoretical physicists.

• Nonlinear Filtering
• Multi-Object Tracking
• Deep Machine Learning
• +۳ مورد دیگر

Lennart Svensson is a Professor at Chalmers University of Technology in the Signal Processing research group. His work focuses on nonlinear filtering, multi-object tracking, Bayesian statistics, and deep machine learning with applications in autonomous systems and sensor fusion. Research Interests Nonlinear Filtering and Bayesian Inference Multi-Object Tracking and Sensor Fusion Deep Learning for Autonomous Systems Performance Metrics (GOSPA, T-GOSPA) Lidar-Camera Fusion and Radiance Fields 5G SLAM and mmWave Sensing Publications Trends Recent work emphasizes uncertainty-aware multi-object tracking metrics, trajectory estimation using Poisson Multi-Bernoulli Mixtures, and sensor fusion techniques for autonomous driving. His research integrates Bayesian methods with deep learning for applications in automotive radar, lidar, and 5G positioning systems. Contact Email: lennart.svensson@chalmers.se

• Magnetic Resonance Imaging (MRI)
• Neuroimaging Biophysics
• Brain Metabolism Analysis
• +۶ مورد دیگر

Harald E. Möller is a Professor and Head of the Nuclear Magnetic Resonance Research and Development Unit at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig. With a career spanning over four decades, he has held academic positions including Honorary Professor at the University of Leipzig and leadership roles in institutions like Duke University Medical Center and the University of Münster. His research focuses on advancing MRI methodologies, biophysical imaging principles, and their applications in neurology and neuroscience. Education: 1979-1985: Chemistry & Physics studies at Universities of Dortmund and Münster 1985: M.Sc. (Diploma) in Chemistry 1988: PhD in Physical Chemistry (summa cum laude) 2000: Habilitation in Physical Chemistry 2002: Habilitation in Biophysical Chemistry Research Interests: Development of novel MRI methods Quantitative tissue characterization Myelin sheath imaging Cerebral blood flow dynamics High-field MRI hardware

Jinchuan Xingمشاهده پروفایل

استاد

• Mobile Elements
• Human Genomic Variation
• Evolutionary Genetics
• +۱۴ مورد دیگر

Jinchuan Xing is a Professor at Rutgers, The State University of New Jersey, where he leads the Xing Lab of Genomics. His research focuses on human genomic variation, mobile DNA elements, evolutionary and population genetics, and their implications for human disease. He integrates computational and experimental methods to study genome-wide variation, with applications in disease gene identification and genomic technology development. His research interests include: Mobile DNA element biology Human demographic history and population diversity Disease gene identification using whole-exome and whole-genome sequencing High-altitude adaptation genetics Transposable element regulation and expression piRNA and small RNA pathways His recent publications highlight a strong trend in reproductive genomics, particularly in identifying genetic risk factors for embryo aneuploidy in IVF patients, using advanced sequencing technologies. Other work spans evolutionary genomics in diverse species (bats, moths, Drosophila), structural variation in neurodevelopmental disorders, and proteogenomic discovery. His lab actively develops and applies bioinformatic tools for variant analysis and gene prioritization. Scientific awards and honors are not explicitly mentioned in the provided text. Jinchuan Xing advises several graduate students, including Nan Wang, Siqi, Ellie Lu, and Tongji Xing. His lab has received significant funding, including an R01 grant from NICHD on aneuploidy risk, a grant from the Center for Human Evolutionary Studies, and a Life Sciences Alliance Pilot Seed Funding grant in collaboration with the Department of Statistics. These grants support research in fertility genomics, disease gene discovery, and genomic tool development. The Xing Lab of Genomics is an active research group conducting interdisciplinary studies combining genomics, bioinformatics, and molecular biology. The lab welcomes new members regularly, including master’s and PhD students, and collaborates across departments. Current projects include understanding the genetic basis of meiosis, fertility, and high-altitude adaptation, as well as developing Markovian gene networks for disease gene discovery.

Rodolfo Jalabertمشاهده پروفایل

استاد

• Condensed Matter Theory
• Mesoscopic Quantum Physics
• Quantum Chaos
• +۳ مورد دیگر

Rodolfo Jalabert is a Professor at the University of Strasbourg's Institut de Physique et Chimie des Matériaux de Strasbourg (IPCMS), where he leads research in the Magnetic Objects on the NanoScale (DMONS) team. He joined the university in 1994 after postdoctoral positions at Yale University (1989–1992), CEA Saclay (1992–1993), and IPN-CNRS Orsay (1993–1994). He holds a PhD in Physics from the University of Maryland (1984–1989). His research centers on Condensed Matter Theory , Mesoscopic Quantum Physics , and Quantum Chaos , with emphasis on: Quantum transport in nanostructures (e.g., scanning gate microscopy, quantum dots) Plasmon dynamics in metallic nanoparticles Spin relaxation in semiconductors Decoherence and quantum chaos (e.g., OTOCs, Loschmidt echo) Orbital magnetism in nanoscale systems His publications (2015–2020) predominantly explore quantum coherence, electron transport, plasmonics, and chaos in low-dimensional systems. Trends include advanced scanning probe techniques, out-of-time-ordered correlators for chaos detection, and spin dynamics in disordered materials. Jalabert collaborates with the Mesoscopic Quantum Physics team at IPCMS, focusing on theoretical modeling of nanoscale phenomena. No awards, students, or grants are detailed in the provided text.

Emily Gibsonمشاهده پروفایل

دانشیار

• Neurophotonics
• Biomedical Optics
• Neural Imaging
• +۴ مورد دیگر

Dr. Emily Gibson is an Associate Professor in the Department of Bioengineering at the University of Colorado School of Medicine. She holds a PhD from the University of Colorado Boulder (2004) and a BS from the Colorado School of Mines (1997). Her multidisciplinary research focuses on developing advanced optical technologies for neuroscience applications. Her primary research interests include: Development of implantable miniature microscopes for two-photon brain imaging in freely behaving animals Superresolution STED microscopy for subcellular imaging of protein dynamics Optical interfaces for neural modulation and sensing in central and peripheral nervous systems Applications in brain mapping, neural circuit analysis, and bioelectronic medicine Dr. Gibson's recent publications demonstrate a strong focus on neurophotonic tool development, including miniature microscopes, fiber-optic imaging systems, and superresolution techniques. Her work consistently applies these technologies to study neural coding, learning mechanisms, and neurodegenerative processes. She leads the Biophotonics Lab at CU Anschutz, which actively develops open-source neurophotonic tools. Current projects include BRAIN Initiative-funded work on voltage imaging and NSF-supported research on odor navigation. Her lab maintains active collaborations with neuroscientists and clinicians to translate optical technologies into neuroscience research and clinical applications.

Amin Darvazehbanمشاهده پروفایل

پژوهشگر ارشد

• Electromagnetic Antenna Design
• Medical Imaging
• Microwave Engineering
• +۵ مورد دیگر

Dr. Amin Darvazehban is an Adjunct Research Fellow at the School of Electrical Engineering and Computer Science, The University of Queensland. His research focuses on electromagnetic antenna design for biomedical imaging systems, particularly targeting torso and liver diagnostics. Key Research Areas: Medical microwave imaging systems Metasurface and reconfigurable antenna technologies Dielectric property analysis for diagnostics Biomedical electromagnetic sensors Quantum signal processing applications Publication Trends: Recent work highlights electromagnetic solutions for non-invasive steatotic liver detection, torso imaging optimization, and metasurface-based antenna systems. His articles span IEEE journals in Antennas, Microwaves in Medicine, and Biosensors. Education: Completed his PhD thesis in 2021 on 'Reconfigurable antennas for electromagnetic torso imaging' at the School of Information Technology and Electrical Engineering, The University of Queensland. Patent: Co-inventor of an apparatus for electromagnetic characterization of internal features (US20230228917A1, 2023).

• Medical Physics
• Radiation Oncology
• Proton Therapy
• +۳ مورد دیگر

Sara Margareta Cecilia Pilskog serves as an Associate Professor in the Department of Physics and Technology at the University of Bergen, Norway, with dual affiliation at Haukeland University Hospital's Department of Cancer Treatment and Medical Physics. Her research bridges theoretical medical physics and clinical oncology applications, focusing on precision radiotherapy techniques and biological optimization. Her primary research interests center on proton therapy innovation, where she investigates biological optimization strategies using linear energy transfer (LET) and relative biological effectiveness (RBE) modeling. She develops adaptive radiotherapy frameworks to address inter-fractional motion in pelvic cancers, particularly prostate and rectal malignancies. Her work also pioneers neutron-based in-vivo range verification systems and statistical deformation models for dose accumulation. Current projects emphasize reducing treatment margins through anatomical robustness and optimizing biological dose distributions for organ sparing. Analysis of her 15 most recent publications reveals a dominant focus on improving proton therapy precision for pelvic cancers through biological modeling and motion management. Approximately 70% of her work addresses prostate cancer applications, with significant contributions to adaptive strategies for inter-fractional changes and biological optimization techniques. Her research consistently employs Monte Carlo simulations (particularly FLUKA) and clinical data analysis to translate theoretical models into clinically viable solutions. No scientific awards were documented in the provided materials. While specific advising details remain unreported, her collaborative patterns indicate active mentorship within the University of Bergen's medical physics research ecosystem. Her publications consistently involve junior co-authors from clinical physics teams at Haukeland University Hospital, suggesting hands-on supervision of technical staff and research fellows in radiotherapy innovation projects. Grant funding appears primarily channeled through institutional hospital-university partnerships focused on clinical translation of advanced radiotherapy techniques. Dr. Pilskog operates within the University of Bergen's medical physics research cluster that maintains close operational ties to Haukeland University Hospital's radiotherapy department. This integrated academic-clinical environment enables direct implementation of her research on adaptive proton therapy and biological optimization into clinical workflows, with particular emphasis on pelvic cancer treatment protocols. The team utilizes advanced Monte Carlo simulation platforms and clinical treatment planning systems to develop and validate next-generation radiotherapy approaches.

• X-ray tomography
• Computed tomography
• Micro-CT imaging
• +۵ مورد دیگر

Dr. Glenn Myers is a Research Fellow in the Department of Materials Physics at Australian National University (ANU), where he works within the X-ray tomography and applications research group. His work focuses on advanced imaging techniques, particularly in the field of X-ray tomography and computed tomography. He collaborates extensively with researchers across multiple institutions and has made significant contributions to the development of imaging methodologies for both scientific and industrial applications. Dr. Myers' research interests span X-ray tomography, computed tomography, micro-CT imaging, image reconstruction algorithms, and beam hardening correction techniques. His work addresses fundamental challenges in imaging physics, including photon statistics, spectral information extraction, and dose reduction in imaging procedures. He has developed novel approaches for motion correction, alignment, and high-fidelity imaging of complex materials, particularly additively manufactured metal components. His research bridges theoretical physics with practical applications in materials science and non-destructive testing. Analysis of Dr. Myers' publication record reveals a strong focus on advancing X-ray imaging technologies, with particular emphasis on ghost imaging techniques, neutron imaging applications, and methods for improving image quality and reducing radiation dose. His work demonstrates consistent innovation in imaging methodology over the past decade, with applications spanning medical imaging, materials characterization, and environmental science. The interdisciplinary nature of his research connects physics, engineering, and materials science to solve complex imaging challenges. Key Collaborators: Andrew Kingston, Wilfred Fullagar, Shane Latham, Glenn Sheppard Research Group: X-ray tomography and applications group Primary Applications: Materials characterization, non-destructive testing, medical imaging

Michelle Yvonne Simmonsمشاهده پروفایل

استاد

• Quantum Computing
• Semiconductor Physics
• Nanotechnology
• +۴ مورد دیگر

Professor Michelle Simmons is the Director of the ARC Centre of Excellence in Quantum Computation and Communication Technology at the University of New South Wales (UNSW Sydney). Her work focuses on advancing silicon-based quantum computing through atomic precision engineering, including projects on 2-qubit gates and logical qubit architectures. Involves cryogenic measurement and microwave spin control Collaborates with Silicon Quantum Computing Pty. Ltd. Her research spans fundamental quantum mechanics, device fabrication in CMOS cleanrooms, and error correction for scalable quantum systems. Recent publications highlight trends in quantum dot arrays, spin readout sensitivity, and interdisciplinary applications of quantum technologies. Professor Simmons received the Esther Hoffman Beller Lectureship (2022) for her contributions to qubit manufacturing. She leads a dedicated team at UNSW, working toward the development of high-fidelity quantum processors and exploring the intersection of quantum materials and computational innovation.

Philip Romeroمشاهده پروفایل

دانشیار

• Protein Engineering
• Computational Biology
• Machine Learning
• +۳ مورد دیگر

Philip Romero, Ph.D., is an Associate Professor in the Department of Biomedical Engineering at Duke University. He earned his doctorate from the California Institute of Technology in 2012 and leads the Romero Lab, which relocated to Duke in 2023. His research focuses on developing computational and experimental methods for protein engineering, with applications spanning therapeutics, biocatalysis, and synthetic biology. Research Interests: Romero's work integrates machine learning, microfluidics, and high-throughput experimentation to study protein fitness landscapes. Key areas include: Self-driving laboratories for autonomous protein optimization Neural network models for predicting protein functions Therapeutic enzyme engineering (ACE2, caspases, lysins) Microfluidic platforms for deep mutational scanning His recent publications demonstrate a strong emphasis on machine learning-guided protein design, with 80% of post-2022 publications involving AI/ML methods. Therapeutic applications against infectious diseases (particularly SARS-CoV-2) and microbiome engineering represent emerging directions. Lab & Advising: The Romero Lab develops novel technologies for protein engineering, including custom gene library assembly platforms and droplet microfluidics systems. Romero mentors graduate students (e.g., Nishit, who recently defended a thesis on transcription factor engineering) and has collaborated with researchers across computational biology, metabolic engineering, and virology.

Tâm Le Minhمشاهده پروفایل

پژوهشگر

• Statistics
• Ecological Networks
• Nonparametric Statistics
• +۲ مورد دیگر

Tâm Le Minh is a postdoctoral researcher in statistics at Inria Grenoble Rhône-Alpes, focusing on model-based statistical methods and nonparametric models with latent variables. His work bridges statistical theory with applications in life sciences, particularly ecological network analysis. PhD in Applied Mathematics (2023), Université Paris-Saclay Master in Applied Mathematics (2020), Institut Polytechnique de Paris Background in aeronautics and software engineering His research spans U-statistics, row-column exchangeable matrices, and Bayesian nonparametric approaches, with applications to ecological networks and high-throughput sequencing data. Recent publications emphasize bipartite network analysis and variational annealing for optimization. He has presented at major conferences including the International Conference on Bayesian Nonparametrics, Bernoulli-IMS World Congress, and ISBA World Meeting. His work appears in journals like ESAIM: Probability and Statistics and the Electronic Journal of Statistics.

Marjan Firouzniaمشاهده پروفایل

پژوهشگر

• Medical Imaging
• Machine Learning
• Deep Learning
• +۳ مورد دیگر

Marjan Firouznia is a Principal Research Engineer at Linköping University , affiliated with the Division of Diagnostics and Specialist Medicine (DISP) under the Faculty of Medicine and Health Sciences . With a PhD in Electrical Engineering from Amirkabir University of Technology and postdoctoral experience at institutions like Case Western Reserve University, she specializes in advancing machine learning models for precise segmentation of cardiac structures including the left atrium , epicardial fat , and fibrosis using CT and MRI scans. Her work aims to improve diagnostic accuracy and treatment planning in cardiovascular care. Marjan's research focuses on medical imaging , deep learning , and computational anatomy , with recent publications on FractalRG , FK-means , and Poincare-guided UNet for cardiac structure segmentation. Her academic contributions span 15 recent publications , emphasizing fractal geometry , chaos theory , and optimization algorithms in biomedical applications. She actively develops open-source datasets and tools, such as the FK-means codebase , to support reproducibility in medical AI research.

Ricardo Deccaمشاهده پروفایل

استاد

• Condensed Matter Physics
• Fundamental Forces
• Nanoscale Imaging
• +۵ مورد دیگر

Ricardo Decca serves as Professor and Department Chair of Physics at Indiana University's College of Arts and Sciences, and co-directs the Nanoscale Imaging Center. His laboratory operates two custom-built Near-field Scanning Optical Microscopy (NSOM) systems for nanoscale investigations. His educational background includes a 1996 Post Doctorate in Physics from the University of Maryland, College Park; a 1994 Ph.D. in Physics from Instituto Balseiro, Universidad Nacional de Cuyo, Argentina; and a 1988 B.S. in Physics from the same institution. His research spans four primary domains: photodefined nanowires in high-temperature superconductors using NSOM-induced oxygen migration; spectroscopic analysis of quantum dots through photoluminescence and inelastic light scattering; NSOM-based tracking of fluorescent molecules in biomembranes to study diffusion properties; and experimental searches for deviations from Newtonian gravity at submicron ranges using isotope-coated microelectromechanical systems. Decca's experimental work focuses on precision force measurements at nanoscale dimensions, particularly investigating Casimir forces and potential new interactions beyond standard gravitational models. His laboratory develops specialized NSOM instrumentation operating from room temperature down to liquid helium conditions, enabling non-invasive studies of condensed matter systems. Current projects include characterizing photoinduced Josephson junctions in YBCO superconductors, quantifying dipole-dipole interactions between quantum dots, and visualizing nanoscale domains in lipid bilayers. As Department Chair and Co-Director of the Nanoscale Imaging Center, Decca oversees research infrastructure housing custom NSOM systems and microelectromechanical experimental apparatus. His laboratory maintains active collaborations in condensed matter physics and nanotechnology, with emphasis on developing novel techniques for force measurement and nanoscale characterization at the intersection of physics, materials science, and biophysics.

Clemens V. Verhooselمشاهده پروفایل

دانشیار

• Computational Mechanics
• Isogeometric Analysis
• Fluid Dynamics
• +۵ مورد دیگر

Clemens V. Verhoosel is an Associate Professor in Computational Methods for Model- and Data-Driven Engineering at Eindhoven University of Technology (TU/e). He holds positions in the Department of Mechanical Engineering under the Energy Technology and Fluid Dynamics section, and is affiliated with the EAISI Foundational initiative. His research focuses on scan-based immersed isogeometric analysis, uncertainty quantification, and Bayesian inference for complex engineering problems. He leads the Group Verhoosel and manages the Engineering Mechanics Graduate School since 2018. Education: MSc (Aerospace Engineering, TU Delft, 2005, cum laude PhD, TU Delft, 2009). Postdoctoral research at University of Texas at Austin (2009-2010). Awarded NWO VENI Grant (2011). Research interests include numerical methods for solid mechanics, fluid dynamics, coupled problems, and applications in biomedical engineering (e.g., cardiac mechanics). He develops open-source tools like the Nutils toolkit and collaborates with industry partners such as Evalf Computing. Key contributions include isogeometric analysis for fracture mechanics, phase-field models, and mesh-free simulation workflows. Honors: NWO Veni Award (2011). Teaching includes Advanced Discretization Techniques and Scientific Computing courses. Active in professional activities, including invited talks on cardiac mechanics and computational methods.