جستجوی استاد راهنمای دانشگاهی

Bingdong Changمشاهده پروفایل

پژوهشگر

• Nanofabrication
• Microelectromechanical Systems (MEMS)
• Plasma Processing
• +۳ مورد دیگر

Bingdong Chang is a Researcher at the Department of Civil and Mechanical Engineering, Technical University of Denmark (DTU), specializing in advanced nanofabrication and materials science. His work contributes significantly to UN Sustainable Development Goals through innovative engineering solutions. His research focuses on nanofabrication techniques including ice lithography, plasma etching, and nanowire synthesis. Key interests span Reactive ion etching optimization Nanocrystalline material development Semiconductor manufacturing processes Microelectromechanical systems (MEMS) Plasma diagnostics innovation with notable expertise in silicon processing and photoresist engineering. Chang's publication portfolio demonstrates strong trends in nanoscale manufacturing and materials characterization , particularly in lithography advancements and plasma processing. His work bridges fundamental materials science with practical applications in microdevice fabrication. His completed PhD project Technology Development for Silicon NEMS devices (2015-2019) established foundations in etching processes, microstructure analysis, and nanowire fabrication using zinc oxide. Current research extends into neuromodulation devices and advanced photopolymerization techniques. Chang actively collaborates internationally, with research networks spanning multiple continents. His laboratory work emphasizes precision nanofabrication techniques and novel material synthesis approaches for next-generation microdevices.

Anders Nymark Christensenمشاهده پروفایل

دانشیار

• Image Analysis
• Computer Vision
• Medical Imaging
• +۷ مورد دیگر

Anders Nymark Christensen is an Associate Professor in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU), specializing in Visual Computing. His work bridges computer vision, medical imaging, and materials science, with a strong focus on explainable AI in clinical applications and structural analysis of complex materials. Institution: Technical University of Denmark (DTU) School: Department of Applied Mathematics and Computer Science Department: Visual Computing Role: Associate Professor Christensen’s research interests include image analysis, computer vision, explainable AI, ultrasound imaging, fetal medicine, and fiber orientation in composites. He applies advanced computational techniques to solve real-world problems in healthcare and materials engineering, particularly through structure tensor analysis and deep learning. His recent publications highlight a strong trend in developing AI tools for clinical decision support in fetal medicine, structural analysis of food and composite materials, and ultrasound imaging. These works span journals such as Scientific Reports , Food Structure , and IEEE Access , reflecting interdisciplinary innovation. Clinical validation of explainable AI for fetal growth scans Characterization of anisotropy in mozzarella cheese Determining fetal orientations from ultrasound video Structure tensor analysis in composites He supervises several PhD students in projects related to AI in skin lesion analysis, cancer detection, and ultrasound imaging. His collaborative network includes key researchers at DTU such as Anders Bjorholm Dahl, Vedrana Andersen Dahl, and Mads Nielsen. He has been involved in significant research grants and is active in both medical and engineering domains, contributing to open datasets and reproducible research. Christensen leads and contributes to numerous active projects, including: Decision Support AI for Skin Lesions (2024–2027) Fighting Cancer with Generative AI (2024–2027) SONAI: Explainable AI in the Clinic (2022–2026) Deep learning for identifying biomarkers in medical images (2022–2025) His work supports UN Sustainable Development Goals related to health, innovation, and responsible consumption, particularly through advancements in medical diagnostics and sustainable materials.

Glyn Johnsonمشاهده پروفایل

استاد

• Medical Physics
• Magnetic Resonance Imaging (MRI)
• Clinical MRI Physics
• +۷ مورد دیگر

Glyn Johnson is a Professor of Clinical MRI Physics at Norwich Medical School, University of East Anglia, and an Adjunct Associate Professor of Radiology at New York University School of Medicine. He is also an Honorary Professorial Fellow and a member of Cancer Studies at UEA. His career spans leading institutions in the UK and the US, including the University of Aberdeen, Columbia University, and NYU, where he led the brain tumour imaging research group. BA in Natural Sciences (Physics and Theoretical Physics), University of Cambridge (1977) MSc in Medical Physics, University of Aberdeen (1978) PhD in Medical Physics, University of Aberdeen (1981) His research focuses on developing quantitative MRI techniques to improve diagnostic accuracy in cancer, particularly by distinguishing benign from malignant lesions. His work addresses challenges in lesion characterization using advanced MRI methods such as perfusion, diffusion, and sodium imaging. He has made seminal contributions to MRI physics, including co-developing spin warp imaging during his PhD. His recent publications show a strong trend in applying diffusion MRI and perfusion modeling to prostate and brain cancers, with increasing emphasis on computational and Monte Carlo modeling of tissue microstructure. He also contributes to interdisciplinary research linking nutrition, cognitive ageing, and neuroimaging. Notable scientific engagement includes membership in the ISMRM annual meeting program committee (2005–2007), ongoing service on NIH review panels, and extensive peer-review activity for academic journals since 1984. He has led multiple research projects funded by the National Institutes of Health and Abbott Nutrition, focusing on brain tumour imaging, cognitive ageing, and prostate cancer detection. His work is cited in policy and media, reflecting its translational impact. He is actively involved in collaborative research and continues to publish and secure grants, indicating ongoing academic leadership. Johnson is affiliated with research teams at UEA and NYU, and his projects often involve multi-institutional collaborations, particularly in neuroimaging and cancer studies.

Kumari Poojaمشاهده پروفایل

پژوهشگر

• Machine Learning
• Deep Learning
• Image Processing
• +۴ مورد دیگر

Kumari Pooja is a Marie Curie Doctoral Researcher and PhD Student at the Technical University of Denmark (DTU), affiliated with the Department of Applied Mathematics and Computer Science Visual Computing. She contributes to open-source computational tools and geometric modeling. Research Interests: Machine Learning and Deep Learning for imaging 3D Visualization and Fiber Tracking Medical Imaging and Hyperspectral Data Analysis Optimizing Computational Efficiency in Image Reconstruction Scientific Contributions: Her work spans 3D Python tool development , deep unrolled neural networks , and hyperspectral classification architectures , with a focus on robustness to noise and multi-scale analysis. Awards: Marie Curie Doctoral Researcher Fellowship Contact: pooja@dtu.dk

David Rudkoمشاهده پروفایل

دانشیار

• Neuroimaging
• MRI Methodology
• Biophysical Modeling
• +۵ مورد دیگر

David Rudko is an Associate Professor and Director of the 7T Pre-Clinical MRI Unit at the Montreal Neurological Institute-Hospital (The Neuro), a bilingual academic healthcare institution and McGill University research and teaching institute. He is part of the Brain Imaging Centre (BIC) Core Faculty and serves as a Killam Scholar. His work bridges advanced MRI technology development with neurological disease research, particularly focusing on multiple sclerosis and other neuroimmunological conditions. Dr. Rudko's research centers on the application of novel MRI methodology in conjunction with biophysical modeling to enhance understanding of brain anatomy and physiology. His laboratory develops cutting-edge MRI physics acquisition and post-processing techniques for mapping myelin density, axonal packing, and axonal geometry. A key focus is on ultra-high field (UHF, >3T) MRI, where his team addresses critical challenges including RF field homogenization and static magnetic field inhomogeneities. The lab utilizes both small animal (7T) and human MRI/MRS (3T, 7T) systems in conjunction with optical microscopy and advanced image processing methods. Analysis of Dr. Rudko's recent publications reveals a strong emphasis on multiple sclerosis research using advanced MRI techniques. His work spans from fundamental MRI physics development to clinical applications, with particular attention to cortical pathology, white matter lesions, and iron metabolism in neurological disorders. His research group has made significant contributions to understanding the microstructural basis of neurological diseases through innovative imaging approaches that bridge cellular-level observations with macroscopic imaging metrics. Killam Scholar Dr. Rudko leads the Rudko Lab, which is affiliated with both the Neuroimaging and Neuroinformatics Research Group and the Neuroimmunological Diseases Research Group at The Neuro. His laboratory focuses on developing and applying advanced MRI techniques to understand the cellular and microstructural basis of neurological diseases, with particular emphasis on multiple sclerosis. The lab utilizes a multidisciplinary approach combining physics, engineering, neuroscience, and clinical medicine to advance both the technical capabilities of MRI and its applications to neurological disorders.

Ryan Dehoffمشاهده پروفایل

پژوهشگر

• Additive Manufacturing
• 3D Printing
• Materials Science
• +۳ مورد دیگر

Ryan Dehoff is a leading researcher at Oak Ridge National Laboratory (ORNL) , where he serves as the Director of the Manufacturing Demonstration Facility and Technical Area Lead for Advanced Manufacturing under the Nuclear Energy AMMT Program. His work focuses on additive manufacturing (3D printing) of metals and alloys, integrating digital thread for certification of advanced components. Education: Ph.D., Materials Science & Engineering, The Ohio State University (2008) M.S., Materials Science & Engineering, The Ohio State University (2005) B.S., Materials Science & Engineering, The Ohio State University (2002) Ryan's research spans process development in electron beam melting, laser metal deposition, and ultrasonic additive manufacturing. He explores material performance to enhance energy efficiency, reduce waste, and improve scalability. His projects include near-net-shape titanium fabrication and laser processing of nanocomposite coatings . His 15 most recent publications address topics such as irradiation capsule design , phase stability in intermetallic compounds , and deep learning-based defect detection . These works reflect trends in nuclear engineering , materials characterization , and data-driven manufacturing platforms . Scientific Awards: 2013 UT Battelle Early Career Award for Engineering 2012 R&D 100 Awards for NanoSHIELD Coating and Low-Cost Robotic Hand 1997–2007 Scholarships and Fellowships from The Ohio State University and NASA/DoD URETI

Robert Kirchnerمشاهده پروفایل

دانشیار

• 3D Lithography
• Micro-Electro-Mechanical Systems
• Nano-Electro-Mechanical Systems
• +۴ مورد دیگر

Dr. Robert Kirchner serves as Group Leader at the Center for Advancing Electronics Dresden (cfaed) at Dresden University of Technology, where he heads the Mesoscopic 3D Systems Group. Since 2017, he has held a prestigious DFG Heisenberg Stipendiat position, focusing on advanced 3D fabrication technologies. His research group is closely associated with the HETEROMERGE startup project, which develops innovative hardware solutions for multi-material 3D printing on two-photon systems with unprecedented precision and speed. Dr. Kirchner's academic journey includes: PhD (Dr.Ing.) in Electrical Engineering from Dresden University of Technology and Fraunhofer Institute for Photonic Microsystems (2007-2011) Diploma in Electrical Engineering from Dresden University of Technology and Chalmers University of Technology in Gothenburg, Sweden (2001-2007) His research program centers on high-resolution 3D lithography techniques including electron beam lithography (EBL), two-photon polymerization (2PP), and extreme ultraviolet (EUV) lithography. He investigates self-optimization and self-organization processes in mesoscopic systems, particularly Micro-Electro-Mechanical Systems (MEMS) and Nano-Electro-Mechanical Systems (NEMS). His work explores material characterization and the modification of polymer properties through high-energy radiation exposure, along with computational modeling of surface effects on polymer melts. The Kirchner Group develops novel approaches to 3D micro- and nanofabrication with applications spanning micro-optics, plasmonics, and multi-material integration for advanced devices. Analysis of Dr. Kirchner's publication record reveals a clear trajectory from fundamental fabrication techniques toward increasingly complex multi-material systems and commercial applications. His early work focused on basic lithography and surface modification techniques, while recent publications emphasize practical implementations in multi-material 3D printing, plasmonic structures, and MEMS integration. The establishment of HETEROMERGE represents a significant commercialization effort translating academic research into industry-ready technology for multi-material 3D printing at nanoscale resolution. Dr. Kirchner's most significant recognition is the DFG Heisenberg Stipendiat award, which supports exceptional researchers on the path to professorship in Germany. His work has secured substantial research funding, including affiliation with Research Training Group 2767 "Supracolloidal Structures: From Materials to Optical and Electronic Devices" funded by the Deutsche Forschungsgemeinschaft. DFG Heisenberg Stipendiat (2017-present) Dr. Kirchner actively mentors multiple PhD students and postdoctoral researchers in his group. His HETEROMERGE startup project demonstrates successful technology transfer from academic research to commercial application, offering hardware solutions that enable multi-material 3D printing at highest resolution with 10 nm placement accuracy. The group maintains active collaborations with institutions including Paul Scherrer Institute in Switzerland and participates in multiple research consortia focused on advanced micro- and nanofabrication techniques. The Mesoscopic 3D Systems Group operates within the Center for Advancing Electronics Dresden (cfaed), one of Germany's Clusters of Excellence. The group maintains state-of-the-art facilities for micro- and nanofabrication and collaborates closely with the HETEROMERGE startup team. Their research environment fosters innovation in 3D fabrication technologies, with particular emphasis on overcoming current limitations in multi-material integration, resolution, and printing speed for applications in micro-optics, integrated photonics, and MEMS/NEMS devices.

Yingxin Linمشاهده پروفایل

پژوهشگر

• Bioinformatics
• Statistical Genetics
• Computational Biology
• +۳ مورد دیگر

Dr. Yingxin Lin is a Researcher at the School of Mathematics and Statistics , University of Sydney , specializing in Bioinformatics and related fields. Their work spans interdisciplinary applications in biomedical engineering , biostatistics , and materials science , focusing on bone regeneration , bioceramics , and computational modeling of bone metabolism . Current Position: Researcher, Department of Statistics Email: yingxin.lin@sydney.edu.au Research Interests include: Bioinformatics applied to gene expression , signal transduction , and statistical modeling in bone biology . Biostatistical analysis of biomaterials and regenerative medicine outcomes. Computational modeling of bone remodeling and metastatic processes . Recent Publications reveal a focus on 3D-printed scaffolds , mitochondrial-targeting drugs , and biomechanical factors in bone repair and cancer progression . These works employ bioinformatics , biostatistics , and materials science to address osteoporosis , bone metastasis , and biomedical device development . Collaborative Networks include Supervisor: YH Yang Auxiliary Supervisor: JT Ormerod with no current students listed.

• Additive Manufacturing
• Friction Stir Welding
• Gas Metal Arc Welding
• +۴ مورد دیگر

Vincenzo Lunetto is a part-time lecturer at the Department of Management and Production Engineering (DIGEP) of Politecnico di Torino (PoliTO). He also serves as a member of the Interdepartmental Center J-Tech@PoliTO and has held visiting researcher roles at the University of New South Wales (2019-2020) and contract professorship at Libera Università di Bolzano (2018-2019). Current affiliation: PoliTO (DIGEP) Secondary roles: J-Tech@PoliTO center member International experience: UNSW (Australia), Bolzano (Italy) His research focuses on sustainable manufacturing practices, particularly additive manufacturing (powder bed fusion, electron beam systems), friction stir welding (tool design, process parameters), and energy consumption modeling. He investigates microstructural properties of welded components and sustainability implications across production systems. Recent publications highlight neural network-based energy prediction in additive manufacturing, defect analysis in dissimilar welding joints using 3D X-ray tomography, and comparative studies on hybrid manufacturing processes. His work spans both experimental and computational approaches to optimize energy efficiency and material performance. Scientific Recognition: Effective member of AITEM - Associazione Italiana delle Tecnologie Manifatturiere since 2022.

• Civil Engineering
• Materials Science
• Environmental Engineering
• +۲ مورد دیگر

Dr. Yue Liu is a Research Fellow at the University of South Australia, affiliated with the UniSA STEM division. As an ARC Discovery Early Career Researcher, they specialize in sustainable construction materials and environmental engineering, focusing on industrial waste valorization for concrete applications. Research Degree Supervisor Expert in alkali-activated materials and self-healing concrete Research Focus: Investigates waste-to-resource strategies for cementitious systems, including sludge-based composites, biochar concrete, and graphene-enhanced materials. Key areas involve carbon-negative composites, durability optimization, and 3D printed structural elements. Scientific Awards: ARC Discovery Early Career Researcher Award Publication Trends: Recent work (2024-2025) demonstrates expertise in functional materials, covering triaxial concrete mechanics, chloride resistance, nanofiber reinforcement, and industrial byproduct recycling. Emphasis on environmental performance assessment and multi-objective optimization. Supervision & Grants: Actively supervises research degrees while leading projects funded by the Australian Research Council, developing low-carbon construction solutions through material innovation and lifecycle analysis.

• Calculus of Variations
• Partial Differential Equations
• Homogenisation
• +۹ مورد دیگر

Lucia Scardia is an Associate Professor in the Department of Mathematics at Heriot-Watt University (Edinburgh EH14 4AS). Her research focuses on calculus of variations, partial differential equations, homogenisation (deterministic and stochastic), and harmonic analysis, with applications in material science including plasticity, dislocations, non-local aggregation problems, nonlinear elasticity, and fracture theories. Research Focus Primary research domains include: Variational methods for PDEs and homogenisation Mathematical modeling of dislocations and plasticity Stochastic analysis of material defects Nonlocal interaction problems and fracture mechanics Anisotropic energy minimization Publication Trends Recent publications (2019-2025) demonstrate strong focus on: Homogenisation techniques in stochastic/perforated domains; variational analysis of anisotropic/nonlocal energies; explicit minimisers for Coulomb/Riesz interactions; free-discontinuity problems; and mathematical descriptions of dislocation patterns. Work consistently employs Gamma-convergence and variational methods. Student Supervision & Grants Supervised 18+ students including PhD candidate Xavier Pellet (2015-2019) and numerous Bachelor/Master projects on variational methods, dislocations, and PDEs. Major grants include: EPSRC EP/V00204X/1: Mathematical Theory of polycrystalline materials (£576,848, 2021-2024) EPSRC EP/V008897/1: Generalised Solutions of Nonlinear PDEs (£35,960, 2021-2024) EPSRC First Grant EP/N035631/1: Dislocation Patterns beyond equilibrium (£95,699, 2016) Academic Leadership Organizes major conferences including 'Optimal Transport and Calculus of Variations' (ICMS 2023) and 'Polycrystals: Microstructure and Plasticity' (ICMS 2022). Co-founder of the 'One World PDE seminar' (2021-present).

Emanuel Larssonمشاهده پروفایل

پژوهشگر

• X-ray Tomography
• Neutron Tomography
• Synchrotron Imaging
• +۵ مورد دیگر

Emanuel Larsson serves as a Researcher at Lund University's Department of Experimental Medical Science within the Faculty of Medicine. He holds dual institutional roles as Assistant Director at LINXS (Institute of Advanced Neutron and X-ray Science) and as a staff member at MAX IV Laboratory. His operational framework spans national infrastructure coordination including CIPA (Correlative Image Processing and Analysis), InfraVis (National Research Infrastructure for Data Visualization), and HALRIC (Hanseatic Life Science Research Infrastructure Consortium). His research centers on advanced tomographic imaging techniques , specializing in X-ray and neutron tomography for multiscale materials characterization. Key application areas include food science (starch foams), nanomaterials (photonic crystals, nanoporous gold), and biomedical engineering. His work integrates synchrotron radiation methods with machine learning approaches for 3D microstructure analysis, contributing to UN Sustainable Development Goals through materials innovation. Analysis of his 32 publications reveals dominant themes in materials microstructure visualization across food systems, nanocomposites, and reference standards development. His imaging methodologies bridge physics, engineering, and life sciences with emphasis on correlative techniques that combine multiple imaging modalities for comprehensive material analysis. Larsson actively leads infrastructure development through current projects including CIPA (2020-2027), Marine Centre Simrishamn, and MICROMORPH (2026-2028). His organizational roles include coordinating the 2024 SynchroMage hackathon focused on environmental/climate applications of tomography. He manages critical research infrastructure including Correlative Image Processing and Analysis and InfraVis national visualization systems. His laboratory ecosystem operates at the intersection of MAX IV Laboratory's synchrotron facilities, LINXS neutron science infrastructure, and Lund University's medical research environment. Current initiatives involve µCT machine learning integration for morphological diversity analysis and correlative X-ray tomography for membrane studies in food processing applications.

Michele Terzanoمشاهده پروفایل

پژوهشگر

• Biomechanics
• Cardiovascular Engineering
• Computational Modeling
• +۴ مورد دیگر

Michele Terzano is a University Assistant at the Institute of Biomechanics , Graz University of Technology, Austria. Previously, he held postdoctoral positions at Graz (2021-2023) and the University of Parma (2020-2021), with academic visitor roles at Imperial College London (2019-2021). Ph.D. in Civil Engineering (2020), University of Parma M.Sc. in Civil Engineering (2016), University of Parma B.Sc. in Civil Engineering (2016), University of Parma His research spans biomechanics of soft tissues and synthetic polymers , focusing on damage/fracture mechanisms , computational modeling , and robotics in neurosurgery . Key applications include cardiovascular interventions, brain tissue simulation, and tissue engineering hydrogels. The 15 most recent publications reflect trends in multiscale biomechanical modeling (e.g., atherosclerotic arteries, abdominal aortic aneurysms), soft tissue characterization (e.g., SHG microscopy for skin mechanics), and biomaterials development (e.g., poro-viscoelastic hydrogels for brain tissue mimicry). These works integrate experimental data with computational frameworks to address clinical challenges. Scientific awards include a 2020 postdoctoral fellowship at the University of Parma and collaboration on EU-funded Horizon 2020 projects. He teaches Biomedical Engineering courses in Graz while maintaining active research in computational fracture mechanics and bioinspired materials.

• Materials Science
• Mechanical Engineering
• Finite Element Analysis
• +۳ مورد دیگر

Mariana Dimitrova Ichkova is a Lecturer at the Technical University - Gabrovo , affiliated with the Faculty of Mechanical Engineering and Instrument Making and the Department of Materials Science and Mechanics of Materials . Email: ichkova@tugab.bg Her research focuses on residual stress analysis , finite element modeling of cold working processes, and mechanical behavior of aluminum and steel alloys . Key areas include surface treatment optimization, thermo-mechanical simulations, and strengthening techniques for fastener holes. Over the past decade, her work has emphasized finite element simulations for residual stress modeling, cold expansion of holes, and creep behavior in aluminum alloys. Publications span both Bulgarian and international journals, with a strong focus on materials processing and structural integrity applications.

• Materials Physics
• Porous Media
• X-ray Tomography
• +۲ مورد دیگر

Dr. Mahyar Madadi is a Research Fellow at the Australian National University , affiliated with the Materials Physics department. His work focuses on computational analysis of porous and granular materials using advanced imaging techniques like X-ray tomography. Research Interests Dr. Madadi's research spans multiple disciplines including Materials Physics , Geophysics , and Computational Modeling . Key areas of investigation include pore-scale fluid dynamics, elastic properties of granular media, and microstructural analysis of carbonates and foams. Publications His work demonstrates strong expertise in digital rock physics and computational materials science , with significant contributions to understanding relationships between microstructure and macroscopic properties in diverse systems from geological formations to synthetic foams.