جستجوی استاد راهنمای دانشگاهی

Jean-Philippe Thiranمشاهده پروفایل

استاد

• Computational Imaging
• Medical Image Analysis
• Diffusion MRI
• +۵ مورد دیگر

Prof. Jean-Philippe Thiran is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), where he serves as Director of the Signal Processing Laboratory (LTS5) and Director of the Institute of Electrical and Micro Engineering. He also maintains a part-time Associate Professor position with the Department of Radiology of the University Hospital Center (CHUV) and University of Lausanne (UNIL). Born in Namur, Belgium in 1970, he received his Electrical Engineering degree and PhD from the Université catholique de Louvain (UCL), Belgium, in 1993 and 1997 respectively. He joined EPFL in 1998 and has established himself as a leading researcher in computational imaging. His research focuses on computational imaging , with significant contributions to medical image analysis (particularly diffusion MRI, ultrasound imaging, and digital pathology) and computer vision . His recent work integrates advanced modeling, simulation, and machine learning techniques to extract microscopic tissue information from macroscopic MRI signals. This approach combines hyper-realistic synthetic tissue models, advanced Monte-Carlo simulations, and ML-based estimation techniques for brain microstructure analysis with potential applications to other tissues. Senior Member of IEEE Fellow of the European Association for Signal Processing (EURASIP) Prof. Thiran has authored or co-authored 1 book, 9 book chapters, 250 journal papers and over 270 peer-reviewed conference papers, and holds 12 international patents. He previously served as Co-Editor-in-Chief of the Signal Processing journal (2001-2005) and associate editor of IEEE Transactions on Image Processing. He has chaired major conferences including EUSIPCO 2008 and IEEE ICIP 2015. His laboratory at EPFL brings together interdisciplinary researchers to develop innovative imaging techniques that bridge macroscopic measurements and microscopic tissue properties, with significant potential for medical diagnostics and treatment planning applications.

Andrew Spakowitzمشاهده پروفایل

استاد

• Chromosomal organization and dynamics
• Protein self-assembly
• Polymer membranes
• +۷ مورد دیگر

Andrew Spakowitz is a Professor of Chemical Engineering, Materials Science and Engineering, and by courtesy, Applied Physics and Chemistry at Stanford University. He currently serves as the Senior Associate Dean for Research and Faculty Affairs and holds the Tang Family Foundation Chair of the Department of Chemical Engineering. His academic career at Stanford spans from Assistant Professor (2006-2014) to Associate Professor (2014-2020) and now Professor since 2020. Dr. Spakowitz earned his PhD in 2004, MS in 2001 from the California Institute of Technology, and his BS in Chemical Engineering from the University of Wisconsin, Madison in 1999. He completed postdoctoral training in Molecular and Cell Biology and Biophysics at UC Berkeley from 2004-2006. His research focuses on theoretical and computational approaches to understanding biological processes and complex materials. The Spakowitz lab addresses fundamental chemical and physical phenomena through four main research themes: chromosomal organization and dynamics, protein self-assembly, polymer membranes, and charge transport in conducting polymers. His group employs diverse theoretical and computational methods including analytical theory of semiflexible polymers, polymer field theory, continuum elastic mechanics, Brownian dynamics simulation, equilibrium and dynamic Monte Carlo simulations, and reaction-diffusion modeling. Analysis of his recent publications reveals a strong emphasis on epigenetics and chromatin dynamics, with significant work on DNA methylation patterns, nucleosome clustering, and chromosome organization. His research also extends to polymer physics applications in biological systems, particularly in respiratory diseases, water purification membranes, and bacterial phage interactions with human mucus. Tang Family Foundation Chair of the Department of Chemical Engineering Professor Spakowitz mentors several graduate students and postdoctoral scholars in the Chemical Engineering and Materials Science departments. His lab members work on diverse projects spanning from chromatin dynamics to polymer membranes for water purification. He teaches multiple courses including CHEMENG 120B (Energy and Mass Transport), CHEMENG 340 (Molecular Thermodynamics), CHEMENG 466 (Polymer Physics), and CHEMENG 467 (Physics of Biomacromolecules). The Spakowitz lab operates from Clark S295 at Stanford University, conducting theoretical and computational research that bridges chemistry, physics, biology, and engineering disciplines to address complex problems across multiple length and time scales.

• Inverse problems and reconstruction
• Neuroimaging
• Quantitative MRI
• +۱ مورد دیگر

Daan Christiaens is a tenure track lecturer at KU Leuven's Faculty of Medicine and Faculty of Engineering Sciences. He is affiliated with the Department of Electrical Engineering (ESAT) and Department of Imaging & Pathology, serving as a member of the Medical Imaging Division and the KU Leuven Brain Institute (LBI). His academic responsibilities include membership in the Faculty Councils of Engineering Sciences and Medicine. His research focuses on: Inverse problems in medical imaging reconstruction Neuroimaging techniques for brain analysis Advanced quantitative MRI methodologies Diffusion-weighted imaging for microstructural assessment Dr. Christiaens' recent publications (2023-2025) demonstrate a consistent focus on diffusion MRI innovations, including novel reconstruction algorithms, neonatal brain development mapping, and clinical applications for neurodegenerative disorders. Key technical themes include motion correction, multi-shell modeling, and AI-enhanced image processing, while clinical applications span Alzheimer's disease, cerebral palsy, and autism research. He leads significant research projects including: MRI reconstruction with dynamic field monitoring (2024-2028) Compressed sensing for microstructure imaging (2022-2026) Neonatal diffusion MRI network connectivity analysis (2024-2028) As a core developer of the MRtrix3 software framework for medical image processing, he contributes to essential tools in neuroimaging research.

• Medical Image Analysis
• Machine Learning in Medical Imaging
• Neuroimaging
• +۵ مورد دیگر

Lawrence Staib is Professor of Radiology and Biomedical Imaging, Biomedical Engineering, and Electrical Engineering at Yale University. He serves as Director of Undergraduate Studies in Biomedical Engineering and is a member of Yale's Bioimaging Sciences division, Image Processing & Analysis Group, Yale Biomedical Imaging Institute, and Yale-BI Biomedical Data Science Fellowship program. Dr. Staib earned his A.B. in Physics from Cornell University (1982), followed by a Ph.D. in Engineering and Applied Science from Yale University (1990), and completed a postdoctoral fellowship at Yale School of Medicine (1991). His research focuses on developing advanced medical image analysis methods using machine learning and model-based approaches. Key research areas include neuroimaging applications for autism spectrum disorder classification, cardiac imaging analysis for strain and motion assessment, prostate cancer diagnosis and risk mapping, and innovative techniques for medical image segmentation with limited labeled data. Dr. Staib's work emphasizes uncertainty estimation in deep learning models, multi-modal image registration, and domain adaptation techniques to improve clinical decision support systems. His recent publications demonstrate a strong trend toward developing interpretable AI models for clinical applications, with particular emphasis on fMRI analysis for neurological conditions, cardiac motion analysis, and prostate cancer diagnosis. His work frequently addresses the challenge of limited labeled data in medical imaging through innovative self-supervised, semi-supervised, and few-shot learning approaches. Fellow of the American Institute for Medical and Biological Engineering (AIMBE) (2015) Distinguished Investigator Award from the Academy for Radiology & Biomedical Imaging Research (2017) MICCAI Fellow (2022) Medical Image Analysis Second Best MICCAI Paper Award (2005) ASNR Cum Laude Scientific Exhibit Award (2003) Dr. Staib serves on the editorial board of Medical Image Analysis and as Associate Editor of IEEE Transactions on Biomedical Engineering. His research is supported by NIH grants including the Autism Center of Excellence program. He leads the Image Processing & Analysis Group within Yale's Bioimaging Sciences division, collaborating extensively with James Duncan, John Onofrey, Xenophon Papademetris, and other Yale researchers on applications spanning neuroimaging, cardiology, and oncology. Current projects focus on developing robust AI models for clinical decision support with emphasis on uncertainty quantification and interpretability.

Roger Tamمشاهده پروفایل

دانشیار

• Medical Imaging
• Machine Learning
• Quantitative Image Analysis
• +۳ مورد دیگر

Roger Tam is an Associate Professor in the School of Biomedical Engineering (SBME) at the University of British Columbia (UBC), with a joint appointment in the Department of Radiology. He is also the Associate Director of Graduate Studies. His research focuses on machine learning and computer vision applied to medical imaging, particularly in personalized medicine and quantitative image analysis. Tam earned his PhD in computer science from UBC in 2004, specializing in computational geometry and visualization. Education: PhD in Computer Science, UBC (2004) MSc in Computer Science BSc (Honors) Research Interests: Medical imaging biomarkers Machine learning applications in healthcare Quantitative image analysis Personalized medicine His work bridges computer science and clinical medicine, emphasizing translational approaches to improve diagnostic accuracy and patient outcomes. Recent Research Trends: Focus on myelin content analysis in neurological disorders (e.g., multiple sclerosis) Development of efficient machine learning models for medical image classification Impact of physical activity on white matter health Labs & Programs: Directs the Engineers in Scrubs program, which integrates engineering principles into biomedical education. Active in collaborative research initiatives like the Centre for Brain Health and the Canadian Prospective Cohort Study (CanProCo).

Vikram Deshpandeمشاهده پروفایل

استاد

• Mechanobiology
• Solid mechanics
• Data-driven mechanics
• +۴ مورد دیگر

Vikram Deshpande is a Professor in the Department of Engineering at the University of Cambridge, UK, where he has been employed since 2010. He also maintains significant international connections, having served as a Visiting Professor at the Technical University of Eindhoven (2009-2017) and previously holding positions at the University of California, Santa Barbara and Brown University. His research spans multiple disciplines within solid mechanics and materials science, focusing on fundamental mechanisms that govern material behavior across different scales. His research interests encompass Mechanobiology , where he explores cellular organization mechanisms; Solid mechanics with applications to impact and failure; Data-driven mechanics approaches; Microarchitectured solids including mechanical metamaterials; Fluid-structure interaction in impact scenarios; Chemo-mechanics of battery materials; and Dislocation mechanics for understanding material deformation. His work uniquely bridges fundamental physics with practical engineering applications, particularly in developing materials with tailored mechanical properties. The analysis of his recent publications reveals a strong focus on mechanical metamaterials, cellular mechanics, and electro-chemo-mechanical phenomena in energy storage systems. His research demonstrates a consistent pattern of addressing fundamental scientific questions while maintaining strong connections to practical engineering applications, particularly in materials design, protective systems, and energy technologies. His publications frequently combine experimental approaches with sophisticated modeling techniques across multiple scales. 2024 Zdeněk P. Bažant Medal for Failure and Damage Prevention 2023 Fellow, Royal Academy of Engineering and International Member US National Academy of Engineering 2022 Warner T. Koiter Medal and William Prager Medal 2022 European Research Council (ERC) Advanced Grant 2021 Gili Agostinelli Prize and IIT Bombay Distinguished Alumnus Award 2020 Fellow, Royal Society of London and Rodney Hill Prize Professor Deshpande has served on numerous editorial boards including the Journal of the Mechanics and Physics of Solids (current Associate Editor), Modelling and Simulation in Materials Science and Engineering, and Proceedings of the Royal Society A. He chairs the Royal Society Sectional Committee 4 and serves on the Advisory Board of the European Mechanics Society EUROMECH. His leadership extends to directing the International Conference on Fracture and chairing the EUROMECH Mechanics of Materials Conference committee. His research group at Cambridge, accessible through cambridgesolidmechanics.co.uk, focuses on developing fundamental understanding of material behavior to enable the design of next-generation engineering materials.

Christine Tardifمشاهده پروفایل

استادیار

• MRI-based Neuroimaging
• Quantitative MRI (qMRI)
• Biophysical Modeling
• +۸ مورد دیگر

Christine Tardif is an Assistant Professor in the Department of Biomedical Engineering and the Department of Neurology and Neurosurgery at McGill University. As head of the McConnell Brain Imaging Centre lab at the Montreal Neurological Institute, she develops advanced MRI techniques for in-vivo brain imaging, focusing on quantitative mapping of myelin and cortical microstructure. Her work spans methodological innovation (e.g., multi-modal biophysical modeling) and translational applications across preclinical (7 Tesla) and clinical (3 and 7 Tesla) systems. Undergraduate: B.Eng. in Computer Engineering, McGill University (2004) Master's: M.Sc. in Bioengineering, Imperial College London (2006) PhD: Biomedical Engineering, McGill University (2011) Her research explores myelin dynamics in health and disease, emphasizing its role in neural conduction, brain plasticity, and cognitive functions. The lab investigates dysmyelination in psychiatric disorders (e.g., bipolar disorder) and neurodegenerative conditions (e.g., multiple sclerosis) using relaxometry , magnetization transfer , and diffusion-weighted imaging . Recent methodological work includes 3D MERMAID sequences for motion-insensitive diffusion imaging and optimization of magnetization transfer saturation maps. Current projects integrate ultra-high field MRI with histological validation in preclinical models (e.g., marmoset brain sections), aiming to bridge microstructural metrics with macro-scale brain function. Applications span Alzheimer's disease risk assessment via white matter alterations, synaptic density mapping in psychosis, and cortical laminar differentiation studies.

Henrik Myhre Jensenمشاهده پروفایل

استاد

• Mechanics of Materials
• Solid Mechanics
• Mechanical Engineering
• +۴ مورد دیگر

Henrik Myhre Jensen is a Professor at the College of Engineering , Aarhus University, specializing in Mechanics of Materials , Solid Mechanics , and Mechanical Engineering . His research focuses on fracture mechanics, composite materials, and computational modeling of structural behaviors. Research Focus Fracture mechanics in composites and layered materials Computational modeling of kink band propagation Surface wear and coating technologies Ultrasound imaging applications in mechanical systems Notable Contributions Henrik has contributed to understanding crack propagation in cantilever beams, developed numerical methods for simulating delamination in composites, and explored buckling instabilities in solids. His recent work connects machine learning (holomorphic neural networks) to traditional fracture mechanics problems. Key Projects MAGFLY (2017-2021): Magnets for Flywheel Energy Storage InnoVacc (2009): Pressure Testing of Vacuum Chambers Simulation of composite structures (2011-2020): Micro-mechanical modeling

• Optical fiber technology
• Photonics
• Biosensors
• +۵ مورد دیگر

Dr. Stephen Warren-Smith is a Senior Research Fellow at the Future Industries Institute, University of South Australia (UniSA), where he conducts cutting-edge research in optical fiber technology and photonics. He is affiliated with the Laser Physics and Photonic Devices Laboratories within UniSA STEM (Science, Technology, Engineering and Mathematics), and serves as a Research Degree Supervisor for graduate students. Dr. Warren-Smith's primary research interests span optical fiber technology, photonics, and biosensors, with a particular focus on developing novel fiber optic sensing platforms for biomedical and environmental applications. His work encompasses microstructured optical fibers, fluorescence sensing, and the integration of machine learning techniques for enhanced sensor performance. He has made significant contributions to the fields of harmonic generation in optical fibers, NV center-based quantum sensing, and multimode fiber applications. Analysis of Dr. Warren-Smith's recent publications reveals a strong trend toward developing sophisticated fiber optic sensing platforms with diverse applications. His work demonstrates increasing integration of advanced materials (like diamond with NV centers) and computational methods (particularly deep learning) to overcome traditional limitations in optical sensing. The research spans fundamental physics of light-matter interactions in fibers to practical applications in medical diagnostics, environmental monitoring, and industrial process control. A notable pattern is the development of multi-parameter sensing capabilities within single fiber platforms, enabling simultaneous measurement of various physical and chemical properties. Dr. Warren-Smith has secured significant research funding including ARC Future Fellowships (FT200100154), ARC Discovery Projects (DP190102896), and support from the Australian National Fabrication Facility (Optofab Node) utilizing Commonwealth and South Australian State Government resources. His research has received substantial citation counts, with several papers cited multiple times in Web of Science and Scopus. Dr. Warren-Smith leads research activities within the Laser Physics and Photonic Devices Laboratories at UniSA STEM. His team specializes in the design, fabrication, and characterization of advanced optical fiber devices, with particular expertise in microstructured optical fibers, suspended core fibers, and integrated photonic sensing platforms. The laboratory maintains strong connections with the Australian National Fabrication Facility (Optofab Node) for advanced device fabrication capabilities and collaborates extensively with institutions including RMIT University, University of Melbourne, University of Adelaide, and international partners in China.

Travis B. Thompsonمشاهده پروفایل

استادیار

• Mathematical Modeling
• Scientific Computing
• Machine Learning in Medicine
• +۵ مورد دیگر

Travis B. Thompson, Ph.D. is an Assistant Professor in the Department of Mathematics and Statistics at Texas Tech University, leading the TM4 (Texas Tech Translational and Theoretical Mathematical Modeling and Machine Learning in Medicine) research group. His academic journey includes postdoctoral work at Rice University, Simula Research Laboratory, and the University of Oxford, focusing on mathematics applied to neurodegenerative diseases. Education: Ph.D. in Mathematics from Texas A&M University (2013) Dr. Thompson develops theoretical mathematical models and applies scientific computing and machine learning to study neurological pathologies, particularly Alzheimer’s disease. His work explores complex biological processes on networks, translational healthcare applications, and nutritional security implications. Current research trends integrate neuroimaging data with finite element simulations to model tau progression , amyloid beta dynamics , and glymphatic clearance in age-related diseases. Scientific awards and honors were not explicitly mentioned in the provided materials. Dr. Thompson’s interdisciplinary approach connects computational neuroscience with biomedical engineering , utilizing techniques like diffusion tensor imaging and level set methods to analyze pathological protein spread and brain tissue mechanics . The TM4 research group focuses on network neurodegeneration , personalized medicine , and machine learning diagnostics . Their work spans from microfluidic cancer detection to computational modeling of brain clearance mechanisms , addressing challenges in both neurodegenerative diseases and biomedical engineering through rigorous mathematical frameworks.

• low dimensional magnetism
• hydrogen in metals
• neutron scattering
• +۷ مورد دیگر

Björgvin Hjörvarsson is a Professor in Physics at Uppsala University's Department of Physics and Astronomy, specifically within the Materials Physics division where he served as Head until 2024. He is Principal Investigator of the Super ADAM project, Sweden's national neutron facility, and an elected member of both the Royal Academy of Sciences and the Royal Society of Sciences in Uppsala. His research spans low-dimensional aspects of phase transitions, particularly in magnetism and hydrogen in metals. His work has evolved to emphasize finite size effects on structural and magnetic ordering, additive manufacturing, and energy storage and transformation. His research methodology heavily relies on neutron scattering techniques and international collaborations across experimental and theoretical physics. Hjörvarsson's recent publications (2022-2025) reveal a strong focus on metallic glasses produced via additive manufacturing, artificial spin ice systems, magnetic superlattices, and advanced characterization techniques. His work bridges fundamental physics with practical applications in energy storage, materials engineering, and biomedical technologies. Vattenfalls Energistipendium (1985) Liljewalchs scholarship (1989) Good-Guy Award from Fysiska Sällskapet (1990) Idée award from Uppsala University (1995) Benzelius award from Royal Society of Sciences of Uppsala (1995) Letterstedtska award from Royal Swedish Academy of Sciences (2003) Hjörvarsson has supervised 27 PhD students to completion, 1 licenciate student, and currently guides 9 PhD students while supervising 2-3 master's students annually. His research is supported by significant infrastructure including the Super ADAM neutron facility at ILL, Grenoble, which he initiated and developed as Sweden's national neutron scattering infrastructure. Beyond traditional research, he's known for innovative outreach efforts including educational videos on neutron science. Hjörvarsson leads the Materials Physics research group, which maintains strong international collaborations and focuses on experimental condensed matter physics with connections to engineering applications. His team operates specialized laboratories for thin film growth, magnetic characterization, and neutron scattering experiments, supporting both fundamental research and industrial applications.

Edvin Tobias Bokvist Wrammerforsمشاهده پروفایل

پژوهشگر

• Medical Engineering
• Osteoarthritis
• Neutron Tomography
• +۷ مورد دیگر

Edvin Tobias Bokvist Wrammerfors is a doctoral student at the Division for Biomedical Engineering , under the Faculty of Engineering at Lund University . His work focuses on cartilage characterization for osteoarthritis research , utilizing advanced imaging technologies such as neutron tomography and phase-contrast x-ray tomography . Research interests include: Osteoarthritis diagnostics through novel imaging techniques Biomechanics of knee joint tissues Multimodal imaging methods for microstructural analysis Articular cartilage and connective tissue mechanics Recent research output (2024) demonstrates trends in synchrotron imaging , in situ mechanical testing , and microstructural characterization . Collaborations include international partners and Lund University's Engineering Health profile area. Active projects include the PhD Project - Characterization of knee joint tissues via novel neutron and synchrotron imaging techniques , supervised by Professor Hanna Isaksson. Current affiliations involve: Lund University - Faculty of Engineering - Biomedical Engineering Engineering Health profile area Research network spanning medical engineering and connective tissue disciplines

Ben Jeurissenمشاهده پروفایل

استاد پژوهش

• Medical Image Computing
• Quantitative Magnetic Resonance Imaging
• Diffusion MRI
• +۴ مورد دیگر

Prof. Dr. Ben Jeurissen is an Associate Research Professor at the Department of Physics, University of Antwerp , Belgium, specializing in Medical Image Computing , Quantitative MRI , and Diffusion MRI . He received an ERC Consolidator Grant (2023) and FWO Senior Postdoctoral Fellowship (2018–2021) , with a focus on data-driven approaches to study brain microstructure. Education : MSc in Computer Science (2004), Biomedical Imaging (2006), PhD in Science (2012) from University of Antwerp. Research : His work bridges Neuroscience , Medical Imaging , and Computational Methods , particularly in Diffusion MRI and Quantitative MRI for applications in Alzheimer’s disease , spaceflight effects on the brain, and knee imaging . Awards : ERC Consolidator Grant (2023) Australian Museum Eureka Prize Finalist (2024) Multiple Magna/Summa Cum Laude Merit Awards at ISMRM conferences Prize Robert Oppenheimer (2015) Publications span NeuroImage , Human Brain Mapping , Journal of Alzheimer's Disease , and Investigative Radiology , with key contributions to super-resolution MRI , fiber tracking , and brain microstructure analysis . He serves as a contributor to MRtrix and advisor for PhD theses in Computational Anatomy and Medical Imaging .

Edward Sanderمشاهده پروفایل

استاد

• Biomedical Engineering
• Multiscale Mechanics
• Tissue Engineering
• +۷ مورد دیگر

Edward Sander is a Professor in the Department of Biomedical Engineering at the University of Iowa's College of Engineering, where he has been a faculty member since 2011. He also holds researcher positions at the Iowa Institute for Biomedical Imaging and the Iowa Technology Institute, contributing to interdisciplinary research in biomedical engineering and imaging sciences. Education: PhD in Biomedical Engineering, Tulane University, 2006 MS in Biomedical Engineering, Tulane University, 2004 BSE in Chemical Engineering, The University of Texas at Austin, 2000 His research focuses on multiscale mechanics and modeling of biological tissues, with particular emphasis on wound healing, skin tissue engineering, microvessel formation, and the biomechanics of connective, vascular, and ocular tissues. He employs advanced microscopy and image-based computational modeling techniques to study tissue damage and mechanical behavior across scales. His work integrates biomaterials, tissue engineering, and mechanobiology to develop engineered tissue systems and understand native tissue function. Dr. Sander is a member of the Biomedical Engineering Society and leads the Sander 3MT Lab, which focuses on mechanistic, microstructural, and multiphysics modeling of biological materials. While specific publications are not listed in the provided text, his research output is tracked through Google Scholar, indicating an active publication record in his fields of expertise. Scientific Awards and Honors: Robert and Virginia Wheeler Faculty Fellow in Engineering Dr. Sander advises graduate students and likely participates in externally funded research projects, though specific grants and advisees are not detailed. His affiliations with major research institutes at the University of Iowa underscore his role in advancing translational biomedical research and engineering innovation. Research Affiliations: Iowa Institute for Biomedical Imaging Iowa Technology Institute

Niels Aageمشاهده پروفایل

دانشیار

• Topology Optimization
• Acoustics and Vibroacoustics
• Biomechanics
• +۵ مورد دیگر

Niels Aage is an Associate Professor in the Department of Civil and Mechanical Engineering at the Technical University of Denmark (DTU). His research focuses on topology optimization, biomechanics, and multiphysics modeling, with applications in acoustic devices, biomedical implants, and microelectromechanical systems (MEMS). He holds roles such as Vice President of the International Society for Structural and Multidisciplinary Optimization (2023–2027). Education and Professional Background: Conducted a 5-month research visit at the University of Colorado, Boulder (USA) in 2010. Specializes in giga-scale numerical modeling, finite element methods, and topology optimization algorithms. Research Interests: Develops novel methods for topology optimization of fluidic, thermal, and acoustic systems. Explores applications in patient-specific spinal implants, metamaterials with vibroacoustic bandgaps, and nonlinear dynamic substructuring. His work integrates machine learning and reduced-order modeling for efficient simulation. Publications: Over 100 peer-reviewed articles, including recent contributions on connectivity promotion in topology optimization (2025), vibroacoustic metamaterial design (2025), and anatomically conforming spinal fusion cages (2024). Research emphasizes high-resolution modeling and bridging computational design with additive manufacturing. Scientific Awards: ISSMO Haftka Young Investigator Award (2021), Equinor Prize 2020, and Hyperion Innovation Excellence Award (2017). Recognized for contributions to structural optimization and computational mechanics. Advising and Grants: Supervises multiple PhD projects, including work on vibroacoustic shape optimization, quantum-opto-mechanical systems, and smart hearing aid modeling. Engages in collaborative projects funded by industry and academia. Labs/Teams: Collaborates with DTU’s Solid Mechanics group and industry partners on projects involving topology optimization, multiphysics simulation, and biomedical engineering. Active in international conferences and serves on editorial boards.