جست‌وجوی استاد و پژوهشگر

Anthony Rollettمشاهده پروفایل

استاد

• Additive Manufacturing
• Advanced Materials Processing and Manufacturing
• Digital Twins
• +۶ مورد دیگر

Anthony Rollett is a Professor in the Department of Materials Science and Engineering at Carnegie Mellon University , where he has been a faculty member since 1995. He serves as the Principal Investigator and Co-Director of the NASA-supported Institute for Model-Based Qualification & Certification of Additive Manufacturing (IMQCAM) and co-director of the Next Manufacturing Center . Prior to CMU, he held leadership roles at Los Alamos National Laboratory (1991-1995). Education: Ph.D., Materials Engineering, Drexel University (1987) MA, Metallurgy and Materials Science, Cambridge University (1977) Research Interests: Rollett’s work focuses on microstructural evolution and microstructure-property relationships in 3D using experiments and simulations. His expertise spans additive manufacturing , metal 3D printing , materials for energy systems , grain growth , recrystallization , and stereology , with techniques like high-energy diffraction microscopy (HEDM) and dynamic x-ray radiography (DXR) . Scientific Contributions: He has over 320 peer-reviewed publications and an h-index >80 . His recent articles highlight machine learning for laser processing , fatigue analysis of additively manufactured alloys, and design optimization for heat exchangers in supercritical CO2 and solar thermal applications . Scientific Awards: Fellow of ASM International (1996) Fellow of the Institute of Physics (UK) (2004) Fellow of The Minerals, Metals & Materials Society (TMS) (2011) Cyril Stanley Smith Award (TMS, 2014) Member of Honor, French Metallurgical Society (2015) US Steel Professor (2017) Francqui International Professor (2020-2021) International FAME Award (2023) Leadership & Impact: Rollett co-led the development of a NASA Space Technology Research Institute for additive manufacturing and established a new master’s program in additive manufacturing (2018). His research group is funded by industry , federal agencies , and Pennsylvania state grants . He also serves on the Basic Energy Science Advisory Committee and Defense Programs Advisory Committee for the Department of Energy.

• Additive Manufacturing
• Aerospace Engineering
• Thermofluids
• +۱ مورد دیگر

Associate Professor Ng Bing Feng leads research in Additive Manufacturing, Aerospace Engineering, and Thermofluids at Nanyang Technological University's School of Mechanical & Aerospace Engineering. As Cluster Director for Smart & Sustainable Building Technologies at NTU's Energy Research Institute, he oversees projects spanning energy-efficient cooling technologies, advanced filtration systems, and bio-inspired materials. His interdisciplinary work integrates advanced manufacturing with environmental engineering, focusing on sustainable solutions for air quality management and thermal regulation. Current research explores radiative cooling technologies, acoustic agglomeration for emissions control, and crashworthy structures via biomimetic design. Professor Ng's publications demonstrate consistent innovation in multi-scale manufacturing and fluid dynamics, with growing emphasis on sustainable urban technologies. Methodologies combine experimental fluid dynamics with computational modeling and AI-driven design. Leadership Roles: Cluster Director, Energy Research Institute @ NTU Principal Investigator for multiple industry collaborations in sustainable materials Research Output: 42+ publications in high-impact journals Multiple patents in filtration technologies and cooling systems

Jack Beuthمشاهده پروفایل

استاد

• Additive Manufacturing
• Manufacturing Processes
• Solid Mechanics
• +۶ مورد دیگر

Jack Beuth is a Professor of Mechanical Engineering at Carnegie Mellon University (CMU), affiliated with the College of Engineering. He has been on the faculty since 1992 and leads the NextManufacturing Center, focusing on additive manufacturing (AM) research. His work emphasizes process mapping for AM, material science, and machine learning integration in manufacturing processes. Key affiliations include the Engineering Research Accelerator and the Manufacturing Futures Institute. Education: Ph.D. in Engineering Sciences, Harvard University (1992) M.S. in Engineering Sciences, Harvard University (1989) M.S. in Engineering Science and Mechanics, Virginia Tech (1987) B.S. in Engineering Science and Mechanics, Virginia Tech (1984) Research Interests: Additive Manufacturing (process modeling, material characterization, and defect analysis) Melt pool dynamics and thermal modeling Machine learning for process optimization and quality control Advanced materials for AM (e.g., Ti-6Al-4V, Inconel 718) His research has led to innovations like 'process map' approaches for AM, enabling better control over variables such as melt pool geometry and microstructure. Awards and Recognition: Ralph R. Teetor Educational Award (1998) George Tallman and Florence Barrett Ladd Development Professorship (2000) ASME Curriculum Innovation Award (2005) Benjamin Richard Teare Teaching Award (2009) Grants and Collaborations: $3.5M cooperative agreement with the U.S. Army Combat Capabilities Development Command’s Army Research Laboratory (ARL) for AI-driven AM process optimization. Collaborations with Westinghouse Electric Company on 3D-printed nuclear components, such as spacer grids for pressurized water reactors. Labs and Teams: NextManufacturing Center: A research hub for AM innovation, emphasizing industrial partnerships and applied research. Beuth’s Additive Lab: Specializes in melt pool analysis, process mapping, and material behavior under AM conditions.

• Bayesian methodology
• Variable selection and model averaging
• Nonparametric regression models
• +۳ مورد دیگر

Scientia Professor Robert Kohn is a distinguished academic at the University of New South Wales, holding a position in the School of Economics within the UNSW Business School. With a career spanning several decades, Professor Kohn has established himself as a leading expert in statistical methodology and econometric modeling. His research has significantly contributed to Bayesian statistics and computational methods for complex data analysis. Professor Kohn's research focuses on advanced statistical methodologies including Bayesian methodology, variable selection and model averaging, nonparametric regression models, time series modeling, multivariate Gaussian and non-Gaussian regression, and Markov chain Monte Carlo simulation algorithms. His work bridges theoretical statistics with practical applications across economics, finance, and cognitive science. His research demonstrates a consistent trajectory toward developing more efficient computational methods for complex statistical models, with recent work emphasizing variational Bayesian methods, particle filtering techniques, and applications to time series analysis. Analysis of his recent publications (2022-2025) reveals a strong focus on advancing computational statistical methods, particularly in Bayesian inference for complex models. His work shows increasing integration of machine learning techniques with traditional statistical methods, especially in handling high-dimensional data and complex time series structures. Professor Kohn has made significant contributions to variational inference methods, particle-based computational techniques, and applications to financial time series and cognitive modeling. Professor Kohn has maintained an exceptionally productive research career with continuous publication output since the 1970s, demonstrating remarkable longevity and adaptability in his research focus as statistical methodologies have evolved. His work shows strong international collaboration, particularly with researchers in Australia, the United States, and Europe, reflecting his standing in the global statistical community.

Matthias Barzمشاهده پروفایل

استاد

• Polymer Science
• Biotherapeutic Delivery
• Nanoparticle Synthesis
• +۷ مورد دیگر

Matthias Barz is a Professor of Biotherapeutic Delivery at the Leiden Academic Centre for Drug Research (LACDR) , Faculty of Science , Leiden University . He leads the Barz Lab , focusing on polymer science and biomedical applications of functional nanoparticles. Professor of Biotherapeutic Delivery (Leiden University) Head of the Division of BioTherapeutics Researcher in reactive polymer systems and nanocarrier design His research bridges polymer chemistry with biomedical applications, emphasizing polypept(o)ide-based nanocarriers for targeted drug delivery in cancer, inflammation, and neurodegenerative diseases. Key areas include: Stimuli-responsive polymer architectures Secondary structure-driven self-assembly Core-crosslinked micelles for controlled cargo release Redox-sensitive disulfide bonds for intracellular delivery Protein-repellent nanoparticle shells Riboflavin-functionalized nanocarriers for tumor targeting The lab's publications highlight advancements in polysarcosine-containing copolymers , orthogonal functional group utilization , and modular nanoparticle platforms with precise control over morphology and function. Current projects explore the clinical translation of these systems for immunotherapy and diagnostics. Scientific recognition includes: Dozentenpreis des Fonds der Chemischen Industrie (2018) PMSE Young Investigator Award (2018) Nachwuchswissenschaftlerstipendium der GDCh (2017) His team trains graduate students in polymer synthesis, nanoparticle characterization, and biomedical application testing. Collaborations span institutions like the University of Tokyo and Johannes Gutenberg University Mainz , with ongoing projects under the SFB 1066 initiative for malignant melanoma immunotherapy.

Jason Schweinsbergمشاهده پروفایل

استاد

• Probability Theory
• Stochastic Processes
• Mathematical Biology
• +۵ مورد دیگر

Jason Schweinsberg is a Professor in the Department of Mathematics at the University of California, San Diego (UCSD), where he has been a faculty member since Fall 2004. His academic journey began with a Ph.D. in Statistics from the University of California, Berkeley in 2001, followed by a three-year NSF Postdoctoral Fellowship at Cornell University. His research focuses on probability theory with applications to evolutionary biology and population genetics. Schweinsberg's work centers on stochastic processes involving coalescence, branching Brownian motion, and their connections to biological phenomena. He has made significant contributions to understanding population models undergoing selection, cancer evolution, and spatial mutation processes. Recent publications reveal a strong emphasis on coalescent theory (particularly Λ-coalescents and nested coalescents), branching processes with absorption, and spatial evolutionary models. His work often bridges rigorous mathematical analysis with biological applications, especially in population genetics and cancer modeling. The 15 most recent articles demonstrate consistent focus on asymptotic analysis of stochastic processes, genealogical structures, and mutation dynamics in evolving populations. Scientific Awards: Fellow of the Institute of Mathematical Statistics NSF Postdoctoral Research Fellowship While specific student names aren't listed in the source material, Schweinsberg has delivered numerous lecture series at international institutions including the Indian Institute of Science (Bangalore), Centre de Recherches Mathématiques (Montreal), and the Isaac Newton Institute (Cambridge), indicating active mentorship and academic leadership. His collaborations span multiple institutions, with frequent co-authorship with researchers like Julien Berestycki, Nathanaël Berestycki, and Rick Durrett. Though no formal lab structure is mentioned, Schweinsberg participates in interdisciplinary research communities through workshops at institutions like BIRS (Banff International Research Station), where he presented on mutation patterns in spatially structured populations in May 2025. His work connects probability theory with biological applications through sustained collaborations across mathematics, statistics, and computational biology fields.

• Microbiology
• Immunology
• Medicinal Chemistry
• +۴ مورد دیگر

Yan Liu is a Senior Lecturer in Glycosciences at Imperial College's Department of Metabolism, Digestion and Reproduction (Faculty of Medicine). She leads the Wellcome Trust-funded Carbohydrate Microarray Facility and co-leads the GlycoTWINNG Network. Her research focuses on glycan-mediated interactions in host-microbiota interfaces, with applications in infectious diseases and reproductive health. She holds a B.Sc. from Peking University and a Ph.D. from the University of Bristol, followed by postdoctoral work at Imperial College under Professor Ten Feizi FRS. Her academic journey includes roles as a Microarray Project Leader and co-investigator in the March of Dimes European Preterm Birth Research Centre. She is PI of a £1.34M Wellcome Trust grant maintaining Imperial's Carbohydrate Microarray Facility, advancing glycan array technologies. Research interests span microbiology, immunology, and biomolecular chemistry, with a focus on glycobiology. Key contributions include defining glycan interactions in pathogen-host systems (e.g., Candida albicans, adenoviruses), developing glycan probes, and analyzing vaginal microbiota impacts on preterm birth. Grants and collaborations include EPSRC Translational funding and the UK 'FluTrialMAP' consortium. Labs affiliations include the Glycosciences Laboratory and Imperial's Institute of Infection.

Martin Achmusمشاهده پروفایل

استاد

• Geotechnical Engineering
• Offshore Engineering
• Soil Mechanics
• +۳ مورد دیگر

Prof. Dr.-Ing. Martin Achmus is a Professor at Leibniz University Hannover, affiliated with the Faculty of Civil Engineering and Geodetic Science and the Institute for Geotechnical Engineering. He holds multiple leadership roles, including Designated Dean of Civil Engineering and Executive Director of the Institute of Geotechnical Engineering. His research focuses on geotechnical engineering challenges in offshore wind energy, cyclic soil-pile interactions, and foundation design for renewable energy infrastructure. Positions: Designated Dean, Executive Director (Institute of Geotechnical Engineering), Board Member (Testzentrum Tragstrukturen), Exchange Coordinator (Civil Engineering/Computer-Assisted Engineering). Key Projects: Collaborative Research Center (SFB) 'Offshore-Megastructures', DFWind, ProBucket, Ho-Pile, and SEALENCE, focusing on offshore foundations, cyclic loading, and soil-structure interactions. Research Interests: Load-bearing behavior of offshore foundations, soil-pipeline interaction, cyclic loading effects on piles, and geotechnical design methodologies. His work bridges experimental testing (e.g., model tests, particle image velocimetry) and numerical simulations to address challenges in renewable energy infrastructure and geotechnical systems. Publications: Over 150 peer-reviewed articles, emphasizing cyclic soil responses, monopile foundations, suction bucket behavior, and district heating pipeline interactions. Recent work explores novel p-y curve models, capacity degradation under cyclic loading, and scaling approaches for sand behavior. Grants & Collaborations: Funded by DFG, BMWi, and EU initiatives. Collaborates with industry partners on offshore wind turbine foundations and geotechnical innovations. Labs/Teams: Leads research teams within the Institute of Geotechnical Engineering, focusing on experimental and computational geotechnics, with active participation in national and international research networks.

Olga Menaمشاهده پروفایل

استاد پژوهشی

• Cosmology
• Astroparticle Physics
• Neutrino Physics
• +۲ مورد دیگر

Olga Mena is a Research Professor at the Spanish National Research Council (CSIC), affiliated with the Institute of Particle Physics (IFIC) in Valencia, Spain. She leads research in cosmology and astroparticle physics, focusing on neutrinos' role in shaping the universe. Mena holds prestigious awards, including the Excellence PhD Prize, and has accumulated 4 Sexenios and 5 Quinquenios for research excellence. Education : PhD in Theoretical Physics (2002), Universidad Autónoma de Madrid Research Interests : Her work spans cosmology, astroparticle physics, and neutrino physics. She investigates neutrino mass hierarchy, CP violation, and large-scale structure formation. Mena collaborates on major experiments like SKA, DUNE, and BOSS, contributing to dark matter and cosmic microwave background studies. Awards & Honors : Excellence PhD Prize 4 Sexenios de Investigación 5 Quinquenios de Investigación Advising & Grants : Supervised 3 PhD and 2 Master’s theses (current) and 12+ past students Co-Principal Investigator (co-IP) of projects: GRAMOLA (ASFAE/2022/020), SOM (PID2020-113644GB-I00), and others PI of CSIC’s participation in InvisiblesPlus Labs & Collaborations : Member of SKA (world’s largest radio telescope), DUNE (neutrino experiments), and BOSS (SDSS III galaxy survey). Leads IFIC’s research team in InvisiblesPlus.

Michael Scottمشاهده پروفایل

استاد

• Structural Engineering
• Nonlinear Structural Analysis
• Finite Element Analysis
• +۶ مورد دیگر

Michael Scott is a Professor in the Department of Civil and Construction Engineering at Oregon State University, part of the College of Engineering. He holds a Ph.D. in Structural Engineering from the University of California, Berkeley (2004), an M.S. from the same institution (1999), and a B.S. in Civil Engineering from North Carolina State University (1998). His research focuses on nonlinear structural analysis, dynamics, numerical methods, and software design, particularly in the context of bridges and fluid-structure interactions. He has developed widely used tools like OpenSees and contributed to multi-hazard resilience frameworks for infrastructure. Key research areas include tsunami impacts on coastal bridges, GPU-accelerated analysis, and machine learning applications for structural simulation. His work emphasizes sensitivity analysis and software reliability, with notable contributions to OpenSees and PFEM methodologies. He has been recognized with the 2019 Celebrate Excellence Awards for Online Teaching. His research also addresses bridge loading from truck platooning, seismic sensitivity, and ponding effects on structural steel roofs. Educations: Ph.D., Structural Engineering, UC Berkeley (2004) M.S., Structural Engineering, UC Berkeley (1999) B.S., Civil Engineering, NC State University (1998) Awards: 2019 Celebrate Excellence Awards, Online Teaching Award Key Contributions: Development of OpenSees software framework Pioneering work in PFEM for fluid-structure interaction Multi-hazard engineering for tsunami resilience

Jonathan Doyeمشاهده پروفایل

استاد

• DNA Biophysics
• DNA Nanotechnology
• Liquid Crystals
• +۶ مورد دیگر

Jonathan Doye is a Professor of Theoretical Chemistry at the University of Oxford, affiliated with Queens College. He holds positions in the Department of Chemistry and collaborates with the Brandeis Bioinspired Soft Materials MRSEC. His research focuses on theoretical and computational studies of soft matter and biomolecular systems, including DNA biophysics, DNA nanotechnology, liquid crystals, and quasicrystals. He co-developed the oxDNA coarse-grained model for DNA simulations, widely used in nanotechnology research. Education: Bachelor’s and PhD in Theoretical Chemistry from the University of Cambridge Postdoctoral research at FOM Institute in Amsterdam (1996–1998) Research Interests: Coarse-grained modeling of DNA and RNA Patchy-particle self-assembly (including quasicrystals) Prokaryotic S-layer structural analysis Liquid crystal phase behavior of DNA origami rods Key Achievements: Discovery of one-component icosahedral quasicrystals via patchy particles Development of oxDNA model for DNA origami simulations Structural elucidation of S-layers across prokaryotes Awards: Royal Society of Chemistry Harrison Memorial Prize (2000) Labs/Teams: Jonathan Doye's Research Group focuses on computational studies of soft matter systems, with experimental collaborations in DNA nanotechnology and materials science.

• Numerical Modeling
• Geotechnical Engineering
• Renewable Energy Systems
• +۳ مورد دیگر

Dr. Liang Cui is an Associate Professor at the University of Surrey , affiliated with the School of Sustainability, Civil and Environmental Engineering and Institute for Sustainability . With a PhD from University College Dublin (2006) and BE (1st honor) from Tsinghua University (2002) , his career spans geotechnical research and education since joining Surrey in 2009. Key roles: Undergraduate Programme Leader (2020-2022, 2023-on), MSc Programme Leader for Advanced Geotechnical/Civil/Structural Engineering (2022-2023) Professional memberships: Chartered Engineer (CEng), Member of Institution of Civil Engineers (MICE), Fellow of Higher Education Academy (FHEA) His primary research focuses on numerical modeling (DEM/FEM) for geotechnical applications including offshore wind foundations , geothermal energy systems , methane hydrate exploitation , and extra-terrestrial soil mechanics . Secondary interests involve material characterization of polymeric foams , porous media , and biological tissues . Recent 15 publications (2023-2025) demonstrate expertise in soil-structure interaction for renewable energy infrastructure, thermal feedback in groundwater heat pumps, and hypothesis-driven DEM simulations for lunar/martian environments. Collaborative projects span institutions including Tsinghua University , University of Bristol , and Indian Institute of Technology Bhubaneswar . Scientific Awards: Sustainability Fellow (University of Surrey, 2023) Chartered Engineer (CEng) and MICE FHEA for educational contributions Dr. Cui supervises 7 postgraduate researchers and contributes to teaching modules in soil mechanics and energy geotechnics. His work addresses challenges in hybrid marine energy systems , needleless drug delivery , and seismic resilience of critical infrastructure.

John Dolbowمشاهده پروفایل

استاد

• Computational Mechanics
• Fracture Mechanics
• Numerical Methods
• +۵ مورد دیگر

John Dolbow is a Professor in the Thomas Lord Department of Mechanical Engineering and Materials Science at Duke University, with secondary appointments in Civil and Environmental Engineering and Mathematics. He is a Bass Fellow and holds leadership roles as Associate Vice President for Research & Innovation since 2024. Education: B.S.M.E. (University of New Hampshire, 1995), M.S. (Northwestern, 1998), Ph.D. (Northwestern, 1999) Research Focus: Computational fracture mechanics, phase-field modeling, hydrogels, and multiphysics problems in geomechanics and biomedical engineering His recent work advances phase-field methods for fracture nucleation, hydraulic fracturing in geothermal systems, and laser lithotripsy simulations. Dolbow leads Duke's Computational Mechanics Laboratory, integrating civil, mechanical, and materials science approaches. Key contributions include: Erratum corrections for computational mechanics frameworks Nitsche-stabilized methods for interface constraints Phase-field models for surfactant-driven particle raft fracture Multi-resolution approaches for hydraulic fracture simulation Embedded FEM techniques for moving boundary problems Scientific Recognition: R. H. Gallagher Young Investigator Award (2005) Robert J. Melosh Medal for Finite Element Analysis (1999) DOE Computational Science Graduate Fellowship (1997) DOE CSGF Steering Committee Chair

Athanasios Koliosمشاهده پروفایل

استاد

• Wind Turbine Engineering
• Offshore Wind Turbines Engineering
• Offshore Wind Farms Engineering
• +۳ مورد دیگر

Athanasios Kolios serves as Professor and Head of the Structural Integrity and Loads Assessment section within the Department of Wind and Energy Systems at the Technical University of Denmark (DTU). His work focuses on advancing wind energy technology through structural analysis, materials science, and system optimization for both onshore and offshore applications. His primary research domains include wind turbine structural integrity, offshore wind farm layout optimization, and structural health monitoring systems. He investigates critical challenges in operation and maintenance strategies, techno-economic metrics for wind projects, and materials behavior under dynamic loading conditions. His fingerprint analysis reveals dominant expertise in Wind Turbine Engineering (100%), Offshore Wind Turbines Engineering (45%), and Offshore Wind Farms Engineering (36%). Recent publications demonstrate strong emphasis on data-driven approaches for wind energy systems, including structural optimization algorithms, virtual sensing techniques, and techno-economic assessments of offshore projects. His work consistently bridges theoretical engineering principles with practical industry applications, particularly in Brazilian and European offshore wind contexts. Scientific Awards: No scientific awards were documented in the provided information Professor Kolios actively supervises five PhD candidates across major research initiatives while mentoring Master's students in structural wind energy applications. His research portfolio includes six significant projects addressing critical industry needs: PhD Supervision: Chopard (anomaly interpretation), Piovesan (risk-based technology qualification), Yildirim (floating turbine uncertainty), Rodrigues Faria (autonomous operation), Al-Hagri (offshore structure maintenance) Master's Supervision: Rushil S. Mahajan (monopile buckling analysis) Current Projects: Decision support systems, life cycle cost modeling, floating wind turbine modeling, autonomous operation frameworks, sustainable offshore structure design As section head at DTU Wind and Energy Systems, he leads an internationally collaborative research group focused on structural integrity assessment, load prediction methodologies, and materials innovation for next-generation wind turbines. The team maintains strong industry partnerships and contributes to global wind energy standards development through participation in initiatives like ISSC.

• Engineering Materials
• Engineering Manufacture
• Engineering Mechanical
• +۳ مورد دیگر

Professor Hailiang Yu is an Honorary Fellow at the University of Wollongong's School of Mechanical, Materials, Mechatronic and Biomedical Engineering. His research focuses on engineering materials, manufacturing processes, and mechanical engineering, with over 100 journal/conference publications and 30 science-focused newspaper commentaries. He serves as co-Editor-in-Chief of Modeling and Numerical Simulation of Material Science , and holds editorial roles in Scientific Reports and International Research Journal of Engineering Science, Technology and Innovation . Yu has secured significant funding through grants such as the Australian Research Council's 'Large-volume gradient materials' project (2017–2020) and 'A Physical-based abrasive wear model' (2013–2016). His work emphasizes cryorolling, microstructure optimization, and advanced material fabrication techniques. He currently supervises Master's and PhD students in materials engineering and manufacturing innovation. Key research themes include cryogenically processed alloys, bimetallic clad sheets, and high-entropy composites. His publications in journals like Metallurgical and Materials Transactions A and Journal of Materials Processing Technology reflect expertise in structural optimization, tribology, and corrosion resistance. Yu aims to become an international leader in materials manufacturing and mechanical engineering.