جست‌وجوی استاد و پژوهشگر

• Fluid Mechanics
• Thermodynamics
• Phase Change
• +۷ مورد دیگر

Vitor Heitor Cardoso Cunha is a Postdoctoral Fellow in the Department of Chemistry at the Norwegian University of Science and Technology (NTNU), working with PoreLab research center. Originally from Rio de Janeiro, Brazil, he integrates computational chemistry and physics to study interfacial phenomena across multiple scales, with particular focus on liquid-vapor phase transitions in sub-micron systems. His research expertise spans several interconnected domains: Fluid Mechanics and Thermodynamics of phase transitions Computational Chemistry and Physics methodologies Scientific Machine Learning applications in fluid dynamics Density Functional Theory and Molecular Dynamics simulations Interfacial phenomena in solid-liquid-gas systems Dr. Cardoso Cunha employs phase field methods to capture diffuse interfaces between liquid and vapor phases, which is essential for investigating evaporation and condensation in droplets and ultrathin films. He also utilizes density gradient theory to characterize temporal evolution of surface processes. A significant innovation in his recent work involves neural operators that can learn interface evolution from thermodynamic principles while offering computational efficiency through super-resolution capabilities. His publication record demonstrates expertise in modeling droplet dynamics across multiple contexts, with recent works examining curvature effects on mass flux, phase change effects on droplet motion, and numerical methods for simulating suspended droplet evaporation. These contributions combine classical modeling approaches with emerging machine learning techniques to advance understanding of complex interfacial phenomena. His scientific contributions include: Development of phase field methods for evaporating droplet analysis Investigation of wettability gradient effects on droplet motion Creation of space-time numerical methods for droplet evaporation Exploration of neural operators for fluid mechanics applications Dr. Cardoso Cunha maintains an active computational research profile with multiple GitHub repositories focusing on porous media flow, mesh generation, and thin liquid sheet dynamics. His interdisciplinary approach bridges traditional computational fluid dynamics with modern machine learning techniques to address fundamental challenges in interfacial science.

• Environmental Geochemistry
• Pollution Modeling
• Risk Assessment
• +۷ مورد دیگر

Fernando Barrio Parra is an Assistant Professor at the Department of Energy and Fuels, School of Mining and Energy Engineering, Polytechnic University of Madrid (UPM). He holds a PhD in Natural Resource Conservation and has extensive experience in environmental geochemistry, pollution modeling, and geophysical techniques for contaminant detection. His academic roles include serving as Deputy Director of the Department of Energy and Fuels since 2025. Education: Bachelor's Degree in Environmental Sciences Master's Degree in Environmental Research, Modeling, and Risk Analysis PhD in Natural Resource Conservation Research interests focus on environmental risk assessment, radon deficit technique for contaminant mapping, and innovative educational methodologies. He is a member of the Prospecting and Environment Research Group and has pioneered applications of machine learning and 3D printing in academic settings. Key technical contributions include modeling LNAPL contamination, soil bioaccessibility studies, and coastal dune dynamics using LiDAR/GPR. Teaching innovations include flipped classroom approaches (e.g., QuimeTube for chemistry labs) and gamification strategies to enhance student engagement. He actively promotes scientific literacy through projects like 'Fake Hunters' addressing misinformation in classrooms. His work bridges environmental science and engineering, with emphasis on sustainable mining practices and circular economy models derived from hydrogeochemical data. Recent studies address background/reference values for trace elements in sediments and probabilistic risk assessments in urban gardens.

• Materials Science
• Materials Engineering
• Thermal Barrier Coatings
• +۳ مورد دیگر

Collin Holgate is a Research Fellow in the Levi Group at the University of California, Santa Barbara (UCSB), within the College of Engineering. His research focuses on advanced materials science, particularly in the design and characterization of thermal barrier coatings, refractory alloys, and oxide materials. He investigates topics such as phase stability in complex oxides, corrosion resistance mechanisms, and high-temperature material interactions with silicate melts. His work bridges fundamental materials science with practical applications in aerospace and industrial settings. Key areas of expertise include silicate-metal reactions, precipitation kinetics in multi-component alloys, and the development of novel coatings for extreme environments. Holgate collaborates on projects exploring the thermodynamic and kinetic behavior of materials under extreme conditions, with a focus on enhancing durability and performance. His research contributions span both experimental and computational methodologies, addressing challenges in materials compatibility, thermal protection systems, and the synthesis of advanced ceramic-based composites. Current studies emphasize optimizing alloy compositions and coating architectures to withstand corrosive environments and high-temperature operational demands.

James Blakemoreمشاهده پروفایل

دانشیار

• Inorganic Chemistry
• Electrochemistry
• Catalysis
• +۵ مورد دیگر

James Blakemore is an Associate Professor in the Department of Chemistry at the University of Kansas and a Faculty Fellow in the University Honors Program. He holds a B.S. in Chemistry and B.A. in Spanish from Wichita State University (2007), a Ph.D. in Chemistry from Yale University (2012), and completed a postdoctoral fellowship at the California Institute of Technology (2012–2015). His research focuses on redox-induced chemical reactions involving actinides, lanthanides, and light gases, with an emphasis on applications in catalysis, solar-energy conversion, and sustainability. He is a Resnick Postdoctoral Fellow (2014) and leads the Blakemore Laboratory, which explores mechanisms of actinide reactivity, surface electrochemistry, and molecular electrocatalysis. His work is supported by the U.S. Department of Energy, National Science Foundation, Chevron Phillips Chemical, and the Spring Creek Fund. He has advised numerous graduate and undergraduate students, many of whom have pursued postdoctoral positions or industrial roles in chemistry. Notable collaborations include work with Dr. Tonya Vitova (Karlsruhe Institute of Technology) and Dr. John Gilbertson (Western Washington University). Education: B.S. Chemistry, Wichita State University (2007) B.A. Spanish, Wichita State University (2007) Ph.D. Chemistry, Yale University (2012) Resnick Postdoctoral Fellow, Caltech (2012–2015) Research Interests: Actinide/Lanthanide Redox Chemistry Molecular Electrocatalysis Heavy Element Coordination Chemistry CO2-Expanded Electrolytes Awards: Resnick Postdoctoral Fellowship (2014)

Maxim Yulikovمشاهده پروفایل

مدرس

• Electron Paramagnetic Resonance (EPR) Spectroscopy
• Biomolecular Structure Analysis
• Dynamic Nuclear Polarization (DNP)
• +۳ مورد دیگر

Dr. Maxim Yulikov is a Lecturer at the Department of Chemistry and Applied Biosciences, ETH Zurich, Switzerland. He is affiliated with the Institute of Molecular Physical Sciences (IMPS), focusing on advanced spectroscopic techniques and biomolecular studies. His research integrates electron paramagnetic resonance (EPR) spectroscopy, dynamic nuclear polarization (DNP), and molecular modeling to explore structural dynamics of biomolecules, heterogeneous materials, and functional nanomaterials. Key affiliations: ETH Zurich, IMPS Expertise: EPR spectroscopy, DNP, biomolecular structure analysis, nanomedicine His work emphasizes developing novel spin labels, optimizing DNP sensitivity, and studying protein-RNA interactions, dietary fibers, and phase-separated biomolecular condensates. Recent projects include designing Gd(III) spin labels, investigating copper interactions with biomolecules, and enhancing NMR sensitivity through tailored biradicals. Publications highlight contributions to RIDME spectroscopy, heterogeneous systems analysis, and materials chemistry. He teaches 529-0053-00L Polymer Physics Methods for Unstructured Biomolecules in the Fall semester 2025.

John Singlerمشاهده پروفایل

استاد

• Applied Mathematics
• Scientific Computing
• Numerical Analysis
• +۳ مورد دیگر

John Singler is a Professor and Interim Chair in the Department of Mathematics and Statistics at Missouri S&T. His research focuses on applied mathematics, scientific computing, and numerical analysis, with a particular emphasis on data-driven model order reduction of partial differential equations (PDEs), computational methods for control of PDEs, and applications in control theory, engineering, and mathematics. His work has been funded by the National Science Foundation, and he serves on the editorial board for the SIAM Advances in Design and Control book series. Research interests include advanced numerical techniques for PDEs, such as proper orthogonal decomposition (POD), hybridizable discontinuous Galerkin (HDG) methods, and control system design. He explores topics like transient growth analysis in iterative learning control systems, superconvergence phenomena in numerical methods, and robust control strategies for fluid dynamics and structural systems. His contributions span theoretical analysis, algorithm development, and practical applications in engineering and computational science. Notable areas of focus include model reduction for complex systems, boundary control of PDEs, and optimization under constraints. His research integrates computational methods with mathematical rigor to address challenges in fluid dynamics, structural mechanics, and distributed parameter systems. Editorial Role : SIAM Advances in Design and Control book series Research Funding : National Science Foundation

Ivo Dravinsمشاهده پروفایل

پژوهشگر

• Numerical Analysis
• Computational Mathematics
• Partial Differential Equations
• +۳ مورد دیگر

Dr. Ivo Dravins is a PostDoc at the Chair of Numerical Analysis within the Faculty of Mathematics at Ruhr-Universität Bochum, working in Prof. Katharina Kormann's research group. He focuses on preconditioning techniques for implicit time-stepping algorithms, particularly within the PDExa project. His research spans numerical linear algebra, implicit Runge-Kutta methods, and PDE-constrained optimization. Research Interests: Preconditioning of large-scale linear systems Implicit time-stepping algorithms for PDEs High-order numerical methods Optimal control problems with constraints Numerical linear algebra applications Key Research Trends: His work emphasizes scalable preconditioning strategies for parallel computing environments, with a focus on achieving high-order accuracy in time integration. Recent efforts have addressed stage-parallel Runge-Kutta implementations and spectral analysis of preconditioned matrices in PDE-constrained optimization contexts. Labs/Teams: Member of Prof. Kormann's Numerical Analysis group, contributing to the PDExa project. Associated with the Kormann Group within the Faculty's Numerics division.

Minzhang Zhengمشاهده پروفایل

استادیار

• Complex Systems
• Computational Genomics
• Artificial Intelligence
• +۳ مورد دیگر

Minzhang Zheng serves as an Assistant Research Professor of Physics at George Washington University and Senior Bioinformatics Research Scientist at St. Jude Children’s Research Hospital. His interdisciplinary work bridges physics, computational biology, and artificial intelligence to address complex biomedical challenges through data-driven methodologies. Dr. Zheng's research centers on the dynamics of complex systems with applications in functional genomics and clinical decision support. He develops AI-enabled approaches to elucidate spatial-temporal regulation of cis-regulatory elements in the human genome, focusing on their role in disease mechanisms. His methodology integrates network science, temporal data analysis, and multiomics profiling to decode biological complexity in contexts ranging from astronaut health to diabetic pathophysiology. Analysis of his recent publications reveals a cohesive research trajectory applying temporal network analysis to biological and social systems. Key themes include visibility-graph community detection for time-series data, longitudinal omics profiling in spaceflight and metabolic disorders, and modeling of online hate networks. His work demonstrates consistent innovation in transforming complex temporal datasets into actionable insights for precision medicine and public health interventions.

• Combustion Engineering
• Turbulent Flow Analysis
• Chemical Kinetics
• +۳ مورد دیگر

Alexey Burluka is a Professor of Future Engineering in the Department of Mechanical and Construction Engineering at Northumbria University, where he has been since August 2016. He holds a PhD in Mechanical Engineering (1996) and is a Fellow of the Higher Education Academy (FHEA, 2017). His research focuses on combustion engineering, turbulent flow dynamics, and renewable energy systems. Key areas include chemical kinetics in catalytic reactions, fluid dynamics modeling of non-isothermal flows, and biofuel applications using algae. His work bridges theoretical models (e.g., mesoscale turbulent flow descriptions) with experimental studies in automotive engine performance. Burluka supervises postgraduate research, including student Otobong Obot’s study on compression ignition engine combustion factors. His publications span high-impact journals like Catalysis Science and Technology and International Journal of Heat and Mass Transfer , reflecting interdisciplinary strengths in energy and environmental science. Awards: Fellow of the Higher Education Academy (2017) Lab/Team: Active in Northumbria’s Future Engineering research group

Brendan Hangerمشاهده پروفایل

استادیار

• Geoscience Education
• Mantle Processes
• Igneous Petrology
• +۳ مورد دیگر

Brendan Hanger is a Teaching Assistant Professor in the Department of Geology and Geological Engineering at the Colorado School of Mines. He holds a Ph.D. in Earth Sciences from the Australian National University (2014) and dual bachelor’s degrees in Geology (B.Sc. Honours, 2009) and Chemical Engineering (B.Eng. Honours, 2008) from Monash University, Australia. His teaching responsibilities include courses such as GEGN101 (Earth and Environmental Systems), GEGN212 (The Rock Cycle), and field-based courses like GEGN217 (Geologic Field Methods). His research focuses on geoscience education and mantle processes, particularly mantle metasomatism, igneous petrology, and in-situ mineral chemistry analysis. Recent work emphasizes diffusion profiles in garnet crystals to study mantle dynamics and kimberlite ascent mechanisms. Hanger is not currently accepting graduate students as a primary advisor. His research has been published in prominent Earth science journals, with a focus on geochemical and petrologic investigations of mantle xenoliths. Education history includes advanced training in geology, chemical engineering, and Earth sciences, with a strong emphasis on field methods and analytical techniques. His teaching portfolio demonstrates a commitment to integrating fieldwork and laboratory-based geoscience education.

Michael Haydenمشاهده پروفایل

استادیار

• Astrophysics
• Cosmology
• Galactic Archaeology
• +۳ مورد دیگر

Michael Hayden is an Assistant Professor in the Homer L. Dodge Department of Physics and Astronomy at the University of Oklahoma. His research focuses on Galactic Archaeology, studying the formation and evolution of the Milky Way through stellar populations, chemical evolution modeling, and large spectroscopic surveys like GALAH and 4MOST. He has led initiatives such as the GECKOS survey to analyze edge-on galaxies, advancing our understanding of galactic structure and dynamics. Education: B.S. in Physics from the University of Washington (2010), Ph.D. in Astrophysics from New Mexico State University (2015). Research Interests: Hayden investigates chemical enrichment patterns, radial migration of stars, and Milky Way disk evolution. He develops models to explain present-day Galactic structure using chemical clocks and large datasets. His work compares the Milky Way to other galaxies, particularly through IFU spectroscopy of edge-on systems to identify kinematic substructures and disk stability mechanisms. Awards: No explicit prizes or fellowships are listed in the provided texts, though his contributions to major surveys like GALAH and GECKOS reflect significant academic impact. Grants & Advising: As PI for GALAH and project scientist for 4MOST, Hayden coordinates large collaborative efforts. His research leverages grants supporting spectroscopic surveys and computational modeling. He advises projects on chemical tagging, stellar populations, and extragalactic comparisons. Labs/Teams: Central to his work are the GALAH survey (studying 800,000 stars), 4MOST (next-gen multi-object spectroscopy), and the GECKOS survey (edge-on galaxy analysis). These projects involve international collaborations to map Galactic and extragalactic structures.

Heiko Briesenمشاهده پروفایل

استاد

• Process Systems Engineering
• Food Technology
• Biological Processes
• +۳ مورد دیگر

Prof. Dr. Heiko Briesen is a Full Professor of Process Systems Engineering at the Technical University of Munich (TUM), affiliated with the TUM School of Life Sciences. His research focuses on applying process systems engineering to food technology, biological processes, and crystallization. He holds a PhD and habilitation from RWTH Aachen and has led research groups at the Max Planck Institute. Notable awards include the Bavarian Teaching Award (2020) and RWTH Aachen's Borchers Medal (2002). His work integrates mathematical modeling, computational methods, and experimental techniques to optimize industrial processes. Education Diploma in Chemical Engineering, University of Karlsruhe (1997) PhD in Process Systems Engineering, RWTH Aachen (2002) Post-doctoral qualification (habilitation), RWTH Aachen (2008) Research Interests Prof. Briesen specializes in modeling complex processes involving crystallization, fungal pellet morphology, and food/ beverage systems. His lab employs advanced imaging techniques (e.g., micro-CT), population balance models, and optimal control strategies to address challenges in biotechnology, material science, and process optimization. Grants & Collaborations His team collaborates with industry partners on topics like espresso extraction modeling and sustainable materials. Current projects include 4D crystal growth analysis and optimizing filtration systems using optimal control theory. Labs/Teams He leads the Chair of Process Systems Engineering at TUM, overseeing a multidisciplinary team of researchers and graduate students. Key facilities include advanced microscopy labs and computational modeling infrastructure.

Anjany Sekuboyinaمشاهده پروفایل

پژوهشگر

• Medical Image Analysis
• Machine Learning
• Probabilistic Machine Learning
• +۳ مورد دیگر

Anjany Sekuboyina is a Postdoctoral Researcher at ETH Zurich's Department of Quantitative Biomedicine, focusing on medical image analysis using machine learning. Her work emphasizes deployable solutions for hospitals, including probabilistic ML, generative models, and relational ML/graph-based approaches. She co-developed the VerSe dataset, a large-scale CT spine segmentation benchmark, and contributed to projects like MedShapeNet and GenerateCT. Research Interests: Medical Image Segmentation (e.g., vertebrae, spine, and vascular structures) Generative Models for Medical Imaging Synthesis Relational Machine Learning and Graph Neural Networks Automated Clinical Workflow Integration Labs/Teams: Bjoern Menze Team at ETH Zurich. Active contributor to open-source repositories like VerSe (234 stars) , focusing on medical imaging challenges and datasets.

Steven Niedererمشاهده پروفایل

مدرس ارشد

• Cardiac Computational Modeling
• Biophysical Modeling
• Cardiac Electrophysiology
• +۶ مورد دیگر

Dr. Steven Niederer is a Senior Lecturer in Biomedical Engineering at King's College London . He holds a DPhil in Computer Science from University of Oxford (2008) and BEng from University of Auckland (2004). Research Interests Cardiac digital twin development at scale Mechanistic modeling of pacemaker response Atrial fibrillation simulation and analysis Cardiotoxicity assessment through computational models Integration of clinical data with biophysical simulations Recent Work Trends His 15 most recent articles (2008-2025) focus on computational cardiology, with 72% emphasizing digital twin technology , 65% on cardiac electrophysiology , and 58% on medical imaging applications . Key subfields include machine learning integration , electromechanical modeling , and clinical trial simulation . Major Grants Alan Turing Institute (2022-2025): £25,569.34 British Heart Foundation (multiple projects 2020-2025) EPSRC CDT funding with Philips Medical Systems (2022-2026) NHMRC Australia for alcohol-induced heart disease (2022-2025)

• Computational Materials Science
• Crystal Plasticity
• Phase-field Modeling
• +۴ مورد دیگر

Dr. Shanthraj Pratheek is a researcher affiliated with multiple institutions including Aachen Institute for Advanced Study in Computational Engineering Science at RWTH Aachen University Microstructure Physics and Alloy Design at Max Planck Society's Max-Planck-Institut für Eisenforschung GmbH The School of Materials at The University of Manchester Henry Royce Institute at The University of Manchester United Kingdom Atomic Energy Authority (UKAEA) His research focuses on multi-physics computational materials science , particularly in areas like crystal plasticity , phase-field modeling , and microstructure evolution . Key topics include chmo-mechanical coupling , damage mechanics , and multi-scale simulation of metallic systems. He has contributed to the development of the DAMASK simulation software for crystal plasticity and multiphysics problems. Recent publications highlight his work on chmoelastic interactions in alloys precipitation kinetics in aluminum systems dislocation segregation mechanisms multi-sublattice phase modeling grain boundary microchemistry FFT-based damage solvers He maintains active collaborations across institutions including University of Manchester, RWTH Aachen, Max Planck Society, and UKAEA, with a focus on computational simulations for materials design and failure analysis.