جستجوی استاد راهنمای دانشگاهی

Barbara Solenthalerمشاهده پروفایل

پژوهشگر ارشد

• Physics-based modeling and simulation
• Data-driven simulations
• Deep learning for physics
• +۲ مورد دیگر

Barbara Solenthaler is a Senior Research Scientist at ETH Zurich's Computer Graphics Laboratory, leading the Simulation and Animation Group. She holds a Hans Fischer Fellowship at the Technical University of Munich (TUM-IAS). Her research focuses on physics-based simulations for computer graphics applications, integrating deep learning to enhance efficiency and artist control. She has co-founded Apagom AG, providing real-time fluid engines using machine learning. Education: PhD in Computer Science, University of Zurich Research Interests: Physics-driven simulations for visual effects, games, and biomedical computing Data-driven methods and neural networks for fluid dynamics Real-time computation and artist-controllable workflows Awards: Hans Fischer Fellowship (2019) Best Paper Awards (2017, 2011) Swiss National Science Foundation grants Advising & Grants: She has led research projects funded by SNSF, ETH Zurich, and Innosuisse. Her work bridges academic research and industry applications through collaborations like Apagom AG. Labs/Teams: Leads the Simulation and Animation Group at ETH Zurich and contributes to TUM-IAS's Simulation and Digital Twin focus group.

Katrin Wudyمشاهده پروفایل

استاد

• Additive Manufacturing
• Laser Processing
• Materials Engineering
• +۲ مورد دیگر

Prof. Dr.-Ing. Katrin Wudy is a Professor at the Technical University of Munich's School of Engineering and Design, specializing in Laser-based Additive Manufacturing. Her research encompasses the entire additive manufacturing process chain from material development and new process strategies to automation solutions and quality management. She completed her PhD at Friedrich-Alexander-Universität Erlangen-Nürnberg in powder and beam-based additive manufacturing. Her research interests focus on laser-based processing of plastics and metals, with particular emphasis on thermal analysis, beam shaping techniques, and process optimization. Recent work investigates melt pool behavior, multispectral imaging for temperature measurement, and productivity enhancement in powder bed fusion systems. Analyses of recent publications show strong focus on advanced beam shaping technologies, thermal process monitoring, and microstructure control in metal additive manufacturing, with emerging interests in AI applications and multi-material processing. Wudy has led the Additive Manufacturing working group at the Institute of Polymer Technology and served as Managing Director of the CRC 814 Additive Manufacturing consortium.

• Social Hierarchy
• Social Networks
• Anthropology
• +۳ مورد دیگر

Daniel Redhead is a Researcher at the Max Planck Institute for Evolutionary Anthropology within the Department of Human Behavior, Ecology and Culture. He holds a PhD in Psychology from the University of Essex and advanced degrees in Anthropology from Durham University. His research examines social hierarchy dynamics through interdisciplinary approaches combining anthropology, psychology, and network analysis. Research interests focus on: Evolution of social hierarchies and status acquisition Cross-cultural analysis of cooperation networks Computational modeling of group dynamics Longitudinal studies in diverse populations including indigenous communities Development of methodological tools for social network analysis His publications (2019-2025) demonstrate consistent focus on social networks, inequality, and cultural transmission, with methodological innovation in statistical modeling and field research. Recent works emphasize computational approaches to network analysis and cross-cultural examinations of cooperation. Awards and honors include: ESRC Research Methods Development Grant (Co-I, £200K, 2020) European Human Behavior & Evolution Association Award (2017) Experimental Psychology Society Study Visit Award (2016) Multiple University of Essex research grants and scholarships Teaching experience includes graduate instruction in Social Network Analysis and Research Methods at University of Essex. Professional activities encompass peer review for major journals and memberships in anthropological/psychological associations. Fieldwork spans four continents including ongoing longitudinal research with Mayangna communities in Nicaragua.

Marita Thomasمشاهده پروفایل

استاد

• Material Modeling
• Damage Mechanics
• Fracture Mechanics
• +۵ مورد دیگر

Marita Thomas is a Professor (W2) for Applied Analysis at Freie Universität Berlin since August 2022 and Head of the Weierstrass group 'Bulk-Interface Processes' at the Weierstrass Institute since April 2017. She holds a PhD in Mathematics from Humboldt-Universität zu Berlin (2010) and a Diplom in Mathematics (with application to chemistry) from the University of Stuttgart (2006). Her research focuses on material modeling, damage and fracture mechanics, variational methods, and the coupling of optoelectronics with thermomechanics. She has led numerous projects including those within CRC 1114 'Scaling Cascades in Complex Systems' and the Berlin Mathematics Research Center MATH+. Education: PhD in Mathematics (Humboldt-Universität, 2010); Diplom in Mathematics (University of Stuttgart, 2006) Key Projects: Materials with discontinuities on multiple scales, Interface dynamics bridging stochastic and hydrodynamic descriptions, Dynamics of rock dehydration Her research integrates analytical approaches with numerical simulations, addressing challenges in continuum mechanics, phase-field fracture, and optoelectronic device optimization. She has organized international workshops and minisymposia, including the Thematic Einstein Semester on Energy-based Mathematical Methods.

• Fractional-Order Systems
• Chaotic Systems
• Field-Programmable Gate Array (FPGA) Implementations
• +۵ مورد دیگر

Ahmed Gomaa Radwan is a Professor at Cairo University's Department of Engineering Mathematics and Physics, Egypt. His research spans fractional-order systems , chaotic dynamics , FPGA implementations , and bio-impedance modeling , with numerous publications in IEEE Access, Microelectronics Journal, and Circuits Systems Signal Processing. Key collaborators include Lobna A. Said , Wafaa S. Sayed , and Ahmed Soltan . His work emphasizes chaos-based encryption , fractional calculus , and hardware accelerators for real-world applications. Publications highlight trends in fractional-order chaotic systems , memristor technology , and secure image processing , often involving CNTFET designs and nonlinear resonators .

• Machine Learning
• Deep Learning
• Neural Networks
• +۷ مورد دیگر

Sung-Bae Cho is a prolific researcher in computer science with a publication record spanning over three decades from 1990 to 2025, demonstrating sustained academic productivity and research leadership. Their work primarily focuses on machine learning, neural networks, and their applications across diverse domains including cybersecurity, healthcare, and intelligent systems. Cho's research interests center around advanced machine learning techniques including deep learning architectures, Bayesian networks, and context-aware systems. Their work shows a consistent evolution from traditional neural networks to modern deep learning approaches, with recent publications emphasizing graph neural networks, federated learning, and anomaly detection systems. The research demonstrates strong methodological rigor with applications in practical domains such as traffic prediction, medical diagnosis, and security systems. The publication pattern reveals significant research productivity with multiple high-impact papers annually in reputable venues including IEEE Access, Neurocomputing, and Expert Systems with Applications. Recent work shows particular emphasis on addressing contemporary challenges in machine learning including continual learning, few-shot learning, and privacy-preserving approaches in federated settings. The research demonstrates both theoretical contributions and practical implementations across various application domains. Cho has cultivated an extensive collaborative network with numerous co-authors including Kyung-Joong Kim, Satchidananda Dehuri, Jin-Hyuk Hong, and Seok-Jun Bu, suggesting leadership in research groups and projects. The collaborative pattern indicates supervision of junior researchers and students, though specific advisee relationships aren't explicitly documented in the publication metadata. The researcher maintains active contributions to laboratory and team-based research, with recent publications indicating involvement in projects related to healthcare AI, cybersecurity systems, and intelligent transportation. Current research directions appear focused on addressing limitations in deep learning including catastrophic forgetting, data scarcity, and privacy concerns through novel architectural and training approaches.

Mark Bangertمشاهده پروفایل

پژوهشگر

• Radiation Therapy Physics
• Intensity-Modulated Radiation Therapy
• Beam Angle Optimization
• +۴ مورد دیگر

Mark Bangert is a researcher in the Department of Medical Physics in Radiation Oncology at the German Cancer Research Center (DKFZ) in Heidelberg, Germany. His work focuses on optimizing radiation therapy treatments through advanced computational methods and physics principles, particularly for complex cases involving critical organs at risk. Dr. Bangert completed his PhD at Heidelberg University in 2011 with a dissertation titled 'New concepts for beam angle selection in IMRT treatment planning: From heuristics to combinatorial optimization.' His doctoral work was supervised by Prof. Uwe Oelfke and Prof. Wolfgang Schlegel, established experts in medical physics and radiation oncology. His research spans radiation therapy physics, intensity-modulated radiation therapy (IMRT), beam angle optimization, proton therapy, and treatment planning. Dr. Bangert pioneered methods for selecting optimal beam angles in IMRT, demonstrating that noncoplanar beam configurations could significantly reduce radiation doses to organs at risk while maintaining target coverage. His early work established the importance of integrating fluence optimization into beam angle selection. Analysis of his publication history reveals an evolution from traditional IMRT optimization to sophisticated multi-modality treatment approaches combining photons with particle therapies (protons, carbon ions, and helium). His recent work emphasizes probabilistic modeling to address range uncertainties in particle therapy, analytical dose calculation methods, and the integration of biological optimization into treatment planning. He has made significant contributions to open-source software development for radiation therapy planning education. Dr. Bangert has played a key role in developing matRad, an open-source multi-modality treatment planning toolkit designed for educational purposes. This software provides accessible tools for students and researchers to explore radiation therapy planning concepts without commercial constraints. His work bridges theoretical optimization methods with practical clinical applications, improving treatment precision while minimizing damage to healthy tissues.

Thorsten Wiegandمشاهده پروفایل

پژوهشگر

• Ecological Modelling
• Spatial Ecology
• Forest Dynamics
• +۵ مورد دیگر

Thorsten Wiegand is a researcher at the Helmholtz Centre for Environmental Research (UFZ) in Leipzig, Germany, leading the Department of Ecological Modelling . He holds a PhD in theoretical ecology from the University of Marburg (1992) and has been conducting research at UFZ since its inception. His work focuses on spatial ecology , integrating mathematical models with spatial statistics to understand forest dynamics, species coexistence, and biodiversity patterns. In 2023, he secured an ERC Advanced Grant (€2.5M) to develop spatial theories explaining species-rich forest stability, collaborating with Prof. Andreas Huth and international partners. Research interests include: Spatial patterns in tropical and temperate forests Seed dispersal mechanisms and stochastic environmental effects Individual-based simulation models linking micro-scale interactions to macro-scale ecological patterns Current projects involve analyzing forest inventory data from global networks (e.g., Smithsonian's ForestGEO) and field studies in Sri Lanka/Thailand. Funds will support early-career researchers and international workshops. Wiegand's work bridges ecology, physics, and mathematics to address climate change impacts on biodiversity.

Martin Schrönمشاهده پروفایل

پژوهشگر

• Environmental Science
• Hydrology
• Remote Sensing
• +۳ مورد دیگر

Dr. Martin Schrön is a postdoctoral researcher at the Helmholtz Centre for Environmental Research (UFZ) in Leipzig, Germany, specializing in cosmic-ray neutron sensing (CRNS) for environmental monitoring. His work focuses on advancing CRNS technology to improve soil moisture and snow water equivalent measurements at various spatial and temporal scales. Schrön holds a PhD from the University of Potsdam and has conducted research at the University of Bristol. He is involved in projects such as MOWAX (water budget assessment in Saxony) and COCAP (pandemic coping strategies), and contributes to software development for neutron simulation (URANOS) and environmental modeling (mHM). His education includes a Physics degree from the University of Heidelberg and postdoctoral research at the University of Greifswald and UFZ. He has supervised multiple students and won awards like the Klartext Award for science communication (2018) and the UFZ Research Award (2017). His research bridges geophysics and environmental science, with applications in climate change, hydrology, and remote sensing. Education: Physics (Heidelberg University), PhD (University of Potsdam) Affiliations: Department of Computational Hydrosystems, UFZ Leipzig Key Projects: CRNS network in Saxony, Svalbard cosmic-ray observations, Low-water strategy for Thuringia Research interests include CRNS applications in soil moisture dynamics, neutron transport modeling, and environmental data integration. He has developed software tools and contributed to international collaborations, emphasizing science communication through FameLab and ScienceSlam.

Almudena García-Garcíaمشاهده پروفایل

پژوهشگر

• Remote Sensing
• Climate Science
• Environmental Monitoring
• +۶ مورد دیگر

Almudena García-García is a Researcher in the Department of Remote Sensing at the Helmholtz Centre for Environmental Research - UFZ in Leipzig, Germany. Her work focuses on land-atmosphere interactions, climate extremes, satellite remote sensing, and process-based modeling. She holds a Ph.D. in Environmental Sciences from Memorial University of Newfoundland (2020), a Master's in Earth Sciences from St. Francis Xavier University (2016), and a BSc in Physics from the University of Murcia (2014). She has been recognized with the Moire A. Wadleigh Award (2020) and the Governor General Graduate Medal (2016), and was nominated for the Lindau Nobel Laureate Meeting (2014). Her research integrates remote sensing data with climate models to study energy and water fluxes, soil moisture dynamics, and heat extremes. Key projects include the 4DHydro initiative (2023–2025) for hyper-resolution Earth observations and the iDiv Flexpool project on biodiversity mapping. She leads studies on soil heat extremes, continental heat storage, and transpiration modeling using satellite data and neural networks. Publications highlight contributions to global soil moisture products, continental heat dynamics, and climate extremes. She collaborates on the GCOS Earth Heat Inventory and has co-authored over 30 peer-reviewed articles. Her work bridges environmental informatics and Earth system science, addressing climate change impacts and sustainable monitoring solutions.

Jens Struckmeierمشاهده پروفایل

استاد

• Numerical Analysis
• Computational Fluid Dynamics
• Kinetic Theory
• +۳ مورد دیگر

Prof. Jens Struckmeier is a faculty member at the University of Hamburg, holding the position of Professor of Numerics within the Department of Mathematics, Faculty of Mathematics, Computer Science and Natural Sciences. His research focuses on applied mathematics, particularly numerical methods for partial differential equations, computational fluid dynamics, kinetic theory, and optimal control. He has contributed extensively to areas such as particle methods for the Boltzmann equation, finite-volume particle methods for conservation laws, and mathematical modeling of crystallization processes and thermal flows. His work often bridges theoretical developments with industrial applications, such as fire simulations in vehicle tunnels and polymer crystallization studies. Struckmeier's research interests include numerical analysis, kinetic theory, and the development of efficient algorithms for complex systems. He has authored or co-authored numerous publications, including books on hyperbolic partial differential equations and articles in journals like Journal of Computational Physics and Mathematical Models and Methods in Applied Sciences . His work on radiation models for low Mach number flows and optimal control of crystallization processes demonstrates interdisciplinary applications of mathematical modeling. Notable contributions include the finite-volume particle method for moving domains and kinetic schemes for granular flow equations (Savage-Hutter equations). He collaborates widely, with co-authors across institutions, and his research often addresses real-world challenges in engineering and physics. While no specific awards are listed, his sustained academic output reflects significant contributions to numerical mathematics and applied sciences.

Sascha Julian Oksمشاهده پروفایل

پژوهشگر

• Digital Transformation
• Cyber-Physical Systems
• Industrial Value Creation
• +۷ مورد دیگر

Sascha Julian Oks is a Postdoctoral Researcher at the School of Business, Economics and Society and the Chair of Information Systems I, Innovation and Value Creation at Friedrich-Alexander University Erlangen-Nürnberg (FAU). He is also a Postdoc at HHL Leipzig Graduate School of Management and serves as CEO of the FAU spin-off QuartRevo , which focuses on innovative business models for SMEs using cyber-physical systems. Additionally, he holds the rank of Kapitänleutnant (OF-2) at the German Naval Academy Marineschule Mürwik, where he instructs leadership courses. His academic journey includes a Ph.D. in Business Information Systems (Wirtschaftsinformatik) from FAU (2023), a Master of Science in Business Administration from Stellenbosch University (South Africa, 2012), and prior degrees from Universität Bayreuth (2009–2011). His research interests center on the digital transformation’s impact on industrial value creation, particularly in cyber-physical systems (CPS), Industry 4.0 implementation, and open innovation in medical technology. He has developed web-tools like the PID4CPS demonstrator and co-authored several books and articles on CPS integration, stakeholder-oriented system design, and digital transformation strategies. His work bridges academic research with practical applications, emphasizing systematic digitization strategies and the alignment of organizational processes with technological advancements. He has presented his findings at major conferences such as EURAM, IEEE INDIN, and the International Symposium on Open Collaboration. His contributions include exploring blockchain-based traceability systems for industrial IoT, modular service bundles for maintenance efficiency, and the role of CPS in redefining personnel roles and services in manufacturing. His interdisciplinary approach also extends to military education, focusing on leadership development and translating qualifications between civilian and military contexts.

Alberto Leonardiمشاهده پروفایل

پژوهشگر ارشد

• Nano-materials for energy and sustainability
• Scattering and diffraction methods
• Multiscale simulation
• +۵ مورد دیگر

Dr. Alberto Leonardi is a Beamline Scientist at Diamond Light Source Ltd. (UK) and holds a Habilitand position at Friedrich-Alexander Universität Erlangen-Nürnberg (Germany) . His research focuses on nano-materials for energy and sustainability, combining experimental scattering techniques with multiscale simulations. He specializes in developing high-performance algorithms for simulating diffraction patterns of large atomistic models, as demonstrated by the ROSE-X software. Education: University of Trento (Italy) Indiana University Bloomington (USA) Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany) Key Research Areas: Structure-property relationships in nanomaterials Diffraction-based analysis and simulation High-performance computing (HPC) for materials modeling Leonardi’s work emphasizes linking experimental observations with computational models to study material kinetics, mechanical properties, and chemical sensitivity. He has developed innovative methods for analyzing structural defects and disorder in nano-polycrystalline materials. His ROSE-X software enables rapid simulation of diffraction patterns for systems with millions of atoms, leveraging parallel computing on CPU/GPU clusters. He has taught at academic and high-school levels, emphasizing interdisciplinary approaches. His international collaborations span diverse institutions, including the Rutherford Appleton Laboratory (UK).

Paolo Morettiمشاهده پروفایل

استاد

• Materials Science
• Computational Materials Science
• Fracture Mechanics
• +۳ مورد دیگر

Paolo Moretti is a Professor at the Department of Materials Science and Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), leading the Chair for Materials Simulation. His research focuses on hierarchical materials, network models, and failure mechanisms in materials under mechanical and thermal loads. He employs computational methods and graph theory to study fracture, creep failure, and material behavior under stress. Key research contributions include understanding load redistribution in heterogeneous interfaces, predicting failure via machine learning, and analyzing crack propagation in biomimetic materials. His work spans interdisciplinary areas, integrating materials science with network analysis and polymer chemistry. Education: Advanced degrees in Materials Science (not explicitly stated but inferred from academic rank). Labs: Chair for Materials Simulation at FAU. Publications: Over 50 peer-reviewed articles in journals like Scientific Reports , Physical Review Materials , and Proceedings of the National Academy of Sciences . Research highlights include modeling hierarchical structures for enhanced fault tolerance and developing network-based approaches to predict material failure. His studies often bridge theoretical models with experimental validation, emphasizing practical applications in engineering materials.

Siddhartha Damمشاهده پروفایل

پژوهشگر ارشد

• Materials Science
• Condensed Matter Physics
• Nanotechnology
• +۳ مورد دیگر

Siddhartha Dam is a Research Fellow in the Department of Technical Physics at the University of Würzburg. His research focuses on advanced materials science, including dielectric composites, nanotechnology, and energy materials. He is part of the Technical Physics team at the Chair of Technical Physics, contributing to studies on thin films, thermoelectric properties, and semiconductor physics. Education details are not explicitly provided in the available information. His work involves experimental and theoretical investigations into materials such as PVDF-based composites, MoS 2 , WS 2 , and Bi 2 S 3 nanorods. These studies aim to enhance material performance for applications in energy harvesting, flexible electronics, and quantum technologies. Dr. Dam's research publications emphasize the development of novel materials with improved dielectric, thermoelectric, and photoresponse properties. His work spans interdisciplinary areas, combining experimental synthesis with advanced characterization techniques like Raman spectroscopy and X-ray photoelectron spectroscopy. No scientific awards or grants are mentioned in the provided texts. He advises no students listed, though his role may involve mentoring within his research group. His affiliation with the University of Würzburg’s Technical Physics department places him at the intersection of fundamental research and applied technological innovation.