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نمایش ۳۱-۴۵ از ۱۱۶ استاد راهنما

اطلاعات پروفایل‌ها از صفحات عمومی دانشگاه‌ها گرفته شده و ممکن است به‌روز نباشد.

Ulrich Langerمشاهده پروفایل

استاد

Johannes Kepler University LinzAustria

Ulrich Langer is a Full Professor of Numerical Mathematics at Johannes Kepler University Linz (JKU), Austria. He has held academic positions since 1980, including roles as Scientific Director of the Radon Institute for Computational and Applied Mathematics (2003–2020) and leader of its PDE computational methods research group. He specializes in numerical methods for PDEs, computational mechanics, and parallel computing. Education: Born 1952 in Germany, studied Mathematics at Technical University Karl-Marx-Stadt (Diploma 1975) PhD in Numerical Mathematics from Leningrad University (1980) Habilitation and professorships at Technical Universities of Chemnitz and Linz His research focuses on domain decomposition methods, multigrid techniques, and isogeometric analysis. Key contributions include projects funded by FWF and NSF, such as 'Discontinuous Galerkin Domain Decomposition Methods in Isogeometric Analysis' and 'Goal-Oriented Error Control for Phase-Field Fracture.' Professional Roles: Editorial Board Member of journals like Computing, SIAM Journal on Numerical Analysis, and ZAMM ERC Panel Member for Mathematics (2008–2025) Organized international conferences, e.g., 17th Domain Decomposition Methods (2006) Awards: Multi-Grid Prize (2025). Extensive supervision of 29 PhD students and 24 diploma theses.

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Wilfried Elmenreichمشاهده پروفایل

استاد

University of KlagenfurtAustria

Wilfried Elmenreich is a Professor at the Institute for Networked and Embedded Systems at Alpen-Adria-Universität Klagenfurt. He holds roles as Member of the Senate and Member of the Works Council for Academic University Staff. His research focuses on computational systems, energy engineering, and smart technologies, including swarm intelligence, cyber-physical systems, and sustainable energy solutions. Key interests include non-intrusive load monitoring (NILM), renewable energy integration, and decentralized learning paradigms. Research priorities encompass computer simulation, electrical power engineering, complex systems, and self-organization. Notable work includes frameworks like SwarmFabSim for production scheduling and CPSwarm for swarm robotics design. He also explores sustainability education and pandemic-related behavioral shifts in sustainability attitudes. Recent publications highlight advancements in federated learning for smart grids, energy disaggregation using NILM, and applications of biologically-inspired algorithms in critical infrastructure. His work integrates simulation reproducibility, open-source tools like Gradle/Docker, and educational games for renewable energy awareness (e.g., DAYSAM). Labs/Teams: Core member of the Institute for Networked and Embedded Systems, leading projects in CPS design, energy systems, and swarm robotics. Collaborates on EU initiatives like CPSwarm and educational outreach in sustainable development.

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Henri Balمشاهده پروفایل

استاد

Graz University of TechnologyAustria

Henri Bal is a Full Professor in the Department of Computer Science at Vrije Universiteit Amsterdam's Faculty of Sciences, leading a research group of over 20 members in High Performance Distributed Computing since 2005. His career at the university spans from Research Assistant (1982) to current Professor, with prior appointments including Associate Professor (1994) and split Full Professor roles across Computer Science and Physics (1998). Education: PhD in Computer Science, Vrije Universiteit Amsterdam (1989) MSc in Mathematics, Delft University of Technology (1982) Professor Bal's research integrates fundamental distributed systems with real-world applications, specializing in programming environments for clusters, grids, clouds, and mobile systems. His work spans semantic web reasoning, distributed model checking, and scientific applications in astronomy (LOFAR), high-energy physics (NIKHEF), and climate modeling (Utrecht University), evidenced by systems like Orca, MagPIe, Manta, and Ibis/JavaGAT. Scientific Awards: NWO PIONIER award (1993-1997), comparable to an ERC starting grant Work on Awari recognized in 'The Math Book' as a historic mathematics achievement Multiple first prizes in IEEE International Scalable Computing Challenges (2008, 2010) Two EuroSys Roger Needham PhD awards for his students (2010, 2013) He established foundational Dutch research infrastructure through the NWO DAS project, creating distributed testbeds used by ~100 PhD candidates. As adjunct director of the €40M Virtual Lab for e-Science (2004-2009), he catalyzed the Netherlands eScience Center's formation and participated in EU projects (Gridlab, XtreemOS, Contrail). Currently, he chairs the Department of Computer Science Science committee and explores GPU and smartphone-based distributed systems. His research group actively collaborates with NIKHEF, LOFAR, and Utrecht University on domain-specific applications while advancing hybrid distributed computing frameworks.

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Hans Auerمشاهده پروفایل

استاد

Vienna University of TechnologyAustria

Hans Auer serves as Professor in Energy System Economics and Head of the Energy Economics Group (EEG) at Vienna University of Technology (TU Wien) since 2024, with additional appointment as Adjunct Professor at the Norwegian University of Science and Technology (NTNU) since 2023. His leadership spans academic research, European project coordination, and energy policy development. Education: MSc in Electrical Engineering (1996) PhD in Energy Economics (2000) Venia Docendi in Energy Economics (2012) Research Focus: Professor Auer specializes in energy market design, system modeling, and decarbonization strategies with emphasis on renewable integration, sector coupling, and grid flexibility. His work bridges theoretical modeling with practical policy applications across European energy systems, addressing challenges from local communities to continental-scale transitions through advanced computational methods and economic analysis. Publication Trends: Recent publications (2023-2026) reveal concentrated research on European decarbonization pathways, hydrogen storage economics, electric vehicle integration, and peer-to-peer energy trading. Key thematic clusters include scenario modeling for 2050+ transitions, optimization of flexible resources in congested grids, and socio-technical analysis of local energy communities within circular economy frameworks. Academic Leadership: With over 25 years of supervision experience for bachelor, master, and PhD students, Professor Auer coordinates major European initiatives including PSS2030+ (power system security), iDesignRES (renewable integration tools), and RENVELOPE (building energy retrofits). His project portfolio demonstrates sustained funding success across EU Horizon programs and national research agencies. Operational Framework: Leading the EEG research unit within TU Wien's Institute of Energy Systems and Electrical Drives, he directs a multidisciplinary team conducting policy-relevant analysis for European Commission bodies, national regulators, and industry stakeholders through evidence-based modeling of energy transitions.

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Wolfgang Kastnerمشاهده پروفایل

استاد

Vienna University of TechnologyAustria

Wolfgang Kastner is a Full Professor at the Department of Automation Systems, Faculty of Informatics, Vienna University of Technology (TU Wien). His research focuses on Distributed Automation, Industry 4.0, Smart Grids, IoT, and Cybersecurity in Industrial Systems. He is affiliated with TU Wien and actively contributes to projects funded by institutions like the Austrian Research Promotion Agency (FFG) and TÜV Austria. His work spans safety, security, and integration challenges in IT/OT convergence. Research interests include Industrial Automation, Cyber-physical Systems, and IoT applications. He leads projects such as the TÜV AUSTRIA Security in Industry Research Lab and collaborates on initiatives like FORA (Fog Computing for Robotics) and DiCYCLE (Digitalization in Construction). His research addresses energy efficiency, fault detection, and semantic integration in industrial and building automation systems. Key projects include: Unleashing Sector-coupling Flexibility (2023–2027) Contextual Deep Learning for Predictive Analytics (2023) Semantics-based Explanation of Cyber-physical Systems (2023–2025) His contributions to standards like Asset Administration Shell (AAS) and AutomationML (AML) highlight his role in bridging theoretical and applied cybersecurity and safety engineering.

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Eva Kopeckáمشاهده پروفایل

استاد

University of InnsbruckAustria

Univ.-Prof. Dr. Eva Kopecká is a Professor at the University of Innsbruck's Department of Mathematics, Faculty of Mathematics, Computer Science and Physics. She specializes in Functional Analysis, Geometry of Banach Spaces, Nonlinear Analysis, and Combinatorics. Currently teaching Discrete Mathematics and Introduction to Higher Analysis in the 2024 summer semester, she also leads the Research Seminar in Functional Analysis. Her work focuses on projection algorithms, Lipschitz mappings, and fixed point theory. Notable research includes studies on alternating projections, zone diagrams, and geometric embeddings. She has conducted projects funded by the Austrian Science Fund (FWF), including work on Lipschitz mappings and contraction operators. No formal awards are listed, but her contributions to operator theory and functional analysis are widely recognized. Consultation hours are by email appointment.

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Michael Feischlمشاهده پروفایل

استاد

Vienna University of TechnologyAustria

Michael Feischl is a Professor for Computational PDEs at TU Wien (since 2022) and holds an ERC Consolidator Grant for his project "New Frontiers in Optimal Adaptivity" (2024–2029). His research focuses on partial differential equations with random coefficients, computational micromagnetism (Landau-Lifshitz-Gilbert equation), and optimal adaptive mesh refinement techniques. He leads the Computational PDEs research group within the Institute of Analysis and Scientific Computing. Education and career highlights include roles as Associate Professor at TU Wien (2019–2022), W2 Professor at University of Bonn (2017–2018), and Junior Research Group Leader at KIT (2015–2017). His work bridges numerical analysis, computational physics, and machine learning, with a strong emphasis on rigorous mathematical foundations and algorithmic efficiency. Research interests include: Adaptive finite element and boundary element methods Stochastic modeling and uncertainty quantification Computational methods for micromagnetic simulations Machine learning applications in numerical analysis His recent work explores optimal adaptivity for time-dependent PDEs, neural network-based solvers, and efficient discretization strategies for complex physical systems. Key contributions include advancements in a posteriori error estimation and hierarchical training of neural networks.

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Günther Eiblمشاهده پروفایل

مدرس ارشد

Salzburg University of Applied SciencesAustria

Günther Eibl is a Senior Lecturer and Senior Researcher at the Salzburg University of Applied Sciences , affiliated with the Department Information Technologies and Digitalisation . He serves as Head of Research Group and Deputy Head of the Center for Secure Energy Informatics , combining 50% teaching and 50% research responsibilities. Education: MSc in Mathematics (Numerics Thesis) MSc in Physics (Plasma Physics Simulation Thesis) PhD in Machine Learning (Multiclass Boosting Thesis) Research Interests focus on Privacy in Smart Grids , including: Privacy Analyses – Using machine learning and statistics to extract information from load profiles. Privacy-Enhancing Technologies (PETs) – Historically focused on homomorphic encryption, masking, differential privacy, and wavelet analysis; current research emphasizes privacy-preserving price calculation and proving privacy properties of protocols. Scientific Contributions span 15+ years, with recent work (2025–2021) addressing: Privacy threat modeling for renewable energy communities Smart meter data anonymization Blockchain-based secure aggregation Game-theoretic privacy proofs Differential privacy in load forecasting Intrusion detection in power grids Skills include cryptography, data mining, and energy informatics, with a strong emphasis on visualization and applied statistics . He teaches applied mathematics , applied statistics , and data mining in bachelor and master programs.

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Michael Hausserمشاهده پروفایل

استاد

Graz University of TechnologyAustria

Michael Hausser is a Professor of Neuroscience at University College London (UCL) and a Wellcome Trust Principal Research Fellow. His research focuses on neural computation, synaptic integration, and dendritic physiology. He holds significant academic leadership roles, including co-Chief Editor of Current Opinion in Neurobiology and memberships on numerous scientific advisory boards globally. His honors include election to the Royal Society (2015), Academy of Medical Sciences (2012), and EMBO (2010). Key contributions span optogenetic neural circuit analysis, dendritic processing, and cerebellar function. Education: 1988–1992: D.Phil. in Neuroscience, Oxford University (Commonwealth Scholar) 1992–1995: Postdoctoral Fellowships at Max-Planck Institute (Germany) and Ecole Normale Supérieure (France) Research Interests: Neuronal computation in dendrites Synaptic plasticity mechanisms Cerebellar circuit function In vivo neural circuit analysis Awards: ERC Advanced Grant (2016, 2009) Fellowships from Wellcome Trust, HFSP, and Alexander von Humboldt Foundation Grants & Leadership: Advisory roles at institutions like the Sainsbury-Wellcome Centre and IMP Vienna NIH BRAIN Initiative Panel Member (2014–2015) His lab pioneered techniques like targeted patch-clamp recordings in vivo and explores how neurons process temporal and spatial information at the cellular and circuit levels.

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Albert Wiltscheمشاهده پروفایل

استادیار

Graz University of TechnologyAustria

Albert Wiltsche is an Assistant Professor at the Institute of Architecture and Media , Graz University of Technology. His academic journey began with studies in descriptive geometry and mathematics at Graz University of Technology and Karl-Franzens University of Graz, followed by a doctorate in 2000 with a dissertation titled "Interpolation of Points of a Regular Triangular Grid." He has been actively involved in teaching and research since 1994, transitioning from a contract assistant at the Institute of Geometry to his current role since 2007. Education: Graz University of Technology (PhD in Geometry, 2000), Karl-Franzens University of Graz (Mathematics), Graz University of Technology (Descriptive Geometry). Research Focus: Geometric applications in architecture, parametric modeling, digital fabrication, folding structures, and free-form surface discretization. His work explores the intersection of mathematical precision and architectural creativity, particularly in non-standard geometries and sustainable systems. Collaborations: Frequently works with Milena Stavric on projects like "Parametric Kirigami" and "Interactive Spots," integrating digital tools into architectural education and practice. Projects: Led FWF-funded research on "Non-standard Architecture with Ornaments and Planar Elements," emphasizing material efficiency and aesthetic control in curved surfaces. Publications: Over 84 research outputs spanning computational geometry, digital fabrication strategies, and pedagogical innovations in architectural education.

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Lukas Exlمشاهده پروفایل

مدرس ارشد

University of ViennaAustria

Lukas Exl is a Senior Lecturer at the University of Vienna and a Research Director at the Wolfgang Pauli Institute (WPI), where he leads the Mathematical AI/ML Research Division. He holds a habilitation (venia docendi) in Computational Science from the University of Vienna, the first in this interdisciplinary field. Research Platform MMM Mathematics-Magnetism-Materials Wolfgang Pauli Institute (WPI), Vienna His research integrates Applied Mathematics, Computational Physics, and Scientific Machine Learning, focusing on numerical methods for PDE-based simulations, data-driven modeling, and reduced-order approaches. Key applications include computational micromagnetism for green energy materials and developing physics-informed neural networks (PINNs) with interpretable architectures. Recent publications emphasize machine learning techniques for magnetic material optimization, stray field computation, and trustworthy AI (TAI/XAI). He supervises students in Computational Science, Applied Mathematics, and Physics, with a focus on Extreme Learning Machines (ELMs), PINNs, and tensor decomposition methods. Data-driven Reduced Order Approaches for Micromagnetism (FWF Project, €484k, 2024-2028) Design of Nanocomposite Magnets by Machine Learning (FWF Project, €254k, 2022-2027) Reduced Order Approaches for Micromagnetics (FWF Project, €402k, 2018-2024) His team includes researchers like Dr. Sebastian Schaffer (PhD graduate), Kein Gjordeni, and Caroline Maitz. Collaborations span Danube University Krems and Technical University of Denmark's Energy Conversion and Storage department.

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Susanna Winkelbauerمشاهده پروفایل

پژوهشگر ارشد

University of ViennaAustria

Susanna Winkelbauer is a Research Fellow at the University of Vienna's Institute of Meteorology and Geophysics, specializing in climate data analysis. Her research examines Arctic energy budgets, ocean heat content, and water cycle dynamics using observational data and climate models. She contributes to international collaborations like the Arctic Energy Budget Group. Winkelbauer's work validates climate models against observational data, particularly focusing on CMIP6 simulations in polar regions. She develops methodologies for computing oceanic transports and freshwater fluxes, with applications to Arctic climate studies.

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Battaglia Francesco Paoloمشاهده پروفایل

استاد

Graz University of TechnologyAustria

Francesco Paolo Battaglia is a Full Professor in 'Neuronal Networks of Memory' at the Donders Centre for Neuroscience, Radboud University Nijmegen, The Netherlands. He previously held positions as Associate Professor (2013-2020) and Assistant Professor (2006-2012) at Radboud University and the University of Amsterdam, respectively. His academic career spans institutions in the Netherlands, Belgium, and France, with postdoctoral work at the University of Arizona. PhD in Cognitive Neuroscience (1998) - SISSA, Trieste, Italy Master in Physics (1994) - University of Rome 'La Sapienza' Research Focus: Battaglia bridges computational and systems neuroscience to understand memory mechanisms, particularly through hippocampal networks. His work integrates neurophysiology with advanced data analysis, emphasizing spatial cognition and memory consolidation. He has pioneered interdisciplinary approaches combining neurotechnology and theoretical modeling. Funding & Collaborations: He has secured over €6 million in grants, including ERC Advanced Grant 'REPLAY-DMN' (2019-2024) and leadership roles in EU-funded consortia like M-GATE and NEUROSEEKER. His research has shaped frameworks for entorhinal grid cell function cited in Nobel Prize motivations. Scientific Leadership: Awards highlight his impact: ERC Advanced Grant (2019) 2010 'Prix la Recherche' for Neuron paper 2018 Neuron 'Top 30' recognition 2015 Royal Academy of Sciences Netherlands acknowledgment 2014 Nobel Prize citation contribution Academic Service: Battaglia has organized major events, including the 2018 SISSA School 'Under the surface of memory phenomena' and the 2016 Dutch Optogenetics Meeting. He has mentored 6 postdocs, 9 PhD students, and 18 master students across institutions.

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Christoph Schafferمشاهده پروفایل

استاد

University of Applied Sciences Upper AustriaAustria

Christoph Schaffer is a Professor at the University of Applied Sciences Upper Austria's Research Center Hagenberg, specializing in Information & Communications Technology with a focus on energy systems. He leads projects addressing smart cities, energy data interoperability, and decentralized energy ecosystems. His research integrates artificial intelligence, IoT, and human-centered design to advance sustainable energy solutions. He is the Principal Investigator (PI) for major initiatives including the EU-funded CELINE project (2024–2027) for localized energy innovation and ECLIPSE (2024–2026) targeting energy consumption reduction through open-source frameworks. He also collaborates on the EDDIE project (2023–2025) developing distributed energy data infrastructure. His research interests span microgrid optimization, energy sharing platforms, and HCI strategies for energy literacy. He received the Best Paper Award in 2021 for pioneering work on microgrid energy sharing systems. Key contributions include frameworks for urban microgrid data accessibility (2025), the Common European Energy Data Space blueprint (2024), and end-to-end P2P energy ecosystems (2024). His work bridges technical innovation with community empowerment in energy transition efforts. Grants and projects include €multi-million EU Horizon and national funding, focusing on storage clusters, open-source energy tools, and cross-sectoral digital services.

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Matthias Janetschekمشاهده پروفایل

دانشیار

MCI Management Center InnsbruckAustria

Matthias Janetschek holds the position of Associate Professor at the Management Center Innsbruck (MCI), Austria, since September 2020. Previously, he served as a Lecturer at MCI (2018–2020) and was a Co-Founder/Senior Developer at Felix Solution UG (2013–2015). He earned a PhD in Computer Science from the University of Innsbruck (2011–2019), alongside earlier degrees in Computer Science (BSc 2002–2007, MSc 2007–2011). His research focuses on distributed systems, workflow management, cybersecurity, and IoT , with notable contributions to scientific workflow execution on cloud/manycore architectures and AR/VR applications in education. He has supervised over 18 bachelor/master theses addressing topics like IoT security, reinforcement learning, and edge computing. Teaching responsibilities include courses such as Distributed Systems , Virtual Reality , and Computer Architecture at MCI. He has also completed further training in online education tools (e.g., Sakai, Adobe Connect) and corporate communication. His publications span journals like Multimodal Technologies and Interaction and conference proceedings on workflow systems, cloud computing, and AR usability. Current work emphasizes large-scale IoT security assessments and edge computing optimizations.

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