جست‌وجوی استاد و پژوهشگر

Markus Oppelمشاهده پروفایل

پژوهشگر

• Theoretical Chemistry
• Quantum Chemistry
• Computational Chemistry
• +۵ مورد دیگر

Markus Oppel is a researcher in the Department of Theoretical Chemistry at the Faculty of Chemistry, University of Vienna. With a PhD in Theoretical Chemistry completed in 1998 and a Diploma in Chemistry from Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) completed in 1995, he has established himself as an active contributor to computational and theoretical chemistry with 46 publications spanning nearly three decades. Education: Theoretical Chemistry, PhD (January 1996 - April 1998) Chemistry, Diploma, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) (1990 - 1995) Dr. Oppel's research focuses on quantum dynamics, excited state calculations, and computational method development. His fingerprint analysis reveals significant contributions to Laser Pulse Physics (100%), Infrared Laser Physics (75%), Excited State Chemistry (61%), and Electronic State Chemistry (48%). He has made substantial contributions to major computational chemistry software packages including COLUMBUS for ground and excited state computations and SHARC for non-adiabatic dynamics simulations. His recent work shows a strategic evolution toward quantum computing applications in chemistry, particularly in drug design, where his 2024 Nature Physics paper has garnered significant attention with 160 reader captures and 8 news mentions. This represents a bridge between traditional quantum chemistry methods and emerging computational paradigms. Dr. Oppel maintains an active presence in the scientific community with 25 recorded activities, including recent invited talks such as "Artifizielle Photosynthese" (May 14, 2025) and "Heterogeneous Computing in Quantum Chemistry" (November 18, 2024), demonstrating his recognition as an expert in computational chemistry and quantum dynamics.

• Machine Learning
• Industrial Applications
• Smart Manufacturing
• +۳ مورد دیگر

Florian Bachinger is a researcher at the Research Center Hagenberg, University of Applied Sciences Upper Austria, affiliated with the Center of Excellence for Smart Production Digital Transformation and HEAL research group. His work focuses on bridging machine learning with industrial applications, particularly in smart manufacturing contexts. Active researcher with h-index of 26 Involved in the Josef Ressel Center for Symbolic Regression project (2018-2022) Regular participant in international conferences including EUROCAST and Industry 4.0 events His research interests center on Machine Learning systems for industrial applications, with specializations in symbolic regression, constraint evaluation methods, and composable evolutionary computation. His work addresses practical challenges in implementing AI solutions within manufacturing environments, focusing on domain knowledge integration and constraint handling. Analysis of his recent publications reveals a strong trend toward developing practical machine learning frameworks that incorporate physical constraints and domain knowledge for industrial settings. His 2024-2025 work shows increasing focus on modular, composable systems that can be adapted to specific manufacturing contexts while maintaining scientific rigor. Florian actively collaborates with researchers including Haider, Zenisek, and Affenzeller across multiple projects focused on smart production systems. His work demonstrates strong industry-academia connections through applied research in manufacturing contexts.

• Cultural Management
• Cultural Policy
• Gender Studies
• +۵ مورد دیگر

Dagmar Abfalter is the Head of the Institute of Cultural Management (IKM) at the University of Music and Performing Arts Vienna (mdw) . Her career spans cultural policy, leadership in creative industries, and gender studies, with a focus on power dynamics, cultural institutions, and knowledge-sharing frameworks. She has led initiatives like the 40 Years of IKM celebrations and the International Research Center Gender and Performativity . Research Interests : Cultural Management, Gender Studies, Cultural Policy, Leadership in Performing Arts, Cultural Economics. Notable Projects : FACING_DRAG in Popular Cultures and Performing Arts Gender and Labor in the Cultural Field in Serbia Vienna Music Business Research Days Awards : Honorary Doctorate Torton Beck Methodological Contributions : Hybrid analysis of textual data, GABEK® methodology, qualitative-quantitative integration.

• Real-Time Systems
• Worst-Case Execution Time (WCET) Analysis
• Single-Path Code Optimization
• +۳ مورد دیگر

Peter Puschner is an Associate Professor at Vienna University of Technology (TU Wien), affiliated with the Cyber-Physical Systems Research Area. His work focuses on real-time systems, worst-case execution time (WCET) analysis, and time-predictable code execution. Key research areas: Real-Time Systems, Single-Path Code, Time-Triggered Networks, Cache Architectures Advisor to multiple thesis students including Michael Platzer and Bekim Cilku Co-developer of tools like the platin Toolkit for WCET analysis Recipient of Best Paper Award at ECRTS 2015 for Requirement Semi-formalization Methodology for SoC Design

Stefan Wagnerمشاهده پروفایل

استاد

• Evolutionary Computation
• Optimization
• Genetic Algorithms
• +۴ مورد دیگر

Stefan Wagner serves as a Professor at the University of Applied Sciences Upper Austria (FH OOE), based at the Research Center Hagenberg Center of Excellence for Smart Production. His academic affiliation resides within the Department of Production and Operations Management under the institution's ICT focal area. Wagner holds the title FH-Prof. DI Dr. and actively serves as Principal Investigator (PI) on multiple research projects including ENPro (Energy Neutral Production) and JRZ adaptOp (Josef Ressel Center for Adaptive Optimization), driving innovation in optimization and smart manufacturing systems. Wagner's research expertise centers on Evolutionary Computation and Optimization , with specialized focus on Genetic Algorithms, Heuristic Optimization, and Dynamic Optimization. As lead developer of HeuristicLab —an open-source optimization environment—he bridges theoretical advances with industrial applications in Symbolic Regression, Production Scheduling, and Energy-Efficient Manufacturing. His work addresses complex challenges in logistics, crane scheduling, and energy-neutral production through evolutionary techniques. Recent publications (2025) reveal a pronounced trend toward distributed and dynamic optimization frameworks. Key themes include diversity management in changing environments, containerization for scalable evolutionary computation, and hybrid cooperative approaches for symbolic regression. Applications span container terminal logistics, energy-neutral manufacturing, and robust unloading bay optimization, demonstrating strong industry-oriented problem-solving. Wagner received the FH OÖ Researcher Award in 2019 for exceptional contributions. He has secured funding for 9 research projects including ENPro (2025-2028) and SMART UNLOAD, frequently serving as PI or Co-PI. His projects tackle production optimization, workforce planning, and energy efficiency in Upper Austrian manufacturing. With 4 supervised students and extensive community engagement through EvoSoft at GECCO and EUROCAST peer review, he actively shapes the evolutionary computation landscape. Leading the HeuristicLab project, Wagner collaborates with industry partners through the Center Hagenberg research team to develop simulation and optimization tools for adaptive scheduling. His current work in the ENPro project targets energy-neutral production via modeling and optimization, positioning him at the forefront of sustainable manufacturing innovation in industrial settings.

• Computer Science
• Algorithms
• Linear Algebra
• +۳ مورد دیگر

Carlos Andres Pachajoa Mejia is a faculty member in the Faculty of Computer Science and part of the Research Group Theory and Applications of Algorithms . His work focuses on algorithm design and fault tolerance in high-performance computing environments. Research Areas : Algorithms, Linear Algebra, Fault-Tolerant Computing, Parallel Processing. Key Contributions : Development of node-failure resilience strategies for iterative linear algebra methods, including the Conjugate Gradient Method and checkpoint-recovery techniques. His publications from 2018–2020 reveal a consistent focus on enhancing the reliability of numerical algorithms in distributed systems. Collaborations with researchers like Gansterer and Levonyak underscore his team-based approach to solving computational challenges.

Daniel Jodlbauerمشاهده پروفایل

پژوهشگر

• Computational Mathematics
• Numerical Analysis
• Biomedical Imaging
• +۴ مورد دیگر

Dr. Daniel Jodlbauer is a Research Scientist at the Johann Radon Institute for Computational and Applied Mathematics (RICAM) , part of the Austrian Academy of Sciences (OEAW). He is affiliated with the Transfer Group , focusing on interdisciplinary computational methods and their applications in science and engineering. His research spans numerical analysis, computational mechanics, and biomedical imaging. Key projects include developing matrix-free multigrid solvers for fluid-structure interaction and phase-field fracture problems, and advancing adaptive optics for biomedical imaging (e.g., AO-OCT) and astronomical instrumentation (e.g., the MICADO imager for the Extremely Large Telescope). His work bridges theoretical computational methods with real-world applications in medicine, astronomy, and engineering. Recent contributions highlight advancements in PSF reconstruction for the MICADO project, improving imaging resolution for the ELT telescope, and optimizing wavefront sensors for retinal imaging. His computational methods address challenges in high-performance computing, parallel algorithms, and nonlinear solvers for complex physical systems. Dr. Jodlbauer collaborates across disciplines, contributing to RICAM’s research groups in Computational Methods for PDEs and Optimization. His publications reflect expertise in mathematical data science, inverse problems, and multivariate algorithms, though no academic awards or grants are explicitly noted in the provided text.

Manuel Hermenegildoمشاهده پروفایل

استاد

• Constraint Programming
• Logic Programming
• Functional Programming
• +۷ مورد دیگر

Manuel Hermenegildo is a Full Professor at the Technical University of Madrid (UPM) and Director of the IMDEA Software Research Institute in Spain. He held the Prince of Asturias Endowed Chair at the University of New Mexico (2003-2008) and was previously a project leader at MCC (1986-1989) and Adjunct Associate Professor at the University of Texas at Austin (1987-1990). Education: M.S. and Ph.D. in Computer Engineering, University of Texas at Austin (1986) Engineer's Degree in Electrical and Telecommunications Engineering, Technical University of Madrid (1981) His research spans programming language design , abstract interpretation-based analysis , parallelizing compilers , and parallel/distributed processing . His work integrates theoretical advances with practical implementations like the Ciao system and PiLLoW library. Recent publications focus on parallelization , program verification , mobile code security , and distributed programming . Key methodologies include abstract interpretation , constraint logic programming , and compiler optimization . Scientific Awards: ACM Fellow Julio Rey Pastor Prize (highest Spanish national award in Mathematics and ICT) Aritmel Prize in Computer Science President of the Association for Logic Programming He has led numerous national and international projects, served as area editor for journals like Theory and Practice of Logic Programming , and participated in EU advisory committees (ISTAG, CREST). His work on the Abstraction Carrying Code (ACC) approach advances mobile code safety and trusted computing.

• Digital Media and Multiliteracies
• Media Activism and Citizenship
• East European Studies
• +۴ مورد دیگر

Auksė Balčytienė is a Professor of Journalism and Communication at Vytautas Magnus University (Kaunas, Lithuania), holding the UNESCO Chair on Media and Information Literacy for Knowledge Inclusive Societies since 2018. Previously, she served as Vice-Rector for Public Communication (2006–2015) and held the Erich Brost Professorship for International Journalism in Europe at the University of Dortmund (1999–2000). She earned her Doctoral degree in Philosophy of Education from the University of Eastern Finland (1990–1996). Her research focuses on digital media, media activism, Eastern European studies, and media policy governance. Notable interests include media transformations and their impact on social change, European public sphere dynamics, and comparative media systems. As Editor-in-Chief of Media Transformations (2005–2017), she has contributed to shaping scholarly discourse in these areas. Her work addresses challenges such as disinformation governance, media-politics interactions, and the intersection of media freedom with democratic institutions. Balčytienė’s scholarship bridges theoretical frameworks with policy-oriented analysis, emphasizing inclusive media literacy and resilient democratic practices in post-socialist contexts. Publications from 2015–2021 reflect her engagement with media agency crises, Baltic media accountability, and cross-national comparisons of political communication cultures. These works highlight systemic tensions between journalistic ideals and institutional realities, alongside the evolving role of media in fostering societal well-being and participatory citizenship.

• Databases
• Database Theory
• Complexity Theory
• +۲ مورد دیگر

Christoph Koch is an Associate Professor at Technische Universität Wien specializing in databases and artificial intelligence. His research spans database theory, complexity theory, and logic in computer science, with a focus on XML processing, query optimization, and parallel data science techniques. Lead projects: KnowledgeGraph (2020–2028), HINT (2012–2017), Weblearn (2005–2008) Developed the Lixto visual extraction system and contributed to DLV knowledge representation framework Supervised T. Lukasser's diploma thesis on XPath query processing

Stefan Ohrhallingerمشاهده پروفایل

پژوهشگر

• Computer Graphics
• Geometry Processing
• Surface Reconstruction
• +۳ مورد دیگر

Stefan Ohrhallinger is a Senior Researcher at TU Wien's Institute of Visual Computing and Human-Centered Technology. He holds a PhD from Concordia University (2013) and a Master's in Business Informatics from Johannes Kepler University Linz (1997). His research focuses on surface reconstruction, point-based graphics, and geometry processing with applications in computer graphics and virtual/augmented reality. Education: PhD in Computer Science, Concordia University (2013) Master of Business Informatics, Johannes Kepler University Linz (1997) Affiliations: Principal Investigator for grants totaling €1.7M+ (e.g., WWTF Modeling the World at Scale, FWF Superhumans) Teaching: 'Modeling in Computer Graphics' and 'Scientific Writing' courses His work emphasizes robust algorithms for reconstructing curves/surfaces from sparse/noisy data, with contributions to occlusion-aware processing and large-scale point cloud handling. Notable achievements include the Best Poster Award at Eurographics 2012 and over 30 peer-reviewed publications. Grants & Projects: WWTF 'Modeling the World at Scale' (2020–2026, €578k) FWF 'Superhumans: Walking Through Walls' (2019–2023, €333k) IPA 'Photogrammetry made easy' (2020–2022, €50k)

Majid Salimibeniمشاهده پروفایل

پژوهشگر ارشد

• High Performance Computing
• Parallel Computing
• Message Passing in Large-scale HPC systems
• +۶ مورد دیگر

Majid Salimibeni is a PostDoc Researcher and Research Fellow at Vienna University of Technology (TU Wien) , affiliated with the Parallel Computing research unit. He previously held a Postdoc position at the Department of Computer Science at the University of Salerno, Italy (2024), and has been a visiting researcher at TU Wien (2023). Currently based in Vienna, Austria, his work focuses on High Performance Computing (HPC) and its interdisciplinary applications. Education: Ph.D. in Computer Science, University of Salerno, Italy (2020–2024) M.Sc. in Computer Engineering (Software), Shiraz University, Iran (2017–2020) B.Sc. in Computer Engineering (Software), University of Birjand, Iran (2012–2016) Salimibeni's research explores High Performance and Parallel Computing , with a focus on optimizing GPU communication via NCCL , improving energy efficiency in heterogeneous computing environments , and enhancing MPI collective algorithms for large-scale systems. His work bridges HPC infrastructure with emerging applications in Distributed Deep Learning and AI . Recent publications highlight his expertise in GPU frequency scaling , NCCL profiling , and process arrival pattern analysis to improve distributed system performance. These works appear at top conferences like IPDPS , Cluster Computing , and ASHPC . Scientific Awards: Best Paper Award, Bench 2022 Salimibeni contributes to academic committees as a program committee member for IEEE ICPP 2025, ISC 2025, and BigHPC 2024, and serves on artifact evaluation committees for ASPLOS and CF conferences.

• Compiler Optimization
• Embedded Systems
• Robotics Software Engineering
• +۴ مورد دیگر

Dietmar Schreiner is a Senior Lecturer at TU Wien's Faculty of Informatics within the Department of Compilers and Languages. His research focuses on compiler optimization, real-time systems, robotics software engineering, and component-based automotive software. He has contributed to major projects like C3Pro (2010–2015) and ALL-TIMES (2007–2010), addressing challenges in embedded systems and automotive software. He advises students on robotics and embedded systems projects, including thesis works like 'Robotersteuerung mittels Genetic Programming für die RoboCup Standard Platform League' (2011) and 'Reasoning capabilities for a cognitive-assistive assembly system' (2017). He is actively involved in the Austrian Kangaroos robotics team and has received the Best Poster Award at SAC 2007 for work on UML-based component modeling. His teaching responsibilities include courses such as 'Introduction to Programming 1', 'Programming Principles of Mobile Robotics', and 'Fundamentals of Digital Systems'. He has also contributed to EU and national grants, advancing research in timing analysis and automotive system software.

• Graph Neural Networks
• Machine Learning
• Structured Data Learning
• +۳ مورد دیگر

Pascal Welke is a PostDoc Researcher at the Department of Machine Learning, Technical University of Vienna, working on the StruDL project (2023-2027) funded by the Vienna Science and Technology Fund (WWTF). His research focuses on enhancing graph neural networks (GNNs) through theoretical and practical advancements in expressivity, pooling mechanisms, and global feature integration. Active in graph representation learning, neural architecture design, and model interpretability Collaborates on interdisciplinary projects involving material science and computational linguistics Contributor to NeurIPS, ICLR, and ACL conferences Recent publications analyze the role of expressivity in GNN performance, introduce loop-based WL hierarchies, and develop model distillation techniques. His work spans both theoretical insights (homomorphism-based representations) and practical applications (edge device optimization, nonwoven material analysis). No formal awards or students listed in available records.

• Real-time systems
• Multi-threaded systems analysis
• Weak memory models
• +۵ مورد دیگر

Johann Blieberger is an Associate Professor and Head of the Institute of Computer Engineering at Technische Universität Wien. He also leads the Automation Systems Research Unit (E191-03) and serves as a Principal Member of the Faculty Council. His work focuses on real-time systems, concurrent programming, railway operation optimization using Kronecker Algebra, static analysis, and Ada programming. Key projects include developing simulation tools for sustainable public transport (2021–2023), coordinating autonomous vehicles in pedestrian environments (2017–2019), and optimizing railway systems via Kronecker Algebra (e.g., the Zagreb-Rijeka line). He has secured grants from the Austrian Research Promotion Agency (FFG) and Austrian Science Fund (FWF). Blieberger’s research interests span weak memory models, symbolic evaluation, and algorithm analysis. He actively contributes to the ISO JTC1/SC22/WG9 committee for Ada language development. His advising spans multiple PhD and master’s theses, including work on concurrent program verification and Kronecker Algebra applications.