جستجوی استاد راهنمای دانشگاهی

Katja Hoseمشاهده پروفایل

استاد

• Knowledge Graphs
• Semantic Web
• Data Management
• +۷ مورد دیگر

Katja Hose is a Full Professor of Data Management at TU Wien's DBAI research unit, heading the Data Management and Knowledge-Driven AI Lab. She previously held a Poul Due Jensen Foundation Professorship at Aalborg University. Her research focuses on data and knowledge engineering, including graph databases, knowledge graphs, querying, analytics, and machine learning, with interdisciplinary applications in bioscience, healthcare, and environmental assessment. Education: PhD in Computer Science (Ilmenau University of Technology, 2009), Postdoc at Max Planck Institute for Informatics (2009–2012). Academic roles include Program Co-Chair for ISWC 2024 and EDBT 2023, and editorial board membership at VLDBJ and TGDK. She leads projects like TARGET (health virtual twins) and ARMADA (data management). Research Interests: Knowledge Graphs, Semantic Web, Big Data, Machine Learning, Data Integration, and Provenance Systems. Key contributions include SHACL shape extraction, conversational data analytics, and environmental knowledge graphs. Awards include the 2025 Distinguished Meta-Reviewer Award and 2024 Manfred Paul Award. Advising and Grants: Supervised students including E. Pürmayr (Diploma Thesis 2025). Active in EU projects (TARGET, ARMADA) and grant coordination. Labs/Teams: DMKI Lab at TU Wien, collaborating with interdisciplinary teams in healthcare and environmental science.

Wojciech Rytterمشاهده پروفایل

استاد

• Design and analysis of computer algorithms
• Automata and formal languages
• Parallel algorithms
• +۵ مورد دیگر

Wojciech Rytter is a full professor at the Institute of Informatics, Department of Mathematics and Informatics at the University of Warsaw, Poland, holding this position continuously since October 1971. His academic career includes significant international appointments as full professor at New Jersey Institute of Technology (2002-2004), Liverpool University (1997-2002), and Bonn University (1994-1995), and as visiting professor at University of California, Riverside (1992-1993) and University of Warwick (1985-1986). He earned his MSc in 1971, PhD in 1975, habilitation in 1985, and was awarded the scientific degree of professor in 1997, all from Warsaw University. Professor Rytter's research focuses on the design and analysis of computer algorithms, with particular expertise in automata and formal languages, parallel algorithms, and text algorithms. His work spans efficient sequential and parallel algorithms, automata theory, complexity of recognition and parsing of context-free languages, pattern matching, algorithmics of WWW, parallel combinatorial computing, graph-theoretic algorithms, and algorithmics of highly compressible objects. His theoretical contributions have practical applications in computational biology, bioinformatics, and text processing systems. His recent publications (2022-2025) demonstrate continued activity in string algorithms, particularly in pattern matching, string covers, and combinatorics on words, with a strong focus on theoretical computer science with applications in bioinformatics. 200 problems on automata, languages, computations (Cambridge University Press 2023) 125 Problems in Text Algorithms (Cambridge University Press, 2021) Jewels of Stringology (World Scientific, 2002) Fast parallel algorithms for matching problems in graphs (Oxford University Press 1998) Text algorithms (Oxford University Press 1994) Professor Rytter has collaborated extensively with researchers including Jakub Radoszewski, Tomasz Walen, Tomasz Kociumaka, and Maxime Crochemore. He is a member of the Academy of Europe (elected 2011, Informatics section) and has authored or co-authored more than 130 publications. He maintains an active research laboratory focused on string algorithms and combinatorics on words at the University of Warsaw.

• Reconfigurable Computing
• FPGA Accelerators
• Parallel and Distributed Computing
• +۳ مورد دیگر

Viktor Prasanna is the Charles Lee Powell Chair in Engineering and Professor of Electrical and Computer Engineering and Computer Science at the University of Southern California. He holds courtesy appointments in Computer Science and leads the Center for Energy Informatics, focusing on interdisciplinary research linking energy technologies, computer science, and engineering. Education: BE in Electronics (Bangalore University), ME (Indian Institute of Science), PhD in Computer Science (Pennsylvania State University) His research spans reconfigurable computing, FPGA accelerators, parallel and distributed systems, and big data applications. He has pioneered high-performance architectures and algorithms using FPGAs, impacting domains like networking, security, HPC, and machine learning. Prasanna has published over 600 papers, received 22 best paper awards, and secured >$50M in grants. His work emphasizes energy-efficient computing, with recent grants totaling $12.9M (2016–2021). His h-index is 73, with 23,454 total citations. Scientific Awards: IEEE Fellow, ACM Fellow, AAAS Fellow, W. Wallace McDowell Award, multiple Distinguished Alumnus Awards He has advised over 70 doctoral students and led major centers including CiSoft (Big Data in oilfield tech) and CAST. His editorial roles include Editor-in-Chief of IEEE Transactions on Computers and Journal of Parallel and Distributed Computing.

• Migration Studies
• Refugee Integration
• Cultural Production
• +۵ مورد دیگر

Michael Parzer is an Associate Professor in the Department of Sociology at the Faculty of Social Sciences. His academic work focuses on migration studies, refugee integration, and the intersection of artistic practice with social integration processes. He maintains an active research profile with extensive publication output and ongoing research projects that address contemporary migration challenges. Parzer's research interests encompass Migration Studies, Refugee Integration, Cultural Production, Social Inequality, Artistic Practice, and Transdisciplinary Research . His work often examines how migrants, particularly refugees, navigate social structures and cultural landscapes through artistic expression and musical activities. A significant portion of his recent research has focused on Ukrainian refugees and their integration processes in Austria. His publication record shows substantial scholarly output with 91 publications documented, including numerous articles in 2023 and 2024. His recent work demonstrates a strong focus on refugee experiences, particularly examining how artistic practices facilitate integration and shape social identities in post-migrant societies. The publications reveal a consistent engagement with methodological innovation, often employing transdisciplinary and participatory approaches. Parzer is currently leading or participating in multiple research projects including: MUsikCOnnect (MU_CO) (2023-2025): Developing an online platform for inclusive music education The Art of Arriving (2021-2024): Reframing refugee integration through artistic practices Migration Ties (2020-2022): Examining transnational connections based on migrants' social milieu His academic contributions connect with UN Sustainable Development Goals, particularly those addressing social inequality and inclusive societies. Parzer actively engages with public discourse through media contributions and academic presentations, demonstrating commitment to translating research into practical insights for policymakers and practitioners working in migration and integration fields.

• Mixed Methods Research
• Education Science
• Research Methodology
• +۲ مورد دیگر

Judith Schoonenboom is a Professor at the University of Vienna and Deputy Head of the Department of Education. She teaches courses in quantitative and interpretive methodologies, research design, and PhD/master's thesis supervision, including seminars like 'Methodology and Research Design' and 'Quantitative Methodologies in Education Science'. Her academic responsibilities reflect a focus on advanced research methodologies in educational contexts. Schoonenboom's research centers on mixed methods and multimethod approaches in education science, emphasizing methodological innovation, data integration, and theoretical development. Key interests include the interplay between qualitative and quantitative research, design patterns in mixed methods, and strategies for enhancing inferential rigor in social science studies. Her work bridges epistemological frameworks with practical research applications. Her scholarly publications demonstrate a consistent focus on advancing mixed methods research, particularly through innovations in design, integration techniques, and theoretical reflection. Recent works explore causal inference in qualitative research, visualization of methodological interactions, and performative approaches, highlighting trends toward interdisciplinary synthesis and practical methodology refinement.

Leonard Kwhang-Gil Lemkeمشاهده پروفایل

پژوهشگر

• Economic Resilience
• Environmental Impact Assessment
• Social Innovation
• +۵ مورد دیگر

Leonard Kwhang-Gil Lemke is a researcher at the University of Vienna's Faculty of Earth Sciences, Geography and Astronomy within the Department of Geography and Regional Research. Holding a PhD fellowship at the Vienna International School for Earth and Space Sciences, his work bridges geography, economics, and environmental science with a focus on real-world crisis response. His research interests center on rural resilience during the Covid-19 pandemic , examining social and economic innovation across Austria and Thailand through interdisciplinary frameworks. Key thematic areas include economic resilience (100% fingerprint match), environmental impact assessment (100%), socio-ecological systems (50%), and institutional environments (50%). His work directly contributes to UN Sustainable Development Goals related to poverty reduction and planetary protection. Publication analysis reveals a strong trend toward interdisciplinary crisis response research , particularly examining how rural communities leverage agritourism and institutional innovation during pandemics. His work consistently integrates qualitative systems mapping with environmental policy analysis, emphasizing procedural justice in stakeholder engagement and cognitive mapping of complex socio-ecological challenges. Lemke actively participates in academic knowledge exchange through conference presentations including the German Geography Congress (DKG) and Environmental and Climate Mobilities Network (ECMN) events. His research methodology combines case study approaches with systematic mapping techniques to address regional development challenges in times of global crises.

Fan Wenfeiمشاهده پروفایل

استاد

• Database systems
• Database theory
• Big data
• +۳ مورد دیگر

Professor Wenfei Fan is a Chair of Web Data Management at the University of Edinburgh since 2006. He holds adjunct roles at Huawei Edinburgh Research Laboratory and the International Research Center on Big Data at Beihang University. His research focuses on database systems, theory, big data, data quality, and constraint applications. He is a Fellow of the ACM and Royal Society of Edinburgh, and recipient of the ERC Advanced Grant (2015). His work includes foundational contributions to XML constraints, data quality management, and graph databases, with over 160 top-tier publications and 8 patents. Education: BSc and MSc from Peking University (1985, 1988); PhD from the University of Pennsylvania (1999). Professional Roles: Editor for TODS, TCS, VLDBJ, and TBD; PC Chair for PODS, CIKM, APWeb, and others. Key awards include the Roger Needham Award (2008), Yangtze River Scholar (2007), and multiple best paper awards at SIGMOD, PODS, VLDB, and ICDE. He has led over 15 grants totaling €6M and advised students who all received top conference awards. His labs and initiatives drive industry collaboration, with deployed solutions at Huawei for big data query optimization.

Stefan Lengauerمشاهده پروفایل

پژوهشگر

• Visual Analytics
• 3D Object Retrieval
• Image Processing
• +۴ مورد دیگر

Stefan Lengauer is a Senior Researcher at the Institute of Visual Computing (IVC), Graz University of Technology. His work bridges cultural heritage analysis and health informatics through advanced visualization techniques. PhD in Computer Science (2022), Graz University of Technology MSc in Space Sciences (2018), TU Graz BSc in Computer Science (2014-2022) and Aviation (2015), FH JOANNEUM Research focuses on visual analytics , 3D object retrieval , and cross-modal search , with applications in: Medical domains (diabetes care, health information systems) Cultural heritage (pottery analysis, fragment matching, digital restoration) Pattern recognition (geometric motifs, surface textures) Recent publications highlight trends in adaptive visualization (2024-2025) and 3D cultural heritage analysis (2021-2023). Key projects include: HEREDITARY (2024-present): HORIZON Europe project on gut-brain interaction A+CHIS (2020-present): FWF research group on adaptive health information systems CrossSAVE-CH (2019-2022): Cross-modal search in cultural heritage Scientific recognition includes: Best Challenge Entry (2024) Honorable Mention (2020) PhD distinction (2022) Mentored 12+ students in topics ranging from medical chatbots to 3D pottery analysis . Reviewing activities span journals like Springer Nature and conferences including WSCG.

Bernhard Rengsمشاهده پروفایل

پژوهشگر

• Agent-Based Modelling
• Demography
• Population Economics
• +۵ مورد دیگر

Bernhard Rengs is a researcher affiliated with the Vienna Institute of Demography (VID), part of the Austrian Academy of Sciences. He previously served as Assistant Professor at the Institute for Mathematical Methods in Economics at Vienna University of Technology (2003–2014). His work bridges computer science and economics, focusing on computational agent-based models applied to demography, population economics, socio-economics, and forced migration. Education: Holds degrees in computer science and economics from Vienna University of Technology. Research interests include agent-based computational social simulation, evolutionary economics, and information visualization. Current projects address refugee migration patterns, socio-economic integration, and policy impacts using advanced computational methods. Selected Publications (2023–2013) focus on Ukrainian refugee self-selection, refugee family structures, climate policy modeling, and global value chains. His work combines empirical data analysis with agent-based modeling to address complex socio-economic challenges. No formal awards listed, but contributions to migration and computational demography are widely recognized. Collaborations include the Wittgenstein Centre for Demography and Global Human Capital, with interdisciplinary teams addressing demographic transitions, migration dynamics, and policy implications. His research emphasizes practical applications of computational models for understanding societal systems and informing evidence-based policies.

• Recommender Systems
• Multimodal Learning
• Music Emotion Recognition
• +۳ مورد دیگر

Marta Moscati works at the Institute of Computational Perception at Johannes Kepler University Linz , focusing on advanced recommendation systems and multimodal learning. Her research spans emotion-based music recommendation, privacy-preserving machine learning, and graph neural networks. Recent work includes: Developing multimodal single-branch architectures for cold-start scenarios Creating preference obfuscation techniques in implicit feedback systems Advancing music emotion recognition with semi-supervised graph networks Contributing to the FAME Challenge for multilingual face-voice association She has published extensively in top AI venues while maintaining technical expertise in both deep learning and theoretical physics , with early work on lepton universality violation. At JKU, she contributes to: Recommendation algorithms development Multimodal representation learning research Musical affective computing applications Privacy-preserving AI frameworks

• Algorithms
• Data Structures
• Dynamic Graph Algorithms
• +۳ مورد دیگر

Monika Henzinger is a Professor at the Institute of Science and Technology Austria (ISTA), where she has been serving since 2023, and additionally holds the position of Vice President for Technology Transfer since 2024. Her academic journey includes professorships at the University of Vienna (2009-2023) and EPFL in Switzerland (2005-2009), as well as industry experience at Google (1999-2005) and Digital Equipment Corporation (1996-1999). She earned her PhD from Princeton University in 1993 and served as an Assistant Professor at Cornell University from 1993-1996. Dr. Henzinger's research focuses on the design and analysis of efficient algorithms and data structures, with particular emphasis on dynamic settings where inputs change repeatedly, privacy-preserving algorithms, and translating theoretical algorithms into practical implementations. Her work bridges theoretical computer science with practical applications, addressing fundamental questions about computational efficiency in evolving data environments. Her recent publications (2024-2025) demonstrate a consistent focus on dynamic graph algorithms, differential privacy, and optimization problems. These works explore cutting-edge approaches to maintaining graph structures under continuous updates, developing privacy-preserving mechanisms for streaming data, and creating efficient approximation algorithms for fundamental graph problems. The research shows strong connections between theoretical guarantees and practical implementations, with many papers addressing both theoretical bounds and experimental validation. Dr. Henzinger has received numerous prestigious awards throughout her career, including: The 2024 Best Paper Award at the Symposium on Discrete Algorithms The 2021 Wittgenstein Award Two ERC Advanced Grants (2014, 2021) Fellow of the Association of Computing Machinery (2016) Member of the Austrian Academy of Sciences (2017) The Carus medal of the German Academy of Sciences Leopoldina (2019) She currently leads an active research group comprising PhD students and postdoctoral researchers, and her team is supported by multiple significant grants including an ERC Advanced Grant for 'The design and evaluation of modern fully dynamic data structures,' a Wittgenstein Award from the Austrian Science Fund, and several other projects focused on dynamic graph algorithms and data structures. Her collaborative work spans theoretical computer science, algorithm design, and practical implementations. Dr. Henzinger's research group operates within a vibrant ecosystem of algorithmic research at ISTA, focusing on transforming theoretical insights about computational efficiency into practical tools for handling dynamic data. The group maintains strong connections with both theoretical and applied research communities, bridging the gap between abstract algorithm design and real-world implementation challenges.

• Reconfigurable Computing
• Parallel Computing
• FPGA Accelerators
• +۴ مورد دیگر

Prasanna Viktor is a Professor of Electrical and Computer Engineering and Computer Science at the University of Southern California (USC), holding the Charles Lee Powell Chair in Engineering. He also serves as Director of the Center for Energy Informatics and has held leadership roles in interdisciplinary research centers such as the USC Infosys Center for Advanced Software Technologies. With a BE from Bangalore University, ME from Indian Institute of Science, and PhD from Pennsylvania State University, he is a globally recognized expert in reconfigurable computing, FPGA accelerators, and parallel computing. His research focuses on high-performance architectures for applications in networking, security, HPC, and machine learning. Over 25 years, he has secured research grants totaling over $50M, including $12.9M from 2016–2021. He has advised over 70 doctoral students and published over 600 papers, earning 22 best paper awards. His work has led to IP cores with improved throughput, latency, and energy efficiency. Prasanna is a Fellow of the IEEE, ACM, and AAAS, and an elected member of Academia Europaea. He has received prestigious awards such as the W. Wallace McDowell Award (2015) and the Distinguished Alumnus Award from IISc (2019). He currently serves as Editor-in-Chief of the Journal of Parallel and Distributed Computing. He leads interdisciplinary efforts in energy informatics and smart oilfield technologies, bridging computer science, engineering, and energy sectors. His contributions include foundational work in reconfigurable computing and FPGA-based accelerators for diverse applications.

Mirjam Augsteinمشاهده پروفایل

استاد

• Human-Computer Interaction
• Artificial Intelligence
• User Modeling
• +۵ مورد دیگر

Mirjam Augstein is a Professor at the Research Center Hagenberg, part of the Upper Austria University of Applied Sciences, specializing in Human-Computer Interaction and Information & Communications Technology. She holds a Habilitation in Human-Computer Interaction from Johannes Kepler University Linz (2024), a PhD in Computer Science (2011), and a Dipl.-Ing. in Engineering for Computer-Based Learning (2006). Her research focuses on collaborative systems, hybrid collaboration spaces, user modeling, and AI ethics. She leads projects like HYCOS (Hybrid Collaboration Spaces) and HCAI (Human-Centered Artificial Intelligence), exploring interdisciplinary applications of AI in workplaces and crisis management. Notable contributions include work on personalized online layers, adversarial training for recommenders, and accessibility in mixed-ability teams. Key Projects: CIvolunteer (critical infrastructure coordination), HCAI (AI ethics), HYCOS (collaboration spaces) Key Awards: Best Paper Awards at ACM CSCW 2018 and HUCAPP 2018, Microsoft Productivity Research Grant (2019) Professional Activities: Conference chair for ECSCW'26, peer reviewer for ACM CHI and International Journal of Human-Computer Interaction Her work emphasizes inclusive technology design, with over 75 publications and 14 active/recent research projects since 2012. She advises on smart factory training systems and blockchain-based competency platforms, bridging technical innovation with societal impact.

Zhang Junمشاهده پروفایل

استاد

• Biological Physics
• Nonlinear dynamics and complex systems
• Soft matter physics
• +۴ مورد دیگر

Zhang Jun is a Full Professor of Physics and Mathematics and Co-director of the Applied Math Lab at the Courant Institute, New York University (NYU), USA. He also serves as Co-director of the NYU-ECNU Joint Physics Research Institute in Shanghai, China, and holds an Affiliated Professorship at NYU Shanghai. His research focuses on experimental fluid physics, particularly fluid-structure interactions in biological and geophysical contexts, including bio-locomotion, flapping wings, and continental dynamics. Zhang has authored over 290 invited talks and peer-reviewed papers in journals like Nature and Physical Review Letters. He received the 2017 APS Fellow award for pioneering work in fluid-structure interactions. Beyond academia, he is a freelance illustrator with plans to publish a book of sketches. Education: PhD in Physics (1994), Niels Bohr Institute, University of Copenhagen PhD Candidate (1990-1991), Hebrew University of Jerusalem BSc in Physics (1985), Wuhan University Research Interests: Zhang’s work bridges physics, biology, and geophysics, exploring phenomena like flapping wing aerodynamics, animal locomotion, and Earth’s core-mantle interactions. His experiments often use novel fluid dynamics setups to model natural systems. Awards: APS Fellow (2017) Milton Van Dyke Award (2014) Antarctica Service Medal (2015) Labs & Teams: Co-directs the Courant Institute’s Applied Math Lab, specializing in fluid dynamics experiments. Collaborates with institutions globally, including NYU Shanghai and Aix-Marseille University.

• German Linguistics
• Language Didactics
• Language Variation
• +۴ مورد دیگر

Attila Németh is a Professor of German Linguistics and Language Didactics at the University of Teacher Education Upper Austria, affiliated with the Department of Languages, Literatures, and Cultures (German Studies). His academic trajectory includes extensive research in language variation, dialectology, and cross-cultural communication, with a geographical focus on Hungarian-German linguistic communities. Education: PhD in German Linguistics (Sociolinguistics/Dialectology) from the University of Szeged (2009) Doctoral studies in German Linguistics at the University of Szeged (2001–2004) Interpreter and Translator training at the University of Szeged (2000–2001) MA in Hungarian and German Studies at the University of Szeged (1995–2001) Research Focus: Németh's work investigates the interplay between language contact, sociolinguistic attitudes, and educational applications. Key areas include dialect preservation in minority communities, morphosyntactic complexity in bilingual contexts, and pedagogical strategies for grammar instruction. His research consistently addresses the dynamics of German dialects in Hungary, emphasizing textbook design and language policy implications. Publication Trends: His articles predominantly explore sociolinguistic and contact-linguistic phenomena, with recurring themes of language simplification, bilingual normativity, and dialect erosion. Methodologically, they blend empirical fieldwork with theoretical frameworks, often focusing on Hungarian-German communities to analyze broader patterns of language change and identity. Professional Activities: He co-edited the Zeitschrift für Mitteleuropäische Germanistik (2011–2016) and contributed to DAAD-supported projects like Intercultural Relations within and beyond Borders (2008–2009). Earlier roles include editorial work for academic journals and research coordination at the Pannonian University.