جست‌وجوی استاد و پژوهشگر

• Distributed Systems
• Mobile Edge Computing (MEC)
• Resource Management
• +۳ مورد دیگر

An Du is a Visiting Scientist at TU Wien's Distributed Systems research group (E194-02), affiliated with the Institute of Information Systems Engineering. His research focuses on Mobile Edge Computing (MEC), hierarchical collaborative computing frameworks, and resource management in distributed systems. He collaborates with Northeastern University, China, and has contributed to optimizing service placement and task scheduling in MEC environments. His work addresses challenges in real-time processing and resource allocation across cloud-edge-device hierarchies, aiming to minimize system costs while ensuring performance stability. Funded by grants from the National Natural Science Foundation of China and others, his research emphasizes long-term system efficiency and cross-node resource utilization. Key projects include the development of an online optimization framework for MEC systems, leveraging Lagrangian relaxation techniques to enhance computational efficiency. His findings have been published in IEEE Transactions on Services Computing and presented at international conferences.

• Distributed Systems
• Consensus Algorithms
• Dynamic Networks
• +۱ مورد دیگر

Stephan Felber is a PreDoc Researcher at the Embedded Computing Systems group (Institute E191-02) within the Faculty of Informatics at Vienna University of Technology, holding a Bachelor of Science and Diplom-Ingenieur degree. His research expertise spans: Distributed Systems Consensus Algorithms Dynamic Networks Fault Tolerance His recent publications demonstrate deep theoretical contributions to distributed computing, particularly analyzing consensus impossibility in lossy snapshot models and characterizing message adversaries in directed dynamic networks, establishing foundational limits for fault-tolerant distributed systems. At TU Wien, he teaches core computer engineering courses including Advanced Multiprocessor Programming (191.022, VU), Computer Engineering Practical (191.005, PR), and multiple project-based courses (191.006-191.009, PR). As an integral member of the Embedded Computing Systems research group, he advances theoretical frameworks for reliable distributed computation in challenging network environments.

• Asynchronous Logic
• Real-Time Systems
• VLSI Design
• +۳ مورد دیگر

Markus Ferringer is a Lecturer in the Department of Computer Engineering at Vienna University of Technology. He specializes in asynchronous logic, real-time systems, and fault-tolerant hardware design, with a focus on VLSI implementation and distributed systems. Research Interests: His work explores the integration of asynchronous circuits into real-time systems, emphasizing fault tolerance and reliability. Key areas include self-timed logic, time-triggered protocols, and distributed clock generation. Publications: Markus has published extensively on asynchronous hardware design, interfacing techniques, and process variation impacts. His research spans conferences and workshops such as DSN-W, DDECS, EUROCON, and Austrochip. Projects: He contributed to the ARTS project (2007–2011) supported by the Austrian Research Promotion Agency (FFG) and the THETA project (2004–2008).

• Theoretical Computer Science
• Algorithms
• Complexity Theory
• +۲ مورد دیگر

Alexander Firbas serves as a Researcher at the Institute of Logic and Computation within Vienna University of Technology's Faculty of Informatics, specializing in theoretical computer science with emphasis on graph algorithms and computational complexity. His academic background includes a Diploma Engineer (Dipl.-Ing.) and Bachelor of Science (BSc), with his 2023 Diploma Thesis establishing foundational work on vertex splitting for hereditary graph properties. Current doctoral research extends into parameterized complexity and geometric graph representations. Firbas investigates structural graph properties through computational lenses, focusing on tractability boundaries for problems involving vertex splitting, cluster modifications, and geometric thickness. His methodology integrates fine-grained complexity analysis with algorithmic design for NP-hard graph problems. Recent publications demonstrate consistent exploration of graph modification paradigms, evolving from hereditary property establishment (2023) to cluster vertex splitting (2024) and geometric thickness tractability (2025), reflecting deepening specialization in parameterized approaches to graph-theoretic challenges. He contributes to the multi-year 'Parameterized Graph Drawing' project (2023–2027) while teaching Algorithmic Geometry and Graph Algorithms seminars. His advising activities include supervising master's theses within the Algorithms and Complexity research framework. As an active member of the Algorithms and Complexity research group, Firbas collaborates on theoretical projects examining computational boundaries in graph theory, with ongoing work targeting degree-constrained spanning trees and geometric embedding problems.

• Human-Computer Interaction
• User Experience
• Interaction Design
• +۳ مورد دیگر

Ruadhan James Flynn is a PreDoc Researcher (Projektassistent) at the Vienna University of Technology , affiliated with the Faculty of Informatics and the Human-Computer Interaction department (E193-05). His research focuses on areas related to human-computer interaction, user experience, and usability engineering. Contact him at ruadhan.flynn@tuwien.ac.at .

Pantelis Frangoudisمشاهده پروفایل

پژوهشگر

• Mobile/Wireless Networking
• Edge Computing
• Network Softwarization
• +۴ مورد دیگر

Pantelis Frangoudis is a PostDoctoral Researcher at the Distributed Systems Group of the Vienna University of Technology since 2019. His academic journey includes a Ph.D. in Computer Science (2012), M.Sc. (2005), and B.Sc. (2003) from the Department of Informatics, Athens University of Economics and Business (AUEB) , Greece. His research spans Edge Computing , IoT , Network Softwarization , Federated Learning , and Wireless Networking , focusing on adaptive systems and security. Education B.Sc. in Computer Science (2003), AUEB M.Sc. in Computer Science (2005), AUEB Ph.D. in Computer Science (2012), AUEB His research explores Edge Computing Continuum systems, with emphasis on QoS-aware orchestration , serverless edge deployment , and self-adaptive IoT services . Recent work addresses federated learning for 6G , WebAssembly for edge serverless , and dynamic resource allocation in heterogeneous environments. Key projects include AloTwin (2023–2025), INTEND (2024–2026), and EDENSPACE (2019–2022). His publications (2025–2020) cover machine learning for 5G/6G , MEC application orchestration , and IoT security , with a focus on distributed systems and edge-cloud collaboration . Scientific Awards ERCIM Alain Bensoussan Post-Doctoral Fellowship He has supervised multiple diploma theses at TU Vienna, including topics like serverless edge computing , traffic light AI optimization , and vertical farming IoT systems . His collaborations with institutions like EURECOM (France) and IRISA/INRIA (France) reflect a global academic footprint.

• Virtual Reality
• Augmented Reality
• Haptics
• +۳ مورد دیگر

Mohammad Ghazanfari is a PreDoc Researcher at Vienna University of Technology (Vienna UT), affiliated with the School of Informatics. His work focuses on virtual and augmented reality systems, particularly encounter-type haptics, collaborative architectural design, and robotic interfaces. Current projects include the ACD (2020–2028) initiative, developing AR safety monitoring and stiffness simulation with origami-based haptic devices. Research intersects virtual reality, robotics, and human-centered design, with applications in architectural prototyping and immersive user experiences. His publications demonstrate expertise in haptics, reinforcement learning, and multi-agent systems. Recent articles emphasize walkable VR collaboration, tactile feedback optimization, and real-time safety protocols in mixed reality environments.

• Machine Learning
• Enterprise Architecture
• Conceptual Modeling
• +۳ مورد دیگر

Philipp-Lorenz Glaser is a PreDoc Researcher at the Department of Business Informatics, Technische Universität Wien. His research focuses on conceptual modeling, enterprise architecture, machine learning applications, and knowledge graph construction. Role: PreDoc Researcher (E194-03) Contact: philipp-lorenz.glaser@tuwien.ac.at His work explores methods for encoding semantic information in conceptual models to improve machine learning applications, with a focus on FAIR datasets and hybrid modeling approaches. Key themes include: Enterprise architecture modeling practices Graph-based data representation Integration of textual and graphical modeling Development of modeling tools (e.g., Sprotty-based solutions)

• Compilers
• Programming Languages
• Computer Architecture
• +۳ مورد دیگر

Benedikt Lukas Huber serves as a PreDoc Researcher at TU Wien's Faculty of Informatics within the Compilers and Languages research group (Institute E194-05), located at Argentinierstrasse 8, Room EA0402. His primary affiliation centers on compiler technologies and system architecture research. His research spans Compilers , Programming Languages , and Computer Architecture , with specialized focus on architecture description languages and compiler optimization techniques like software pipelining. Recent work demonstrates sustained innovation in formal system modeling and performance-critical code generation. Publication analysis reveals consistent contributions to compiler infrastructure, particularly through the Vienna Architecture Description Language (2024) and foundational software pipelining research (2008), highlighting expertise in bridging hardware constraints with high-level language design. No scientific awards or fellowships were documented in available sources. Information regarding student advising, research grants, or leadership roles remains unspecified beyond his core research group affiliation. He operates within TU Wien's Compilers and Languages research ecosystem, contributing to compiler design and system architecture initiatives under the Institute of Engineering Mathematics and Computing Science.

• Parameterized Complexity
• Graph Theory
• Computational Complexity
• +۳ مورد دیگر

Liana Khazaliya is a PreDoc Researcher in the Department of Algorithms and Complexity at Vienna University of Technology , specializing in parameterized complexity and graph theory. Her work intersects computational complexity, graph drawing, and structural decomposition techniques. Research Focus: Double-exponential lower bounds for NP problems, crossing number analysis, planar graph extensions, and metric dimension parameterizations Key Collaborations: Works with teams in computational geometry, graph drawing, and algorithmic research Her recent publications analyze algorithmic hardness through treewidth and vertex cover parameterizations, contributing to the understanding of complexity thresholds in graph problems. She actively participates in international conferences like SoCG, GD, and IPEC, advancing fixed-parameter tractability frameworks.

• Computer Science
• Network Security
• Malware Detection
• +۴ مورد دیگر

Engin Kirda is a researcher at the Department of Distributed Systems , Vienna University of Technology . His work focuses on Network Security , Malware Detection , and Web Security , with a particular emphasis on Malware Analysis , XSS Prevention , and Botnet Detection . He has led and contributed to projects such as WOMBAT , SECoverer , and SysSec , funded by entities like the Austrian Research Promotion Agency (FFG) and the European Commission . Research Areas : Network Security, Malware Analysis, Web Application Vulnerabilities Key Projects : WOMBAT (2008–2011), SECoverer (2008–2011), SysSec (2010–2014) His publications highlight advancements in automated malware analysis , phishing detection , and web spam mitigation . He has mentored students in topics including Android security , CSV Attack Prevention , and Malware Threat Landscapes .

Benedikt Lorchمشاهده پروفایل

پژوهشگر

• Steganography
• Multimedia Forensics
• Machine Learning
• +۳ مورد دیگر

Dr. Benedikt Lorch is a researcher currently affiliated with the Security and Privacy Lab at the University of Innsbruck, Austria. His professional journey includes roles as a Postdoctoral Fellow (2023–2024) and Research Assistant (2022–2023) at the same institution, preceded by research and academic roles at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Germany, including a Ph.D. in Computer Science (2018–2023) focused on cybercrime and forensic computing. He has also held visiting researcher positions at Dartmouth College (USA) and Imperial College London (UK). His research interests center on steganography, steganalysis, multimedia forensics, and machine learning applications in digital security. Notable work includes analyzing JPEG image directionality for security implications, improving steganalysis techniques using leaked cover thumbnails, and developing reliable machine learning models for forensic image analysis. His contributions address challenges in digital forensics, such as detecting image tampering, authenticating multimedia content, and enhancing degraded license plate recognition. Key academic awards include the ASQF award for outstanding studies (2019) and a DAAD scholarship for international research (2017). His work spans projects like UNCOVER and emphasizes compliance with regulations like the Artificial Intelligence Act in forensic analysis. Beyond technical contributions, Lorch has explored medical imaging applications, including motion artifact detection in MRI and heart rate estimation using wearable sensors. His research trends reflect a focus on leveraging probabilistic methods and deep learning to enhance forensic reliability, with a particular emphasis on JPEG-based steganalysis and digital image security. Collaborations with institutions like the Pattern Recognition Lab and Biomedical Image Analysis Group highlight interdisciplinary engagement in computer science and medical imaging.

Ricardo Baeza-Yatesمشاهده پروفایل

استاد

• Algorithms
• Responsible AI
• Web Search and Mining
• +۷ مورد دیگر

Ricardo Baeza-Yates serves as Director of Research at the Institute for Experiential AI at Northeastern University's Silicon Valley campus. He also maintains part-time professor positions at Universitat Pompeu Fabra in Barcelona and Universidad de Chile in Santiago. Previously, he was VP of Research at Yahoo Labs (2006-2016) and CTO of NTENT, a semantic search technology company. His academic career spans over three decades with significant contributions to both industry research and academia. Dr. Baeza-Yates earned his Ph.D. in Computer Science from the University of Waterloo, Canada, in 1989. His academic journey includes professorships at Universidad de Chile (1989-2004), ICREA Professor at Universitat Pompeu Fabra (2004-2005), and ongoing part-time appointments at both institutions since 2004 and 2006 respectively. His research spans algorithms, information retrieval, web search and mining, data science, with increasing emphasis on responsible AI and ethical considerations in technology. He is particularly renowned for his work on bias in search systems, algorithmic fairness, and the societal impacts of AI. His expertise uniquely bridges technical aspects of search and data mining with ethical and societal implications, making him a leading voice in the responsible AI movement globally. His recent scholarly output demonstrates a strong focus on bias detection, fairness metrics, responsible technology development, and the societal impacts of algorithms. The work spans technical machine learning and information retrieval while increasingly addressing ethical and social dimensions across diverse application areas from finance to healthcare to social media. Dr. Baeza-Yates has received numerous prestigious awards throughout his distinguished career: 2019 Corresponding Member of the Brazilian Academy of Sciences 2019 Award Salvà i Campillo to the Person of the Year 2018 National Research Award for applied research and technology transfer 2012 ASIS&T Best Information Science Book Award for Modern Information Retrieval 2011 IEEE Fellow for contributions to computer science development 2009 ACM Fellow for contributions to information retrieval algorithms 2002 Corresponding member Chilean Academy of Sciences As an educator and mentor, Dr. Baeza-Yates has advised numerous students throughout his academic career at multiple institutions. His textbook 'Modern Information Retrieval' has become a standard reference in the field, influencing generations of computer scientists. He has secured significant research funding through his leadership roles at Yahoo Labs and academic grants, demonstrating his ability to bridge theoretical research with practical applications. Dr. Baeza-Yates is actively involved with the DATA Lab at Northeastern University's Khoury College of Computer Sciences and previously founded the Web Science and Social Computing Research Group at Universitat Pompeu Fabra. He serves on multiple high-impact advisory boards including the Global AI Ethics Consortium, Global Partnership on AI, and IADB's fAIr LAC Initiative for Latin America and the Caribbean, reflecting his global influence in shaping responsible AI practices.

Petter E. Bjørstadمشاهده پروفایل

استاد

• Numerical analysis
• Domain decomposition
• Elliptic PDE
• +۴ مورد دیگر

Petter E. Bjørstad is a Professor of Computer Science and Mathematics at the University of Bergen, Norway, where he has served as Head of the Department of Informatics since 2010. Previously, he was Director of the Bergen Center for Computational Science (2000-2010) and Professor in both the Department of Mathematics (2006-2010) and Department of Informatics (1985-2005). He also held a position as Professor of Mathematics at the University of Minnesota during 1996-1997 on unpaid leave from Bergen. Dr. Bjørstad earned his PhD in Computer Science from Stanford University in 1980, following which he completed a postdoctoral fellowship at the Courant Institute of Mathematical Sciences at New York University. Before entering academia, he worked as a Principal Engineer at Det Norske Veritas from 1981-1985. Dr. Bjørstad's research focuses on numerical analysis and high-performance computing, with particular expertise in domain decomposition methods, parallel algorithms for elliptic partial differential equations, and scientific computing. His work bridges theoretical mathematics with practical computational challenges, especially in industrial applications. He has led significant research projects including 'Multiscale Domain Decomposition: Algorithms and Analysis' (2010-2014), funded by the Research Council of Norway and the University of Bergen. His publication record demonstrates consistent contributions to the field of numerical methods and parallel computing over several decades. The research trends show a strong focus on developing efficient algorithms for solving partial differential equations through domain decomposition techniques, with applications spanning structural analysis, reservoir simulation, semiconductor device modeling, and other industrial contexts. His work increasingly emphasizes practical implementation on modern parallel architectures including SIMD and MIMD systems. Large number of research grants from Norway and the European Union Dr. Bjørstad has been actively involved in mentoring students and collaborating with industry through projects like the Europort effort, where industrial codes were ported to parallel computing platforms. His laboratory for parallel computing (Parallab) has been instrumental in advancing practical applications of high-performance computing since its establishment in 1985 with Europe's first 64-processor Intel hypercube. The lab has evolved to include multiple MIMD machines including an Intel Paragon, Parsytec GC/Power-Plus, and DEC α-cluster. As Head of the Department of Informatics, Dr. Bjørstad leads one of Norway's premier computing research units with expertise spanning theoretical computer science, numerical methods, and practical applications in various scientific domains. His leadership has helped establish Bergen as a significant center for computational science in Europe.

Paola Bovolentaمشاهده پروفایل

استاد پژوهشی

• Developmental Neurobiology
• Neuroinflammation
• Neurodegeneration
• +۶ مورد دیگر

Paola Bovolenta is a Research Professor at the Spanish National Research Council (CSIC) - Universidad Autónoma de Madrid (UAM), with international recognition in Developmental Neurobiology. She has held leadership roles including Chair of the Tissue and Organ Homeostasis Program (2019–present) and former Chair of the Development and Differentiation Department (2012–2019). Her research spans: Mechanisms of visual axon sorting at the chiasm Morphogen signaling in eye development Neuroinflammation in Alzheimer's disease ADAM10-SFRP1 interactions in neurodegeneration Interdisciplinary approaches to life sciences Recent publications highlight her work on zebrafish models for optic cup morphogenesis, neuroinflammatory crosstalk in Alzheimer's, and synthetic biology applications. Awards include EMBO membership (2012), two Fundaluce Awards (2009, 2012), and ERC Scientific Council membership (2017). She has mentored 21 PhD students (4 ongoing) and 20 postdocs, with active involvement in European research policy through the ERC Open Science Working Group and UE Core Group on Reform of Research Assessment.