جست‌وجوی استاد و پژوهشگر

• Data Management
• Digital Preservation
• Machine Learning
• +۴ مورد دیگر

Andreas Rauber is an Associate Professor in the Department of Data Science at Technical University of Vienna. He serves as Curriculum Coordinator for Bachelor and Master programs in Business Informatics and Data Science, and chairs the Curriculum Commission for Business Informatics. His research focuses on Information Systems Engineering, Logic and Computation, and Visual Computing, addressing challenges in data management, digital preservation, and reproducibility in e-science. He leads projects like OS Trails and FAIR-AI, emphasizing FAIR principles and trustworthy research infrastructures. Rauber has contributed to over 150 publications, including works on data citation frameworks, adversarial ML defenses, and reproducibility in IR. His work bridges technical innovation with policy, exemplified through roles in the EOSC Support Office Austria and RDA Austria initiatives. Key projects include establishing FAIR data practices across universities and advancing digital preservation through repositories like DBRepo. He coordinates international collaborations, such as the EU-funded EOSC-Life and EGI Advanced Computing projects. His teaching spans courses in machine learning, information retrieval, and research methods, fostering next-generation data scientists.

Xu Dongمشاهده پروفایل

استاد

• Artificial Intelligence
• Computer Vision
• Multimedia
• +۳ مورد دیگر

Professor Dong Xu is a Tenured Professor in the Department of Computer Science at the University of Hong Kong (HKU), part of the School of Computing and Data Science. He holds a B.Eng. and Ph.D. from the University of Science and Technology of China (USTC). His career includes tenured roles at Nanyang Technological University and the University of Sydney, alongside postdoctoral research at Columbia University. His research focuses on Artificial Intelligence, Computer Vision, Multimedia, and Machine Learning , with applications in autonomous driving, AR/VR, medical image analysis, and video surveillance. Xu has authored over 150 papers in top journals and conferences, including CVPR, ICCV, and IEEE Transactions. He actively contributes to the academic community as an editorial board member for journals like ACM Computing Surveys and IEEE Transactions, and through leadership roles in conferences such as ACM Multimedia and ICME. Notable awards include Fellowships from IEEE and IAPR, and the IEEE Signal Processing Society Distinguished Lecturer title (2021–2022). Education: B.Eng. (USTC, 2001), Ph.D. (USTC, 2005) Professional Service: Program Coordinator of ACM Multimedia 2024, Guest Editor of over ten special issues.

• Legal Informatics
• Artificial Intelligence and Law
• Data Protection and Privacy
• +۵ مورد دیگر

Erich Schweighofer serves as Associate Professor at the University of Vienna within the Institute for European, International and Comparative Law, specifically affiliated with the Department of International Law and International Relations. His research activities are centered at the Juridicum building (Schottenbastei 10-16, 1010 Vienna), where he maintains an active office presence with scheduled consultation hours. His scholarly focus spans Legal Informatics , Artificial Intelligence and Law , Data Protection , and Legal Knowledge Representation , with particular emphasis on explainable AI systems for legal contexts and formal methodologies for translating legal norms into computational frameworks. This interdisciplinary work bridges jurisprudence and computer science through projects examining biometric regulation, autonomous vehicle governance, and natural language processing applications in legal domains. Analysis of his 2021-2024 publications reveals consistent thematic progression toward operationalizing legal principles in AI systems, with increasing focus on transparency mechanisms, temporal logic for dynamic regulations, and cross-jurisdictional compliance challenges. His work predominantly appears in the International Legal Informatics Symposium (IRIS) proceedings and JURIX conferences, reflecting deep engagement with the legal informatics community. Professor Schweighofer leads a dedicated research team including project assistants Mag. Jessica Fleisch, Mag. Jonas Pfister, Felix Schmautzer, and Mag. Jakob Zanol, while actively participating in the University of Vienna's Working Group on Legal Informatics (Arbeitsgruppe Rechtsinformatik). His collaborative approach extends to organizing the biennial IRIS symposium, which has established itself as a cornerstone event for European legal informatics scholarship since 1998.

• Machine Learning
• Statistical Computing
• Cluster Analysis
• +۲ مورد دیگر

Theresa Scharl-Hirsch is a Senior Scientist and Deputy Scientific Director at the Core Facility Bioinformatics, University of Natural Resources and Life Sciences, Vienna (BOKU). She holds concurrent appointments at the Institute of Statistics, BOKU, and has extensive experience in bioprocess modeling, machine learning, and statistical computing. Her work bridges biochemical engineering with advanced data science methodologies. Her research focuses on real-time monitoring of biopharmaceutical processes, clustering of high-dimensional data (particularly RNA sequencing), and application of explainable machine learning techniques. She has developed statistical models for process optimization and quality prediction in antibody capture and protein purification, with a strong emphasis on industrial implementations using R programming. Key trends in her publications include three-way data analysis, matrix-variate Gaussian mixture models, and permutation-based variable importance methods for deep learning architectures. Her work spans bioprocess engineering, bioinformatics, and industrial data science applications.

Jean Ponceمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Robotics
• +۳ مورد دیگر

Jean Ponce is a Professor of Computer Science at Ecole Normale Superieure (ENS) in Paris and a Part-Time Global Distinguished Professor at New York University's Courant Institute of Mathematical Sciences and Center for Data Science (CDS). He previously served as Director of the ENS Computer Science Department (2011-2017) and held positions at Inria (2017-2022), University of Illinois at Urbana-Champaign (1998-2006), MIT, Stanford, and Inria (1982-1985). Academic Leadership: Scientific Director of PRAIRIE Interdisciplinary AI Research Institute in Paris Startup Involvement: Co-founder and CEO of Enhance Lab (2022) Editorial Roles: Senior Editor-in-Chief of International Journal of Computer Vision (2019-2022) Conference Leadership: Chair of IEEE CVPR (1997,2000), ECCV (2008), and upcoming ICCV (2023) Research Focus: Computer vision, machine learning, robotics, and AI with applications in exoplanet imaging, 3D reconstruction, and image quality assessment. His work bridges statistical learning and deep learning approaches. Awards: IEEE Fellow (2003) ELLIS Fellow (2019) ERC Advanced Grant (2011) IEEE CVPR Longuet-Higgins Prizes (2016,2020) ICML Test-of-Time Award (2019) Patents & Publications: Co-author of influential textbook Computer Vision: A Modern Approach (translated into Chinese, Japanese, Russian). Holds two US patents and one pending French patent. Google Scholar h-index of 78 with over 55,000 citations.

• Neurosymbolic AI
• Answer Set Programming
• Visual Question Answering
• +۳ مورد دیگر

Nelson Nicolas Higuera Ruiz is a PreDoc Researcher at the Vienna University of Technology, affiliated with the Faculty of Informatics' Knowledge-Based Systems research group. His work bridges logic programming and deep learning for explainable AI. Research Focus: Neurosymbolic AI, Visual Question Answering (VQA), Answer Set Programming (ASP), and hybrid reasoning systems Projects: Leads optimization research in the LCS (2017–2025) project, developing neurosymbolic approaches for intelligent systems Key Contributions: Pioneering adaptive large-neighbourhood search algorithms for ASP optimization, modular neurosymbolic architectures, and contrastive explainability frameworks for VQA Collaborations: Active in international workshops and conferences including IJCAI, AAAI, and CLeaR, frequently collaborating with researchers like Thomas Eiter and Johannes Oetsch Publications: Focus on neurosymbolic integration, optimization algorithms, and explainability across AI, logic programming, and computer vision domains

Fajar Juang Ekaputraمشاهده پروفایل

عضو هیئت علمی

• Semantic Web
• Knowledge Graphs
• Neurosymbolic AI
• +۴ مورد دیگر

Fajar Juang Ekaputra is a Tenure Track Assistant Professor at the Institute of Data, Process, and Knowledge Management (DPKM), WU Vienna and a part-time Postdoctoral Researcher at the Data Science research unit, TU Wien . With a focus on Semantic Web , Knowledge Graphs , and their integration with Machine Learning in Neurosymbolic AI systems, his work spans domains like Cyber-Physical Systems and Materials Engineering . Education: Dr.techn. (2018), TU Wien M.T. (2010) and S.T. (2008), Institute Teknologi Bandung (ITB) Research Interests center on hybrid AI systems combining Semantic Web and Machine Learning , with applications in Cyber-Physical Systems (e.g., smart grids, smart buildings), data privacy in smart cities, and materials engineering . His 102+ publications include frameworks like SWeMLS-KG and SHACL4Protege . Recent Articles (2024) address explainable AI in cyber-physical systems, privacy trust in data infrastructures, and neurosymbolic frameworks . Earlier works (2023–2022) explore ontology-based data management , auditable AI , and hybrid system architectures . Scientific Awards: Best Paper Awards (ICoDSE 2023, ICoDSE 2016) Best Poster Nomination (SEMANTiCS 2019) PhD Scholarship (Austria’s Agency for Education and Internationalisation, 2012) Advising includes supervising PhD students (e.g., Majlinda Llugiqi, Katrin Schreiberhuber) and master’s theses on topics like knowledge graph characteristics and data quality assessment . He leads projects such as FAIR-AI (FFG-funded, 2024–2026) and SENSE (Horizon Europe, 2023–2025).

• Brain-Computer Interface
• Biomedical Engineering
• Neuroprosthetics
• +۵ مورد دیگر

Prof. Dr. Gernot R. Müller-Putz is Head of the Institute of Neural Engineering and the Graz Brain-Computer Interface Lab at Graz University of Technology. He serves as Dean of the Faculty of Computer Science & Biomedical Engineering and holds editorial roles at Frontiers in Human Neuroscience IEEE Transactions in Biomedical Engineering Brain-Computer Interface Journal . With over 212 peer-reviewed publications and an h-index of 80, his research focuses on Brain-Computer Interfaces , Neuroprosthetics , and EEG-based Motor Control . His work investigates: Neural signal decoding for spinal cord injury rehabilitation Hybrid BCI systems with error processing Artificial sensory feedback mechanisms Machine learning applications in neural engineering VR-based neurofeedback environments Non-invasive multimodal biosignal recording Research trends show strong emphasis on EEG signal processing , BCI clinical applications , and neurotechnology integration . Scientific Awards : ERC Consolidator Grant (2015) Ludwig-Guttman Award (2017) CYBATHLON Best Paper (2019) State of Styria Research Award (2019) Förderstipendium (2013-2014) He advises 21 PhD students and has managed major projects like MoreGrasp (EU Horizon 2020) , Feel Your Reach (ERC) , and INTRECOM (EU EIC Pathfinder) . The Institute hosts the BCI Racing Team Mirage91 and offers international thesis opportunities.

Wolfgang Nejdlمشاهده پروفایل

استاد

• Search and information retrieval
• Information systems and databases
• Semantic Web and Web 2.0
• +۴ مورد دیگر

Wolfgang Nejdl is a Full Professor of Computer Science at Leibniz Universität Hannover since 1995 and the Head of the L3S Research Center since 2001. His research focuses on Web Science, search and information retrieval, semantic web technologies, peer-to-peer infrastructures, databases, technology-enhanced learning, and artificial intelligence. Education: M.Sc. (1984) and Ph.D. (1988) in Computer Science from Vienna University of Technology. Previous Positions: Assistant Professor in Vienna (1988–1992), Associate Professor at RWTH Aachen (1992–1995), and visiting professor/researcher at Xerox PARC, Stanford, University of Illinois at Urbana-Champaign, EPFL Lausanne, and PUC Rio. His research spans foundational and applied Web technologies, including social networks, trust and reputation, Web infrastructure, digital libraries, semantic web, collaborative filtering, and privacy-preserving systems. Recent projects like PHAROS, OKKAM, LiWA, and LivingKnowledge highlight his work in audio-visual search, web entities, web archive management, and diversity bias algorithms. Wolfgang Nejdl published over 230 scientific articles and held leadership roles as General Chair for AH'08 and PC Chair for WWW'09. He co-founded iSearch IT Solutions in 2006 to commercialize digital library and web engineering research from L3S projects. Scientific Awards: Founding member and head of the L3S Research Center The L3S Research Center, with a 2009 budget of €6 million (75% third-party funding), focuses on connecting the Web to real-world entities through research in Web Science, service computing, and security. Funding comes equally from the European Union and national/industry sources.

Michal Piovarciمشاهده پروفایل

پژوهشگر

• Computer Graphics
• Computational Fabrication
• Haptic Reproduction
• +۳ مورد دیگر

Michal Piovarci is a Researcher (Postdoc) at ETH Zurich's Computational Design Lab led by Bernd Bickel. He holds a Ph.D. from USI Lugano (2020) under Piotr Didyk, receiving the Eurographics PhD Award for his thesis on Perception-Aware Computational Fabrication. His research focuses on computer graphics, computational fabrication, and haptic/appearance reproduction, emphasizing perception-driven solutions. Education: Ph.D., USI Lugano (2020) Previous postdoc at ISTA's Visual Computing Group Research interests include 3D Printing Innovations Haptic Feedback Systems Material Perception Modeling Directional Surface Design Professional Activities: Area chair at ACM Symposium on Computational Fabrication (2024), program committee roles at SIGGRAPH, SAP, and Eurographics. Organized Computational Fabrication Seminars (2021-2022). Grants: SNSF Project Funding (CHF 1M, 2025-2029) and FWF Lise Meitner Grant (2022-2023). Teaching: Taught Scientific Machine Learning for Design (ETH Zurich, 2024) Computational Fabrication (TU Wien, 2022)

• Electrical Engineering
• Computer Science
• Information Technology
• +۳ مورد دیگر

Bernhard Rinner is a Professor at the Institute of Networked and Embedded Systems within the Faculty of Technical Sciences at Alpen-Adria-Universität Klagenfurt. He is a member of the university Senate and serves as Prodekan (Deputy Dean). His research spans robotics, embedded systems, sensor networks, and privacy-aware computing , with a focus on resource-efficient designs for drones, autonomous systems, and IoT applications. Email: Bernhard.Rinner@aau.at Phone: +43 463 2700 3671 Office: B02.1.62, Lakesidepark Haus B02, Klagenfurt, Austria Research Interests include: Self-aware autonomous systems for adaptive mission planning and anomaly detection Resource-efficient embedded AI for drones and camera networks Secure IoT applications with privacy-preserving visual data processing Multi-agent coordination in confined environments and 3D navigation Dynamic sensor calibration for low-cost wireless networks Publications reflect trends in drone networks, self-aware computing, and privacy-aware sensing , emphasizing lightweight architectures, distributed coordination, and energy-efficient designs. Many recent works focus on binary neural networks, decentralized re-identification, and adaptive sensor reconfiguration .

• Cyber-Physical Systems
• Machine Learning
• Autonomous Systems
• +۵ مورد دیگر

Radu Grosu is a Professor at Technische Universität Wien (TU Wien), leading the Forschungsbereich Cyber-Physical Systems . His research focuses on Cyber-Physical Systems (CPS), Machine Learning, and autonomous robotics, with notable contributions to neural network architectures like Liquid Time-Constant Networks (LTC) and their applications in robotics and medical imaging. He is affiliated with the Network Lab and has supervised numerous PhD and Master's students, including Sebastian Michael Bittner, Daniel Scheuchenstuhl, and Sophie Neubauer. His work spans topics such as reinforcement learning, autonomous driving, and IoT ecosystems. Recent projects include developing robust AI systems for healthcare and robotics, such as tumor delineation using PET imaging and neuromorphic IoT architectures for smart villages. Grosu has published extensively on CPS, with over 146 contributions across peer-reviewed journals and conferences. His research emphasizes bridging theory and practice, addressing challenges in safety, scalability, and real-time control in autonomous systems. Key research interests include robotic perception, neural network robustness, and CPS/IoT integration. He has pioneered methods like DeepSTL for translating temporal logic requirements into neural network training objectives and developed frameworks like NimbleAI for neuromorphic sensing-processing systems. His team also explores distributed control algorithms for multi-agent systems, such as flocking drones and formation control using relative distance measurements. Recent work examines the generalization properties of deep filters in CNNs and quantum-classical reinforcement learning models for game AI. Grosu has advised over 20 students on topics ranging from deep learning in wafer defect analysis to bio-inspired neural circuits for auditable autonomy. His lab collaborates on interdisciplinary projects, such as applying AI to battery health estimation and prostate cancer diagnostics. He actively contributes to academic communities, editing special issues on AI in healthcare and CPS resilience, and has organized summer schools on CPS and IoT systems.

Cezary Kaliszykمشاهده پروفایل

استاد

• Theoretical Computer Science
• Automated Reasoning
• Formal Methods
• +۱۳ مورد دیگر

Cezary Kaliszyk is a Professor in Theoretical Computer Science at the University of Melbourne. His research focuses on automated reasoning, formal methods, and learning for reasoning, particularly in the context of interactive theorem proving and formalized mathematics. He leads the ERC project 'FormalWeb3' and has been involved in several other significant research initiatives. Theoretical Computer Science Automated Reasoning Formal Methods Interactive Theorem Proving Machine Learning for Theorem Proving Formalized Mathematics Proof Guidance Learning for Reasoning His research explores the integration of machine learning techniques with formal reasoning systems to enhance automation in theorem proving. This includes developing systems like CoqHammer and Tactician, advancing premise selection, proof guidance, and learning-based proof search strategies. His work bridges logical foundations with practical AI-driven tools for formal verification. The recent publications demonstrate a consistent focus on advancing automated and interactive theorem proving through learning techniques, formalization of mathematical concepts (like surreal numbers), and improving reasoning systems (e.g., Prover9, tableaux methods). There is a strong emphasis on practical system development, formalization projects, and learning-based enhancements to reasoning. ERC project 'FormalWeb3' - Principal Investigator Cost Action EuroProofNet - WG5 Leader until 2024 FWF project P26201 - developing HOL(y)Hammer Other projects: JSPS P10044, NWO MathWiki, SURF WebDed, ProofWeb He has advised several PhD students to completion, including Michael Färber, Thibault Gauthier, Yutaka Nagashima, Stanisław Purgał, and Liao Zhang, and is currently supervising Daniel Ranalter and Neil Vyas. He has not received any explicitly mentioned scientific awards in the provided text. His work involves leadership in collaborative systems such as ProofWeb and HOL Import, and participation in major formalization efforts including the Mizar library integration with Isabelle. He is actively involved in the development of tool ecosystems for formal mathematics and automated reasoning.

Werner Goeblمشاهده پروفایل

استاد

• Music Acoustics
• Piano Performance
• Ensemble Synchronization
• +۳ مورد دیگر

Werner Goebl is a Professor of Music Acoustics and Head of the Department of Music Acoustics – Wiener Klangstil (IWK) at the University of Music and Performing Arts Vienna (mdw) in Vienna, Austria. He leads research in music performance science, acoustics, and technology, with a particular focus on piano performance mechanics and ensemble coordination dynamics. His research spans multiple interconnected domains: Music Acoustics and the 'Wiener Klangstil' (Viennese Sound Style) Piano performance techniques and finger movement efficiency Ensemble synchronization and coordination in musical groups Motion capture analysis of musical performance Digital musicology and music encoding standards Human-computer interaction in music performance Recent publications reveal a strategic shift toward digital musicology and web-based tools for music analysis, particularly through the mei-friend project for Music Encoding Initiative (MEI). His work increasingly combines traditional music acoustics with cutting-edge digital humanities approaches, focusing on ensemble coordination, body motion in performance, and creating accessible digital resources for music scholarship. The TROMPA project (Towards Richer Online Music Public-domain Archives) represents a major European collaboration to enhance access to music resources. Dr. Goebl's research has been supported by significant funding including: Austrian Science Fund (FWF) projects including 'Achieving Togetherness in Ensemble Performance' (P32642, 2020-2023) H2020 Research and Innovation Action 'TROMPA' with a budget over 3M€ (2018-2021) Multiple previous FWF projects on ensemble synchronization and piano performance Erwin-Schrödinger Fellowship at McGill University (2006-2008) He leads the Department of Music Acoustics – Wiener Klangstil (IWK) which houses several specialized laboratories: Acoustic Laboratory with anechoic room Slow Motion Lab Performance Science Lab CEUS Computer Wing with Motion Capture and Eye tracking network

Marko Tkalčičمشاهده پروفایل

استاد

• Recommender Systems
• Computational Psychology
• User Modeling
• +۷ مورد دیگر

Marko Tkalčič is a Full Professor at the Faculty of Mathematics, Natural Sciences and Information Technologies (FAMNIT) at the University of Primorska in Koper, Slovenia. He is affiliated with the Department of Information Sciences and Technologies and leads research in psychologically-informed recommender systems through the HICUP lab. His academic journey includes prior roles as Associate Professor and Assistant Professor at the Free University of Bozen-Bolzano, and postdoctoral work at Johannes Kepler University and the University of Ljubljana. Research interests include computational psychology, user modeling, personality and emotion modeling, affective computing, and bias mitigation in AI. His work integrates machine learning, data mining, and user studies to enhance personalization systems by incorporating cognitive and emotional models. He focuses on music and film domains, with applications in social media, automotive interfaces, and multimedia. The recent publications demonstrate a strong trend toward human-centric AI , exploring eudaimonic and hedonic user experiences, cognitive load in driver assistance, music relistening behavior, privacy in group recommendations, and emotion-based video and music prediction. His research increasingly blends cognitive science theories (e.g., ACT-R) with practical recommender system design. University of Primorska Golden Plaque Award (2024) Stanford List of Top Scientists Cited Worldwide Best Reviewer Award at ISMIR 2020 Italian National Habilitation for Full Professor (2020) Italian National Habilitation for Associate Professor (2017) He actively supervises PhD students, including Elham Motamedi, and has secured teaching and research roles within his team. He is a member of the editorial board for UMUAI and Frontiers in Psychology, and has co-edited books and special issues on group recommender systems and human-centered AI. He leads the HICUP lab, fostering interdisciplinary research at the intersection of psychology and computer science.