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Katja HoseView profile

Professor

• Knowledge Graphs
• Semantic Web
• Data Management
• +7 more

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.

• Data Visualization
• Human-Computer Interaction
• Big Data Analytics
• +13 more

Huamin Qu is a Chair Professor in the Department of Computer Science and Engineering at the Hong Kong University of Science and Technology (HKUST). He serves as the Founding Dean of the Academy of Interdisciplinary Studies (AIS), Founding Head of the Division of Emerging Interdisciplinary Areas (EMIA), and was the Founding Acting Head of Computational Media and Arts (CMA) at HKUST(GZ). Qu directs the VisLab and coordinates the Human-Computer Interaction (HCI) group. He obtained his BS in Mathematics from Xi'an Jiaotong University and MS/PhD in Computer Science from Stony Brook University. Qu's research integrates Data Visualization , Human-Computer Interaction , and Human-Centered AI , with applications in urban informatics, social networks, and explainable AI. His work focuses on developing interactive systems for big data analytics, visual storytelling, and AI-driven decision support. Research extends to multimodal communication, fintech, and augmented reality applications. His publications emphasize visual analytics for complex datasets (mobility, social media, financial), interaction techniques for immersive environments, and AI-enhanced visualization tools. Recent works explore explainable AI interfaces and large-scale data communication frameworks. IEEE Visualization Academy (2020) IEEE VGTC Technical Achievement Award AI 2000 Most Influential Scholar (2019, 2023, 2024) 21 Best Paper/Honorable Mention awards IBM Faculty Award (2009) APICTA Merit Award (2015) Yelp Dataset Grand Prize (2018) Qu has advised 48 PhD graduates (21 now faculty at institutions like UC Davis, University of Minnesota, Texas A&M) and 30 MPhil students. He secured major grants including RGC theme-based projects (digital citizenship, air pollution), UGC AoE (slope safety), and China's 973 Program. As VisLab director, he leads 20+ researchers in visualization/HCI projects adopted by Microsoft, IBM, Huawei, and Tencent.

Cao JiannongView profile

Academic

• Cloud and edge computing
• Parallel and distributed computing
• Big data analytics
• +2 more

Cao Jiannong is currently a Chair Professor and Director of the University Research Facility in Big Data Analytics at Hong Kong Polytechnic University . He has held academic roles including Assistant Professor at City University of Hong Kong and University Lecturer at the University of Adelaide and James Cook University. His research spans Cloud and Edge Computing , Parallel and Distributed Systems , Big Data Analytics , and Wireless Sensing . Ph.D. in Computer Science, Washington State University (1990) MSc in Computer Science, Washington State University (1986) BSc in Computer Science, Nanjing University, China (1982) His work focuses on solving theoretical and practical challenges in distributed computing , mobile cloud systems , and wireless sensor networks . Recent projects include coupled network embedding models for heterogeneous networks and SDN architectures for vehicular communication. His research also pioneers WiFi-based non-invasive health monitoring and fault-tolerant sensor deployment for structural health applications. Dr. Cao's publications highlight advancements in network embedding , edge computing , and WSN optimization . Key papers address multi-user computation partitioning , energy-efficient SHM systems , and consensus protocols for mobile networks. These works have been cited over 15,000 times, with an h-index of 60. Ministry of Education (China) Natural Science Award (2018) Distinguished Member, ACM (2017) Fellow, IEEE (2014) Best Paper Awards at IEEE DSAA, SMARTCOMP, and WCNC Dr. Cao has advised multiple PhD students, including Linchuan Xu and Weigang Wu , whose research on WSN-based SHM and coupled network embedding has practical impact. His leadership includes directing Hong Kong Polytechnic University's Big Data Research Facility and serving on technical committees for IEEE INFOCOM and ACM/IEEE conferences.

Peter DruschelView profile

Professor

• Distributed Systems
• Operating Systems
• Network Security
• +3 more

Peter Druschel is a Professor and founding Director of the Max Planck Institute for Software Systems (MPI-SWS) in Saarbrücken, Germany. He holds adjunct professorships at Saarland University and the University of Maryland. His research focuses on distributed systems, operating systems, and privacy-preserving technologies. He earned his Ph.D. from the University of Arizona in 1994 and has held roles at Rice University since 1994, including Professor of Computer Science (2002–2005). Education: Ph.D. in Computer Science, University of Arizona (1994) Research Interests: Distributed systems, operating systems, network security, accountable computing, and privacy technologies. Current projects include privacy compliance in data systems (Thoth), secure communication (EbN), and privacy-aware image capture (I-Pic). Awards: SIGOPS Mark Weiser Award (2008) NSF CAREER Award (1995) Member of Academia Europaea and German Academy of Sciences Leopoldina Grants & Leadership: Leads the ERC Synergy Project imPACT, chairs the Max Planck Society’s Chemistry, Physics, and Technology Section, and collaborates with institutions like Cornell and Google. Advises on policy issues related to technology and privacy. Labs/Teams: Distributed Systems Group at MPI-SWS, collaborations with Microsoft Research and MIT. Current team includes students and postdocs working on privacy, security, and distributed systems.

• Data Visualization
• Visual Data Analysis
• Data Science
• +3 more

Univ.-Prof. Torsten Möller, PhD is a Professor at the University of Vienna and serves as Head of the Research Group Visualization and Data Analysis and Head of the Research Network Data Science. His work spans data visualization, visual analytics, and human-computer interaction, with a focus on biomedical, environmental, and societal data applications. Academic rank: Professor Research group: Visualization and Data Analysis Network: Data Science Email: torsten.moeller@univie.ac.at Research interests include: Visual data analysis for complex systems Interdisciplinary applications in climate science and medicine Human-computer interaction in data exploration Image processing and computer graphics Recent publication trends show expertise in: Visualizing climate change and pandemic data Multi-volumetric and network analysis Algorithmic transparency and user-centered design Interdisciplinary collaborations (e.g., astrophysics, medical imaging) Statistical and uncertainty visualization Design frameworks for visualization recommendation Teaching includes courses in: Computer graphics and visualization Image processing and analysis Human-computer interaction Data analysis projects Doctoral research seminars

• Computer Vision
• Autonomous Driving
• Robotics
• +7 more

Dominik Schörkhuber is a PreDoc Researcher at the Vienna University of Technology (TU Wien) in the Computer Vision department. With a background in Informatics (BSc, Dipl.-Ing.), he focuses on computer vision applications for autonomous driving, robotics, and human-machine interaction. His work spans driver action recognition, pedestrian prediction, and adaptive lighting systems. Current projects: Empathic Vehicle (2024–2026), SyntheticCabin (2021–2025), SmartProtect (2020–2025) Research themes: Video transformers, synthetic data transfer learning, multi-task learning, and sensor-lighting integration Specializes in 3D sensing, nighttime driving analysis, and mobile video creation tools

Jiannong CaoView profile

Professor

• Cloud and edge computing
• Parallel and distributed computing
• Big data analytics
• +2 more

Jiannong Cao is a Chair Professor and Director of the University Research Facility in Big Data Analytics at the Department of Computing, Hong Kong Polytechnic University. He has held various academic roles since 1990, including Assistant Professor at City University of Hong Kong and Lecturer at Australian universities. PhD in Computer Science, Washington State University (1990) MSc in Computer Science, Washington State University (1986) BSc in Computer Science, Nanjing University (1982) His research focuses on cloud and edge computing , parallel and distributed computing , and mobile computing , with significant contributions to wireless sensor networks (WSN) for structural health monitoring (SHM) and software-defined networking (SDN) for vehicular communications. Recent work includes WiFi-based non-invasive health monitoring systems and multi-user computation partitioning in mobile cloud environments. Dr. Cao’s publications demonstrate trends in WSN optimization , SDN architectures , and cognitive modeling for network embedding , with applications in smart healthcare , transportation systems , and industrial IoT . Ministry of Education Natural Science Award (2018) ACM Distinguished Member (2017) IEEE Fellow (2014) Best Paper Awards at IEEE DSAA, SMARTCOMP, WCNC He has mentored numerous researchers, including Linchuan Xu , Xuefeng Liu , and Weigang Wu , who have authored key publications in top venues like ACM WSDM and IEEE INFOCOM . His professional roles include chairing IEEE committees and serving on grant panels for the Hong Kong Research Grant Council.

Alan BovikView profile

Professor

• Image quality
• Video compression
• Streaming video
• +7 more

Alan Bovik is the Cockrell Family Regents Endowed Chair Professor in the Department of Electrical and Computer Engineering at The University of Texas at Austin's Cockrell School of Engineering. He also holds positions at The Institute for Neurosciences and serves as Director of the Laboratory for Image and Video Engineering (LIVE). With a career spanning over three decades at UT Austin, he has progressed from Assistant Professor (1984-1988) to Associate Professor (1988-1994) to his current position as Full Professor (1994-present). Dr. Bovik received his Ph.D. in Electrical and Computer Engineering in 1984 from the University of Illinois, Urbana-Champaign. Professor Bovik's research focuses on image and video quality assessment, visual perception, and digital media processing. He is renowned for developing groundbreaking algorithms including the Structural Similarity (SSIM) index, Visual Information Fidelity (VIF), and various blind quality assessment models like BRISQUE and NIQE. His work bridges engineering and neuroscience, creating perception-based models that optimize visual media delivery while reducing bandwidth consumption. These innovations have had profound industry impact, with his algorithms processing a significant proportion of global internet video traffic. His recent publications demonstrate continued leadership in perceptual quality assessment, with increasing focus on AI-generated content, high dynamic range (HDR) video, and novel applications in medical imaging. The research shows a clear trajectory toward more sophisticated, neural network-based quality metrics that better align with human visual perception across diverse content types. Professor Bovik has received numerous prestigious awards recognizing his contributions to the field: John Fritz Medal (2024) IEEE Edison Medal (2022) IAMB BaM Award (2022) Elected to the United States National Academy of Engineering (2022) Technology and Engineering Emmy Award (2021) IEEE Fourier Award for Signal Processing (2019) Progress Medal from The Royal Photographic Society (2019) Named Honorary Fellow of The Royal Photographic Society (2019) Primetime Emmy Award (2015) Edwin H. Land Medal from The Optical Society (2017) As Director of the Laboratory for Image and Video Engineering (LIVE), Professor Bovik has secured substantial research funding from organizations including the National Science Foundation and the National Institute for Standards and Technologies. His lab has produced numerous influential datasets including the LIVE Image and Video Quality Databases. He has mentored many successful students who have gone on to make significant contributions in academia and industry, though specific student names are not provided in the source materials. The Laboratory for Image and Video Engineering (LIVE) under Professor Bovik's direction has become a world-renowned center for research in perceptual image and video quality. The lab maintains close collaborations with major technology companies including Netflix, Amazon, and YouTube, ensuring that research has direct practical applications. LIVE has developed numerous influential tools and databases that are widely used in both academic research and industrial applications worldwide.

• Temporal aspects in NLP/IR
• Digital Humanities
• Large Language Models
• +5 more

Adam Jatowt is a Professor and Head of the Data Science group at the Department of Computer Science, University of Innsbruck. He also serves as Deputy Head of the Digital Science Center and Research Center for Digital Humanities. His academic career spans roles at Kyoto University (2010-2020), National Institute of Advanced Industrial Science and Technology (AIST), and visiting positions at Karlsruhe Institute of Technology, University of La Rochelle, and University of California Berkeley. Research interests focus on temporal aspects of NLP/IR, computational history, large language models, and future forecasting. He leads projects combining digital humanities with advanced AI techniques, including temporal validity assessment and hint generation systems. Recent publications (2025) emphasize LLM applications in temporal analysis, QA systems, and energy sector digitalization. His work has been recognized through awards like the Friedrich Wilhelm Bessel Research Award (2024) and top-cited paper distinction in Information Sciences. He actively organizes conferences like ECIR 2026 and Text2Story workshops. Key contributions include developing WikiHint dataset, PlausibleQA framework, and tools like Rankify. His research also addresses societal challenges through ESG rating prediction and medical LLM applications.

Hui PanView profile

Professor

• Networking
• Complex networks
• Mobile computing
• +3 more

Hui Pan is a distinguished academic holding dual positions as Nokia Chair in Data Science and Professor of Computer Science at the University of Helsinki, and Chair Professor of Computational Media and Arts at the Hong Kong University of Science and Technology (HKUST). His research spans networking, mobile computing, augmented reality, and computational social science. He earned his Ph.D. in Computer Science from the University of Cambridge in 2007. His work bridges social networks with mobile systems, pioneering fields like mobile social networks and opportunistic forwarding algorithms. Research interests include data science, complex networks, and innovative applications of augmented reality. His recent publications focus on low-latency AR frameworks, blockchain for computation offloading, and mobile web visualization. He has received prestigious awards, including IEEE Fellow (2018), ACM Distinguished Scientist (2016), and the Nokia Chair Endowment (2017). He has supervised over 15 PhD and 12 MPhil graduates, with 13 current Ph.D. students and 2 MPhil students. His editorial roles include Associate Editorships at IEEE Transactions journals and guest editorships at top venues like IEEE JSAC and ACM Transactions. He has organized conferences such as WWW Track Chair and ExtremeCom General Chair.

Markus VinczeView profile

Associate Professor

• Robotics
• Computer Vision
• Human-Robot Interaction
• +5 more

Markus Vincze is an Associate Professor at the Institute of Automation and Control Engineering (ACIN) at Vienna University of Technology (TU Wien). He founded the Vision for Robotics (V4R) group in 1996 to advance robotic perception, particularly in real-world environments and homes. His work focuses on cognitive computer vision techniques for robotics. Education: Diplom in Mechanical Engineering (1988) and PhD (1993) from TU Wien; M.Sc. (1990) from Rensselaer Polytechnic Institute. V4R coordinates EU projects like ActIPret, robots@home, HOBBIT, and national initiatives like vision@home. Markus has edited a book on Robust Vision with Gregory Hager and authored 62 peer-reviewed journal articles and over 400 reviewed publications. His recent research explores zero-shot 6D pose estimation, sim-to-real transfer, and transparent object detection. Markus has served as program chair for ICRA 2013 and organized HRI 2017 in Vienna. He has advised numerous students and secured grants from the Austrian Academy of Sciences for work at HelpMate Robotics and Yale's Vision Laboratory. The V4R group leads innovations in robotic vision, including frameworks for synthetic data generation (Unrealgensyn), depth completion (CAGT), and educational robotics applications for sustainability. Their work spans household robotics (RH3), agricultural robotics (EdgeSoil), and human-robot collaboration.

Sun MaosongView profile

Professor

• Natural Language Processing
• Artificial Intelligence
• Machine Learning
• +5 more

Prof. Maosong Sun is a Professor at the Department of Computer Science and Technology, Tsinghua University, China. He holds additional leadership roles including Executive Vice Dean of the Institute for Artificial Intelligence and Deputy Director of the National Engineering Laboratory for Cyberlearning and Intelligent Technology. His research focuses on natural language processing (NLP), artificial intelligence, machine learning, and computational education. He leads interdisciplinary projects in computational humanities, knowledge graphs, and MOOC platforms like XuetangX, which has over 58.8 million registered learners. Key contributions include pioneering work in Chinese NLP tools, poetry generation systems like Jiuge, and large-scale research initiatives funded by Chinese and Singaporean programs. Awards include the Tsinghua University Education Award (2019) and the National Outstanding Practitioner Award (2007). Established NLP and Computational Humanities & Social Sciences Lab (2008) Co-director of the Joint Research Center for Extreme Search (2011-present) Over 200 publications with 11,000+ citations (h-index 47)

Senad BećirovićView profile

Professor

• Artificial Intelligence in Education
• Digital Technologies in Education
• Intercultural Education
• +3 more

Senad Bećirović serves as a full Professor at the University of Education Lower Austria (Pädagogische Hochschule Niederösterreich), having progressed from assistant professor (2014) to associate professor (2017) before attaining his current rank in 2023. His academic career spans teaching research methodology, pedagogy, and advanced statistics across undergraduate, graduate, and doctoral programs at international institutions, delivered through both online and in-person formats. Bećirović's research focuses primarily on Artificial Intelligence and digital technologies in education , with significant contributions to intercultural education , gifted education , and foreign language pedagogy . His work demonstrates a consistent trajectory toward understanding how emerging technologies reshape educational practices and outcomes. Through four books published by Springer and Nova Science and over 60 articles in top-tier journals, he has established himself as a leading voice in digital educational transformation. His recent publications (2023-2025) reveal a pronounced emphasis on AI applications in education, with multiple studies examining AI literacy, policy frameworks, and implementation strategies across European higher education contexts. This research demonstrates both theoretical depth and practical relevance to current educational challenges. Bećirović actively contributes to the scholarly community as editor and reviewer for numerous Q1 journals including Smart Learning Environments (Springer), Education and Information Technologies (Springer), and TESOL Quarterly (Wiley). He participates in multiple European Commission-funded initiatives such as ENRICH (Enhancing Teaching and Research through Innovative Digital Technologies) and Erasmus+ projects focused on peace learning and English education. His professional activities extend to international collaboration through membership in the European Network Ethical Use of AI and the American Educational Research Association (AERA). He frequently delivers keynote addresses at international conferences, sharing expertise on AI in education, digital transformation, and intercultural competencies.

• Software Engineering
• Computer Supported Cooperative Work (CSCW)
• Human-Computer Interaction (HCI)
• +5 more

Hilda Tellioglu is an Associate Professor and Dean of Academic Affairs for Informatics at TU Wien, leading the Artifact-based Computing and User Research department. She holds a dual role as Head of Research Unit and oversees the Office of the Dean. Her work focuses on Human-Computer Interaction (HCI), Design Thinking, and Digital Transformation, with a strong emphasis on socio-technical systems and participatory design methodologies. Research interests span software engineering, CSCW, ambient assisted living (AAL), and digital co-creation practices in urban planning. She has spearheaded projects like aspern.mobil LAB, EnviSense, and StreetForum, exploring smart mobility, environmental sensing, and citizen participation in urban development. Her work frequently integrates tangible interfaces and model-based design approaches. Key contributions include frameworks for digital transformation evaluation (EEFCET 2020), user-centered design for informal caregivers (TOPIC platform), and crisis management systems using crowdsourcing (RE-ACTA). She has led over 20+ research projects funded by FFG, EU, and national agencies, focusing on mobility innovation, healthcare technology, and sustainable urban systems. Teaching responsibilities include courses on Design Thinking, Digital Transformation, and Research Methods across bachelor's, master's, and PhD programs. She actively promotes interdisciplinary collaboration through initiatives like the Center for Technology & Society (CTS) and Living Lab methodologies.

• Human-Computer Interaction
• Virtual Reality
• Augmented Reality
• +5 more

Johanna Pirker serves as an Associate Professor at the Institute of Human-Centred Computing, Graz University of Technology, where she holds teaching authorization in Applied Computer Science. Her work bridges academic research with practical applications in interactive technologies, maintaining active consultation hours for students every Monday morning. Her research centers on human-centered computing with emphases on virtual/augmented reality systems, serious game design, and AI-driven interactive experiences. She investigates player behavior, user experience optimization, and therapeutic/educational applications of immersive technologies across diverse contexts including rehabilitation, engineering education, and social platforms. Recent 2025 publications reveal strong trends in AI integration for gaming ecosystems (toxicity detection, dialogue systems), VR-based educational tools across disciplines, and cross-cultural analyses of gaming communities. Her work consistently combines experimental user studies with novel system development to address real-world challenges. While specific grant details and student advising records aren't documented in source materials, her extensive publication output across venues like FDG and iLRN indicates active leadership in interdisciplinary collaborations focused on advancing immersive technologies for societal benefit.