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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.

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

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

Gerald Reiner serves as Head of the Institute for Production Management at the Vienna University of Economics and Business (WU), within the Department of Information Systems and Operations Management. He holds a Magister Degree, doctorate, and Habilitation in Business Administration from WU. His academic career includes positions as full professor in Production Management and Logistics at the University of Neuchatel (Switzerland, 2007-2014) and Universitaet Klagenfurt (Austria, 2014-2018), where he also served as head of the department of Operations, Energy, and Environmental Management. Dr. Reiner has held visiting professorships at Aston Business School (UK), HEC Lausanne (Switzerland), University of Bergamo, and Università Cattolica del Sacro Cuore in Milan (Italy). His research spans several critical areas including Industry 4.0 implementation, integrated capacity and inventory management, humanitarian logistics operations, circular supply chains, and operations management for base of the pyramid contexts. His work particularly focuses on practical applications addressing food waste reduction, sustainable manufacturing, and blockchain technology in supply chains. His publication portfolio demonstrates a clear evolution toward digital transformation in operations, with recent focus on hydrogen production systems, AI integration in manufacturing, and blockchain applications for food supply chain transparency. The research shows increasing emphasis on sustainability integration within traditional operations management frameworks, particularly addressing European manufacturing challenges and food system inefficiencies. Publication Excellence Award 2021 (2023) Researcher of the month (January 2023) Highly Commended paper in the 2017 Emerald Literati Network Awards for Excellence ISIR Service Award (2014) Emerald Outstanding Paper Award (2013) Dr. Reiner coordinates multiple significant international research projects including EU-project 'Keeping Jobs in EU', EU/Ecsel-project 'Power Semiconductor and Electronics Manufacturing 4.0', 'Integrated Development 4.0', and 'Artificial Intelligence in Manufacturing leading to Sustainability and Industry 5.0'. His current projects focus on FOODIS (cross-border ecosystem for innovation in food supply chains), Circular Design implementation, and blockchain applications for banana supply chains. He actively supervises research teams working on food waste reduction, sustainable packaging systems, and AI applications in operations management.

• Circular Supply Chains
• Operations Management for Base of the Pyramid
• Humanitarian Logistics Operations
• +7 more

Professor Moncef Gabbouj is a distinguished academic and researcher currently serving as Professor of Signal Processing at the Department of Computing Sciences, Faculty of Information Technology and Communication Sciences, Tampere University, Finland. Previously, he held the same position at Tampere University of Technology before the merger in 2019. He has also held visiting professorships at prestigious institutions including Hong Kong University of Technology and Science, University of Southern California, and Purdue University. Ph.D. and MSc. in Electrical Engineering from Purdue University, USA (1989 and 1986) B.Sc. in Electrical Engineering from Oklahoma State University, USA (1985) Prof. Gabbouj's research spans multiple domains within signal and image processing, with a strong focus on machine learning applications. His primary research interests include artificial intelligence, machine learning, Big Data analytics, multimedia content-based analysis, indexing and retrieval, nonlinear signal and image processing, voice conversion, and video processing and coding. His work bridges theoretical advancements with practical applications across various industries, particularly in multimedia communications and biomedical applications. His extensive publication record demonstrates a clear evolution from traditional signal processing techniques toward more sophisticated machine learning and deep learning approaches. Recent work shows increasing focus on convolutional neural networks for various applications including ECG classification, video processing, financial time-series analysis, and image recognition tasks, reflecting the broader trend in the field toward deep learning methodologies while maintaining strong foundations in signal processing theory. IEEE Fellow (2011) Member, Finnish Academy of Science and Letters (2014) Knight, First Class, of the Order of the White Rose of Finland (2006) Nokia Foundation Recognition Award (2005) Nokia Foundation Visiting Professor Award (2012) Finnish Cultural Foundation for Art and Science Award (2017) TUT Foundation Grand Award (2015) Prof. Gabbouj has supervised 64 doctoral and 72 Master's theses, demonstrating his significant contribution to academic mentoring. His research has been supported by substantial funding, including research grants totaling 8.5 million Euro (2001-2015). He has served as Academy of Finland Professor during 2011-2015 and has been involved in numerous EU research projects including Horizon, ESPRIT, HCM, IST, COST, Tempus and Erasmus programs. As Editor, Guest Editor or member of the Editorial Board of 6 international scientific journals, he has significantly influenced the academic discourse in his field. He leads the Signal Analysis and Machine Intelligence (SAMI) research group at Tampere University and serves as the Finland Site Director of the NSF IUCRC funded Center for Visual and Decision Informatics. His research unit focuses on applying advanced machine learning techniques to solve complex problems in signal processing, computer vision, and multimedia analytics, with applications ranging from healthcare to multimedia communications and financial analysis.

• Machine learning
• Artificial intelligence
• Signal processing
• +9 more

Eduard Gröller is a Full Professor of Visualization at the Vienna University of Technology (TU Wien), leading the Research Unit of Computer Graphics and the Visualization Group within the Institute of Visual Computing & Human-Centered Technology (VC&HCT). He holds adjunct professorships at the University of Bergen, Norway, and chairs several academic committees. His academic journey began with a PhD in 1993 from TU Wien, followed by extensive contributions to visualization research. His research focuses on visual computing, scientific visualization, and medical imaging, with applications in energy modeling, climate analysis, and molecular biology. Gröller has pioneered methods like BEMTrace for BIM-based energy models and HORA 3D for flood risk visualization. He co-authored over 300 publications, including foundational work in IEEE Transactions on Visualization and Computer Graphics and Computer Graphics Forum . Gröller's awards include the IEEE VGTC Technical Achievement Award (2019), Eurographics 2015 Outstanding Technical Contributions Award, and Fellow of the Eurographics Association (2009). He actively contributes to conferences like EuroVis and IEEE Visualization as program chair and reviewer. His educational efforts span courses in visual computing, graphics, and data analysis, with a focus on immersive tools like ImNDT for material data exploration. Current projects include Climate-Sensitive Adaptive Planning for Resilient Cities, Visual Analytics in Radiation Therapy, and scalable web-based visualization techniques. He leads teams in VRVis, a research center for applied visualization, and collaborates internationally on medical imaging and environmental data challenges.

• Visual Computing
• Scientific Visualization
• Volume Visualization
• +5 more

Cecilia Furlan is an Assistant Professor at the Institute of Landscape Architecture , part of the Department of Landscape, Water and Infrastructure at the University of Natural Resources and Life Sciences, Vienna (BOKU). She holds a joint PhD in Engineering and Urbanism from KU Leuven and IUAV Venice. Landscape Urbanism Circular Economy Urban Metabolism Spatial Research Resource Scarcity Her research focuses on systemic design approaches for circular economy transitions in urban and regional contexts, particularly through projects like ATLANTES and REPAiR . She explores material flow mapping, post-industrial landscape regeneration, and urban wasteland transformation. Recent publications examine geodesign methods for circular construction hubs, ecosystem services in urban cemeteries, and spatial parameters for sustainable development. She contributes to international discourse through presentations at institutions in Austria, Belgium, Italy, Netherlands, and South Africa. 2020: Knowledge Frontiers Symposium grant 2019: EUROPAN 15 Runner-Up 2018: Premio Giovanni Ferraro PhD award 2014: Lisbon Open Room Competition honorable mention As a project leader for initiatives like Reindustrialisation Following the Brownfield Principle , she combines academic research with practical applications. She participates in peer-review activities for journals like Sustainability and Landscape Research , and organizes educational workshops on circular design.

• Landscape Architecture
• Landscape Urbanism
• Circular Economy
• +5 more

Dr. Emma Izquierdo-Verdiguier is a Researcher at the Institute of Geomatics within the University of Natural Resources and Life Sciences, Vienna (BOKU) . She specializes in machine learning algorithms for remote sensing data analysis , with particular focus on land surface phenology and cloud computing environments like Google Earth Engine. Her research spans two decades, including postdoctoral work at the University of Valencia (2017-2018) and University of Twente (2014-2017). She has developed Matlab toolboxes for nonlinear feature extraction and transitioned to JavaScript/Python-based cloud computing solutions for high-resolution image classification. Key methodologies involve kernel methods , multispectral image analysis , and data cube clustering . Recent publications focus on climate change impact assessment (2025), carbon flux modeling (2023), and soil organic carbon monitoring (2025), demonstrating her expertise in Earth Observation and machine learning integration . Her work frequently employs Google Earth Engine for continental-scale analyses. Scientific Awards: 2018 Travel Award sponsored by Remote Sensing 2017 Best Youth Oral Paper Award (X. Wu), ISPRS 2012 2nd Best Paper Award, IEEE IGARSS Student Competition

• Remote Sensing
• Machine Learning
• Geospatial Data Analysis
• +4 more

Christian Beckmann is a Full Professor of Statistics in Imaging Neurosciences at Radboud University Medical Centre Nijmegen and a Principal Investigator at the Donders Institute for Brain, Cognition and Behaviour. His career spans institutions including the University of Twente, Imperial College London, and the University of Oxford, with a focus on interdisciplinary approaches integrating cognitive neuroimaging, imaging genetics, and pharmacology. Education: MSc and DPhil degrees at the University of Oxford (20014). His research centers on developing novel computational analysis methods for neuroimaging data, particularly Independent Component Analysis (ICA), applied to connectomics, imaging epidemiology, and big data analytics. He emphasizes creating sensitive, specific, and interpretable tools for neurobiological applications, such as the widely used FSL (FMRIB Software Library), which impacts over 650 institutions globally. Scientific Awards: Thomson Reuters/Clarivate Analytics Highly Cited Researcher (2014–2016) NWO VIDI Fellowship (2014) Wiley OHBM Young Investigator Award (2011) Membership, Young Academy, University of Twente (2011) Advising & Grants: He has trained over 20 PhD students (8 completed) and 9 postdoctoral researchers, securing grants from the Netherlands Organisation for Scientific Research and other international bodies. His work bridges technical innovation with clinical applications, advancing diagnostics and treatment strategies.

• Big Data
• Neuroimaging
• Model-Free Data Analysis
• +4 more

Dr. Eva Mayr is a Senior Researcher at the University for Continuing Education Krems, affiliated with the Center for Cultures and Technologies of Collecting . Her work focuses on user-centered design, casual information visualization, digital humanities , and cognitive and media psychology . She leads major projects such as the Bibliotheca Eugeniana Digital (2022–2024) funded by the Austrian Academy of Sciences, and previously directed initiatives like In/Tangible European Heritage (2020–2023, EU-funded) and Uncertainty visualization of cultural heritage data (2017–2020, state-funded). Her research emphasizes innovative visualization techniques for cultural heritage, including methods to handle uncertainty in data and enhance accessibility for casual users. She teaches Usability and Research Methods , and actively contributes to organizations like the OCG IIID . Key contributions include frameworks for integrating cultural data (e.g., InTaVia ) and advancing narrative visualization approaches for historical and biographical data. Publications span journals like Frontiers in Big Data and IEEE Computer Graphics and Applications , with a focus on cultural heritage digitization, set visualization, and mental models in design. Projects often bridge academia and applied contexts, addressing challenges in accessibility, collaboration, and data quality within cultural institutions.

• Digital Humanities
• Information Visualization
• User-Centered Design
• +3 more

Lisa Perkhofer is a Researcher at the University of Applied Sciences Upper Austria’s Department of Accounting, Controlling and Financial Management, part of the R&D-Headquarters. She actively contributes to projects focusing on digital transformation, ICT integration, and financial management innovation. Education: PhD in Information Systems (2021), Vienna University of Economics and Business (2014–2021) Master’s in Controlling, Accounting and Finance (2013), University of Applied Sciences Upper Austria (2011–2013) Her research interests revolve around optimizing data visualization for managerial decision-making, leveraging big data and eye-tracking technologies. She explores how cognitive load theory can enhance financial reporting systems, user-centered design principles in interactive dashboards, and sustainability reporting complexity reduction. Her work bridges financial management practices with advanced IT solutions. In her research outputs, Lisa emphasizes digital transformation in financial processes, RPA applications, and SME risk assessment. She combines technical innovations like dashboard design with practical financial management challenges, highlighting trends toward user-centric and data-driven solutions. She has received notable awards including the Best Paper Award (2016) , Dr. Hermann Zemlicka Award (2018) , and the KPMG Stiftungspreis für die beste Masterarbeit im Finanzbereich (2013) . Additionally, she was honored with the Emerald Most Commended Research Award (2015) . Advising and Grants: Contributed to four major research projects as Co-Principal Investigator (CoPI) or Co-Investigator (CoI) Funded projects include FTI-Strukturförderung, COIN Cooperation & Innovation, and Land OÖ Basisfinanzierung Labs/Teams: Involved in interdisciplinary teams such as FinCoM (Financial Condition Monitoring), USIVIS (User-Centered Interactive Visualization for Big Data), and BF-Smart Visualization 4.0, collaborating on topics ranging from dashboard design to SME risk analysis.

• Financial Management
• Managerial Accounting
• Information Systems
• +5 more

Peter Wetz is a researcher affiliated with the Institute of Software Technology and Interactive Systems at TU Wien. His work focuses on semantic data processing, environmental data systems, and interactive data exploration. He has contributed to frameworks like YABench for RDF stream processing and StatSpace for statistical data integration. His research integrates Linked Data, real-time environmental monitoring, and user-friendly data visualization tools. Notable projects include Linked Widgets and Open Mashup Platform, aiming to lower barriers for data exploration. He has authored over 20 publications between 2013–2017, emphasizing interdisciplinary approaches to data management and semantic technologies. Key Areas: Semantic Web, Environmental Data, Stream Processing Tools Developed: YABench, StatSpace, Linked Widgets Platform

• Semantic Web
• Data Integration
• Environmental Data Systems
• +3 more

Viktoria Dorfer is a Professor at the University of Applied Sciences Hagenberg, affiliated with the Bioinformatics Center of Excellence and Medical Engineering/TIMed Center HEAL. She holds an ORCID iD (0000-0002-5332-5701) and has published 66 research outputs with an h-index of 9 and 676 citations. 2007–2012: Doctoral research on algorithmic approaches 2013–2016: FWF Translational Research on MS Amanda 2020–2022: PI for b-tastic project Research Interests: Spanning bioinformatics, mass spectrometry, and medical engineering, her work focuses on: Algorithm development for peptide identification Evolutionary algorithms in data analysis Mass spectrometry software platforms (AMANDA, Annika) Cross-linked peptide analysis Precision agriculture applications Medical device optimization 2024 Trends: Recent contributions include symbolic regression in livestock farming, enhanced rescoring platforms, and structural analysis of the C. elegans Box C/D complex. Awards: EuPA Bioinformatics Mass Spectrometry Award (2020) Leadership: Organized Austrian Proteomic Research Symposia (2017), served as reviewer/peer-reviewer for journals, and led interdisciplinary collaborations.

• Bioinformatics
• Mass Spectrometry
• Machine Learning
• +7 more

Valentine Ananikov is a Professor at Moscow State University and Head of the Division of Structural Studies at the Zelinsky Institute of Organic Chemistry. Elected as a Member of the Russian Academy of Sciences in 2008 and Academia Europaea in 2018, his work focuses on catalysis, nanoparticle chemistry, and sustainable processes. Research Interests : Mechanistic studies of chemical reactions, development of nanoscale and molecular catalysts, biomass conversion, and AI integration in chemistry. His team combines experimental and theoretical methods to advance green chemistry. Scientific Awards : 2024 International Markovnikov Prize 2023 "Gravity" International Prize for AI research 2016 Organometallics Distinguished Author Award 2016 Hitachi High-Technologies Award 2004 Russian State Prize for Young Scientists Notable Contributions : Pioneering hybrid catalytic systems (homogeneous/heterogeneous), sustainable catalyst design from biomass, and AI applications in reaction discovery. His work addresses environmental safety and carbon-neutral chemical processes.

• Mechanistic studies of catalytic reactions
• Sustainable chemical processes
• Transition-metal-catalyzed transformations for organic chemistry
• +6 more

Steven Laureys is a Belgian-Canadian neurologist and neuroscientist holding the Canada Excellence Research Chair in Neuroplasticity at the CERVO Brain Centre (Laval University, Canada) since 2024. He also maintains positions as Professor at Laval University's Faculty of Medicine and Research Director at the Belgian National Fund for Scientific Research (FNRS). A pioneer in consciousness studies, Laureys established the Coma Science Group (2006) and GIGA Consciousness Unit (2014) at the University of Liège, Belgium, before co-founding the Hangzhou International Consciousness Institute (2015) and BRAIN-NM Neuromodulation Clinics (2023). MD, PhD, Vrije Universiteit Brussel (1993) M.Sc. in Pharmaceutical Sciences, VU Brussels (1998) PhD in Neurology of Consciousness, University of Liège (2000) His research focuses on clinical and cognitive neuroscience , particularly disorders of consciousness (coma, vegetative states, locked-in syndrome), neuroplasticity, and neuromodulation therapies. Using multimodal neuroimaging (PET, fMRI, EEG), he investigates brain dynamics during anesthesia, sleep, and meditation while developing novel diagnostic tools and rehabilitation strategies for brain-injured patients. Scientific Trends across his 450+ publications reveal extensive work on EEG microstate analysis (2025), thalamic firing patterns (2025), and neurostimulation techniques (taVNS, tDCS) for consciousness disorders. His team's 2024-2025 studies emphasize AI-driven consciousness mechanisms, cross-cultural end-of-life decision-making, and z-drug paradoxical effects. Scientific Recognition includes: 2004 - ASSC William James Prize 2017 - Francqui Prize (Belgium's highest scientific honor) 2024 - Canada Excellence Research Chair ($32M award) 2024 - Health 2.0 Outstanding Leadership Award As Editor-in-Chief of Brain Connectivity (2024), he advances interdisciplinary dialogue between neuroimaging, neurology, and computational science. His translational work bridges basic neuroscience with clinical applications, including co-founding international neuromodulation clinics and leading multicenter trials in traumatic brain injury rehabilitation.

• Neuroimaging
• Consciousness
• Neurostimulation
• +4 more

Prof. Silvia Miksch is a full professor in the Department of Visual Analytics at TU Wien. Her research focuses on visual analytics, time-oriented data visualization, and human-computer interaction. She leads projects in cultural heritage analysis, fraud detection, and pandemic data visualization. Her work bridges computer science with digital humanities, emphasizing user-centric design and uncertainty modeling. Key contributions include guidance systems for VA environments and network visualization frameworks for art history. Affiliations: TU Wien (since 2000+) Research Labs: Network Lab, Visual Analytics Research Group Recent projects explore temporal patterns in artist exhibitions, parameter space exploration, and pandemic data communication. She has advised over 20 PhD/Master’s students, many contributing to VA systems like COVIS and NEVA. Awarded the VGTC Visualization Technical Achievement Award (2024) for foundational work in temporal visualization. Active in IEEE VAST and serves on journal editorial boards. Her labs develop open-source tools for interactive data exploration.

• Visual Analytics
• Information Visualization
• Time-Oriented Data Analysis
• +3 more