Beng Chin Ooi is a Lee Kong Chian Centennial Professor at the National University of Singapore (NUS), School of Computing (SoC). He holds a B.Sc. (1st Class Honors) and Ph.D. in Computer Science from Monash University. His research focuses on database systems, large-scale analytics, and distributed computing. He has held leadership roles including Dean of School of Computing (2007–2013) and Director of Smart Systems Institute (2011–2021). Key achievements include the Singapore President’s Science Award (2011), ACM Fellow (2011), IEEE Fellow (2009), and multiple best paper awards. His work emphasizes scalable data management, blockchain systems, and healthcare data analytics. Education: Monash University (B.Sc., Ph.D.) Leadership: Dean (SoC), Director (Smart Systems Institute) Awards: Over 15 major honors including ACM SIGMOD E.F. Codd Innovations Award (2020) His research spans distributed databases, big data systems, and innovative applications of blockchain technology. Recent work includes NASI (neural architecture search) and Rafiki (ML-as-a-service).
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.
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.
Jiao Licheng is a Distinguished Professor and Doctoral Supervisor at Xidian University, leading the School of Artificial Intelligence and the Department of Computer Science and Technology. He holds prominent roles such as Director of the Key Laboratory of Intelligent Perception and Image Understanding (Ministry of Education) and the International Joint Research Center for Intelligent Perception and Computing. His research focuses on Artificial Intelligence, Deep Learning, Evolutionary Computation, and Remote Sensing, with significant contributions to image understanding and brain-inspired computing. Education: B.E. (1982) from Shanghai Jiao Tong University, M.E. (1984) and Ph.D. (1990) from Xi'an Jiaotong University. Postdoctoral research at Xidian University (1990–1992). Research Interests include AI, Machine Learning, Image Processing, and Big Data Analysis. His work bridges theoretical advancements and practical applications, such as medical imaging, SAR image analysis, and autonomous systems. Recent articles emphasize innovations in remote sensing, deep learning architectures, and evolutionary algorithms. Awards include IEEE Fellow, IET Fellow, and the Wu Wenjun Artificial Intelligence Outstanding Contribution Award. Labs/Teams: Key Lab of Intelligent Perception, International Joint Research Center, and leadership in national innovation bases. Active in academic societies, including editorial roles in IEEE Transactions on Cybernetics and Geoscience and Remote Sensing.
Vienna University of Economics and BusinessAustria
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.
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.
Kan Haidong is a Distinguished Professor and Associate Dean at the School of Public Health, Fudan University (Shanghai, China). He holds the Chang-Jiang Scholar Professorship from the Ministry of Education and serves as an Associate Editor for Environmental Health Perspectives and International Journal of Epidemiology . His research focuses on environmental epidemiology, air pollution impacts, and climate change health effects. He has authored over 114 h-index papers and been recognized as a Clarivate Highly Cited Researcher and Stanford Top 2% Scientist. Education: PhD in Environmental Epidemiology, Fudan University (2003) MS in Environmental Health Sciences, Fudan University (2000) MD in Preventive Medicine, Shanghai Medical University (1997) Research Interests: Kan’s work bridges environmental exposures (air pollution, climate change) with human health outcomes. Key areas include particulate matter toxicity, heatwave mortality, and policy-driven health interventions. His studies often involve large-scale epidemiological analyses and global health collaborations. Key Awards: Wu-Jieping Paul Janssen Medical-Pharmaceutical Award (2018) US EPA Scientific Achievement Award (2015) Elsevier Top Influential Chinese Scholar (2014–2023) Grants/Editorial Roles: He leads WHO air quality guideline projects and chairs editorial boards for top journals. His grants focus on climate health adaptation and pollution mitigation strategies in China and globally. Labs/Teams: Directs Fudan’s Environmental Health Department and collaborates with global networks like the China Kadoorie Biobank and Lancet Planetary Health initiatives.
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.
Mei Hong is a Professor and Vice President for HR and International Collaboration at Beijing Institute of Technology since 2016. Previously, she held leadership roles including Vice President for Research at Shanghai Jiao Tong University (2013-2016) and Dean of the School of Electronics Engineering and Computer Science at Peking University (2006-2014). She has made groundbreaking contributions to software engineering and system software fields. BSc and MSc in Computer Science & Engineering from Nanjing University of Aeronautics & Astronautics (1984, 1987) PhD in Computer Science and Technology from Shanghai Jiao Tong University (1992) Her research focuses on software architecture , component-based software engineering , and cloud computing/big data systems . She has led over 40 grants totaling 200+ million CNY and holds 20+ patents. Her work addresses critical challenges in software lifecycle modeling, interoperability, and standardization. As a leading authority in software engineering, she has received China's highest honors including State Awards for Science and Technology Progress (2006), Technology Invention (2008), and Natural Science (2012). She was elected Member of the Chinese Academy of Sciences in 2011 and IEEE Fellow in 2014. Executive Editor-in-Chief of Science China-Information Sciences (2012-2017) Editor-in-Chief of Science China-Information Sciences (2018-present) Advisory Board Member of Alibaba DAMO Academy (2017-present)
Rudolf Winter-Ebmer is a Full Professor of Labour Economics at Johannes Kepler University (JKU) Linz, Austria, and a Research Professor at the Institute for Advanced Studies (IHS) in Vienna. He is affiliated with the Centre for Economic Policy Research (London), the Institute for the Future of Labor (IZA, Bonn), and the Centre for the Economics of Migration (UCL). He holds a PhD in Economics from the University of Linz. He has held visiting positions at institutions including the University of California, Berkeley, and has received offers for Full Professorships at Graz, Vienna University of Economics, and NUI Maynooth. He has consulted for the World Bank, Austrian Ministries, and the Vienna Institute for Economic Research. His research focuses on applied labor economics, including immigration, wage determination, ageing, unemployment, discrimination, education economics, empirical industrial organization, gender economics, and demographic research. He leads major initiatives such as the Austrian Christian-Doppler Laboratory for Ageing, Health, and the Labor Market and serves as Austrian country team leader for the SHARE survey. Awards: Maria-Schaumayer Research Prize (1995), Novartis Science Prize (1997), Theodor-Körner Prize (2000), Voestalpine Science Prize (2003), Morgenstern-Award (2010), and membership in the German Academy of Sciences (Leopoldina). Leadership Roles: President of the Austrian Economic Association (2021–2023), former Chair of the National Research Network on Austrian Labor Economics (2008–2014). His work is widely cited (Google Scholar: 8,800 citations, h-index 44), with publications in top journals like the American Economic Review and Journal of Labor Economics.
Emanuel Sallinger is a Full Professor at TU Wien's Databases and Artificial Intelligence Group and Vice Dean of Academic Affairs for Business Informatics and Data Science. He leads the Knowledge Graph Lab, focusing on scalable knowledge-based systems, reasoning in knowledge graphs, and AI integration. His research spans computational logic, database theory, and blockchain applications. Education: PhD in Computer Science (awarded 'sub auspiciis praesidentis rei publicae'), Master's degrees in Computational Intelligence and Informatics Management, and a Bachelor's in Software and Information Engineering. Research Interests: Knowledge graphs (construction, reasoning, scalability), logic-based systems, AI/ML integration with databases, enterprise architecture modeling, and financial knowledge systems. His work emphasizes practical applications like enterprise modeling, sustainable waste management, and regulatory compliance. Grants & Projects: Lead Vienna Science and Technology Fund (WWTF)-funded Knowledge Graph Lab. Involved in projects like 'Knowledge Graph-driven Tour Management' (sustainability), 'SustainGraph' (waste processing), and 'Enterprise Architecture Knowledge Graphs'. Teaching: Offers courses on Knowledge Graphs, Generative AI, Database Systems, and research methodology. Supervises doctoral and master's students in AI, databases, and knowledge representation. Labs/Teams: Knowledge Graph Lab at TU Wien, collaborating with industry on blockchain-based systems, financial AI, and enterprise architecture frameworks.
Zeshui Xu is a Full Professor at the Business School of Sichuan University, China, with concurrent roles as Adjunct Professor at multiple prestigious institutions including Nanjing University of Aeronautics and Astronautics and Southeast University. He has held distinguished positions such as Chair Professor at PLA University of Science and Technology and was part of the Cheung Kong Scholars Program. His research focuses on decision-making theory, information fusion, clustering algorithms, and fuzzy systems. He is a highly cited researcher (2014–2021) and holds fellowships from IEEE, RSA, IFSA, and others. Education: M.Sc. in Operations Research and Cybernetics, Qufu Normal University Ph.D. in Management Science, Southeast University Research Contributions: Dr. Xu has authored 18 Springer monographs and 700+ SSCI/SCI papers, achieving over 73,000 citations with an h-index of 138. His work includes groundbreaking contributions to intuitionistic fuzzy aggregation operators, hesitant fuzzy systems, and probabilistic linguistic decision-making frameworks. Awards & Recognition: Member of EASA and IASCYS Fellowships: IEEE, RSA, ORS, AAIA, and others Natural Science Awards (Ministry of Education) State Council Expert with Special Allowance Editorial Roles: Associate Editor/Editorial Board Member for over 30 journals, including IEEE Transactions on Cybernetics and Fuzzy Systems. Invited to 50+ academic conferences.
Vienna University of Economics and BusinessAustria
Prof. Viktoria HSE Robertson is a Professor of Corporate Law, Antitrust Law, and Digitalization at Vienna University of Economics and Business (WU Vienna), where she also serves as Head of the Department of Antitrust Law and Digitalization. Her research focuses on European and international antitrust law, digitalization's impact on competition, and comparative legal frameworks. She teaches courses such as *Corporate Law*, *Competition, Antitrust and Intellectual Property Law*, and *Competition Law in the Digital Economy*, emphasizing digital markets and regulatory challenges. Her work bridges antitrust law with digital innovation, addressing topics like algorithmic pricing, data governance, and the role of competition law in safeguarding democracy. Robertson is affiliated with organizations such as the Academic Society for Competition Law and the Women in Competition Law Network Austria. Her recent research includes studies on DMA implementation, computational antitrust, and green transition policies within EU competition frameworks. Robertson holds degrees including Mag. (Austria), MJur (Oxford), and has authored books like *Competition Law’s Innovation Factor: The Relevant Market in Dynamic Contexts in the EU and the US*. Her interdisciplinary approach integrates legal analysis with technological and economic considerations, shaping modern competition law discourse globally.
Xiaotie Deng is a distinguished academic and Chair Professor at Peking University (since 2018), with prior roles at Shanghai Jiao Tong University (2013–2017), the University of Liverpool (2010–2013), and City University of Hong Kong (1997–2013). His research focuses on algorithmic game theory, internet economics, and parallel computing. He holds prestigious fellowships including ACM Fellow (2008) and IEEE Fellow (2019). Deng has led significant grants, including a RMB 5M project on algorithmic game theory at Peking University (2018–2020) and NNSFC-funded research on market competitiveness and fairness (2018–2020). Education: PhD in Computer Science from Stanford University (1989), MSc from Chinese Academy of Sciences (1984), BSc from Tsinghua University (1982). Research interests span computational game theory, equilibrium analysis, and blockchain applications. Notable contributions include foundational work on Nash equilibrium complexity and mechanism design for resource allocation. He has advised numerous PhD students and serves on editorial boards of top journals like SIAM Journal on Computing and IEEE Transactions on Cloud Computing. Key awards: ACM and IEEE Fellowships, JSPS Invitation Fellowships (2005, 1996), and NSERC International Fellowship (1991). Active in conference organizing, including PC chairs for WINE 2020 and SAGT 2018. Consultancy includes work with Cryptape, Ant Financial, and Microsoft Research Asia, reflecting his industry engagement in algorithmic solutions and blockchain technologies.
Associate Professor Dr. Thomas Waitz is a tenure-track professor of media cultural studies at the Institute for Theatre, Film and Media Studies at the University of Vienna. His work critically explores intersections of media aesthetics, capitalism, class society, and climate crisis through cultural theory frameworks. Education : Studied film/TV studies and German philology at Ruhr University Bochum, earned PhD from Goethe University Frankfurt in 2013 Research Themes examine: Politics of media representation in late capitalism Class production mechanisms through television Neoliberal self-technologies in digital culture Climate crisis through media studies lens Paradoxes of boredom and procrastination Infrastructure of academic labor and publishing Academic Leadership includes: Senior scientist at University of Vienna Visiting professorships at HBK Braunschweig and University of Vienna Editorial roles in Journal of Media Studies and co-editor of 6 major publications Key Publications span 2014 monograph Images of Transport to 2024 work on digital self-regulation. His research engages with: Algorithmic cultures Surveillance capitalism Media archaeology Urban media spaces Platform labor Body politics Awards & Memberships : Liaison Lecturer, Rosa Luxemburg Foundation Board member, Society for Media Studies Peer reviewer for ZfM , nachdemfilm.de , and Digital Culture & Society
