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).
Christoph Koch is a Full Professor in the School of Computer and Communication Sciences at EPFL (Ecole Polytechnique Federale de Lausanne) , Switzerland. He has held academic positions at Cornell University (2007-2010, 2006), Saarland University (2005-2007), and TU Vienna (2001-2005). His research focuses on database systems, logic, programming languages, and data management.
Dr. Athos Agapiou serves as an Assistant Professor at the Department of Civil Engineering and Geoinformatics, Cyprus University of Technology, where he holds the 'Geoinformatics and Earth Observation' chair. He also serves as Deputy Director of the UNESCO Chair on Digital Cultural Heritage and coordinates the EOCult Laboratory, a specialized research group focused on applying Earth Observation and Geoinformatics for archaeological research and cultural heritage landscapes. His research interests center on developing and applying innovative remote sensing technologies for cultural heritage preservation, addressing challenges posed by environmental and anthropogenic factors. Dr. Agapiou has led numerous high-profile research initiatives at European and national levels, including Horizon Europe and Horizon 2020 projects, as well as programs funded by the Cyprus Research and Innovation Foundation. His publication record demonstrates consistent output in remote sensing applications for archaeology, with particular focus on satellite image fusion, UAV technologies, spatial resolution optimization, and advanced data analysis techniques for archaeological prospection. His work bridges technical remote sensing methodologies with practical archaeological applications. Young Scientist Award from International Society for Digital Earth (2023) Young Researcher Award by Cyprus Research Awards (2018) Top 2% researcher worldwide in field (Stanford studies 2020-2024) Top three global researchers in Geoinformatics for cultural heritage (2024) Dr. Agapiou actively contributes to major research projects and collaborations, with his work influencing both academic research and practical applications in cultural heritage management. His laboratory (EOCult) serves as a hub for interdisciplinary research connecting geospatial technologies with archaeological practice.
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.
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.
Allen J. Scott is a Distinguished Research Professor at the University of California, Los Angeles, with a joint appointment in the Department of Public Policy (School of Public Affairs) and Department of Geography. He has held prestigious positions at UCLA since 1994 and previously at the University of Toronto (1969–1994). His career spans over five decades, focusing on urban geography, regional development, and cultural economy. Education : BA (1961) from Oxford University; MA and PhD (1962, 1965) from Northwestern University. Research Interests include: Creative cities and cognitive-cultural capitalism Political economy of urbanization and globalization Industrial clusters and labor-intensive economies Human capital distribution in metropolitan areas Cultural landscapes and peripheral development Publication Trends (2005–2014) emphasize: Globalization's impact on low-technology industries Cognitive-cultural capitalism in urban contexts Human capital dynamics in metropolitan hierarchies Celebrity culture and urban glamour Creative field theories and urban policy implications Scientific Awards : 1986 Guggenheim Fellow 2003 Vautrin Lud Prize 2005 Meridian Book Prize 1999–2013: Chaires d’Excellence, Fellowships, and Doctor Honoris Causa 2008 Carol and Bruce Mallen Lifetime Achievement Award 2003 ISI Highly Cited Author
Dr. Yunjie Yang is an Associate Professor at the University of Edinburgh's School of Engineering, with affiliations at the Edinburgh Futures Institute (EFI), the Edinburgh Generative AI Laboratory (GAIL), and the Edinburgh Centre for Robotics. He previously held the Chancellor's Fellow in Data Driven Innovation (2018-2023) and Bayes Innovation Fellow (2023-2024) positions. His research focuses on AI-powered sensing and imaging, machine learning, and soft sensors & electronics for robotics. Yang received his PhD in Engineering Electronics from the University of Edinburgh, MSc in Control Science & Engineering from Tsinghua University, and BEng in Measurement & Control Engineering from Anhui University. After his PhD, he worked as a Postdoctoral Research Associate in Chemical Species Tomography before securing his lectureship. His research interests center on developing intelligent sensing systems that replicate human perception capabilities for robotics and intelligent systems. He pioneers flexible sensing and imaging technologies across various scales through innovative multi-modal sensors, soft electronics, and their modeling using machine learning approaches. His work aims to enable autonomous physical artificial intelligence by bridging the gap between robotic systems and human-like perception. Analysis of his recent publications reveals a strong focus on soft robotics perception, particularly through electrical impedance tomography (EIT) and transformer-based architectures. His research spans medical imaging applications, digital twin modeling for industrial processes, and machine learning approaches for sensor data interpretation. The trend shows increasing integration of physics-informed deep learning with traditional tomographic techniques to achieve higher accuracy and efficiency. European Research Council (ERC) Starting Grant (2024) IEEE J. Barry Oakes Advancement Award (2024) IEEE I&M Society Graduate Fellowship Award (2015) Multiple Best Paper Awards Senior Member of IEEE Fellow of the International Society for Industrial Process Tomography Fellow of the Higher Education Academy ESI highly cited papers Dr. Yang serves as Associate Editor for IEEE Transactions on Instrumentation and Measurement and holds editorial positions with Scientific Reports and IEEE Sensors Journal. His research has been licensed to overseas research institutes and industry partners and received wide media coverage including BBC, EFE, USA Today, and STV. He has secured significant grant funding including the prestigious ERC Starting Grant. He leads the Edinburgh SMART Lab (Sensing/imaging + Machine Learning + Robotics), which aims to replicate human perception capabilities for robotics and advance flexible sensing technologies through innovative multi-modal sensors and machine learning approaches. The lab focuses on enabling autonomous physical artificial intelligence with applications spanning medical diagnostics, industrial monitoring, and advanced robotics systems.
Ian Horrocks is a Professor of Computer Science at the University of Oxford and a Fellow of Oriel College. His research focuses on knowledge representation, description logics, automated reasoning, and semantic web technologies. He has held academic positions at the University of Manchester (2003–2007) and served as Chief Scientist at Cerebra Inc. (2001–2006). Horrocks earned his BSc (1st class), MSc, and PhD in Computer Science from the University of Manchester (1981–1997). His work includes foundational contributions to ontology languages (e.g., OWL) and reasoning systems such as HermiT and ELK. He has supervised over twenty doctoral students and postdoctoral researchers. His honors include Fellowships from the Royal Society (2011), ECCAI (2009), and the British Computer Society (2005). He serves as Editor-in-Chief of the Transactions on Graph Data and Knowledge and leads initiatives in semantic web standards and knowledge graph applications. Key Roles: Editor-in-Chief (Journal of Web Semantics), Co-Chair (W3C OWL Working Group) Grants: EPSRC Senior Research Fellowship (2005), numerous international collaborations Labs: Oxford Semantic Technologies, involvement in projects like RDFox and PAGOdA
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
Professor Marta Zofia Kwiatkowska is Professor of Computing Systems and Fellow of Trinity College at the University of Oxford, where she has held a faculty position since 2007. She previously served as Professor of Computer Science at the University of Birmingham (2001–2007), Reader and Lecturer at the University of Birmingham (1994–2001), and Lecturer at the University of Leicester (1986–1994). Her academic career began as Assistant Professor at the Jagiellonian University in Kraków, Poland (1980–1988). Education: BSc/MSc in Computer Science, Jagiellonian University, Kraków MA, University of Oxford PhD, University of Leicester Research Interests: Professor Kwiatkowska spearheaded the development of probabilistic and quantitative verification methods on the international stage. Her work bridges theory and practice through the PRISM model checker—the leading software tool in probabilistic model checking—used worldwide for research and teaching. Application domains include communication and security protocols , nanotechnology designs , power management , ubiquitous computing and systems biology . She investigates automated verification , temporal logics , semantic models for concurrency , real-time systems , and biological process modelling . Current grant funding exceeds £3.7 million from EPSRC, EU and ERC, including the prestigious ERC Advanced Grant VERIWARE. Scientific Awards & Honours: Fellow of the Royal Society Fellow of the ACM Fellow of the European Association for Theoretical Computer Science (EATCS) Fellow of the British Computer Society (BCS) Fellow of the Polish Society of Arts & Sciences Abroad ERC Advanced Grant VERIWARE (€2.046 M, 2010–2015) Top Cited Article Award, Theoretical Computer Science (2005–2010) Best Paper Award, QEST 2006 Doctoral Supervision & Grants: Professor Kwiatkowska actively supervises doctoral students (D.Phil. at Oxford) and post-doctoral researchers. She welcomes applications in areas aligned with her research interests, detailed here . Current students include Charlie Griffin, Daqian Shao, Matthew Yuan and Minghao Liu; past students and researchers number over twenty, many now in faculty or industry leadership roles. Laboratory & Teams: She leads the Oxford Quantitative Verification group within the Department of Computer Science. Ongoing projects include FUN2MODEL, ELSA, FAIR and the flagship PRISM probabilistic model checker. The group maintains strong collaborations with biological, robotics and engineering teams worldwide.
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
Dr. Rajkumar Buyya is a Redmond Barry Distinguished Professor at the University of Melbourne and Founder & CEO of Manjrasoft , a spin-off commercializing cloud innovations. He has held visiting roles at Imperial College London , University of Birmingham , and Tsinghua University . Research Interests : His work spans Cloud Computing , Edge Computing , Grid Systems , and Energy-Efficient Computing , focusing on utility-driven resource allocation, simulation tools, and scalable IoT application frameworks. He pioneered the CloudSim toolkit and Aneka Cloud technologies. Scientific Awards : IEEE Fellow (2015), Web of Science Highly Cited Researcher (2016-2021) Khwarizmi International Award (2020), Scopus Researcher of the Year (2017) Frost & Sullivan New Product Innovation Award (2010), IEEE TCSC Medal (2009) Impact : Authored over 850 publications, including the widely adopted textbook Mastering Cloud Computing . Graduated 54 PhD students now in leadership roles at institutions like Newcastle University and companies such as IBM , Google , and Amazon . His research has driven global adoption of cloud/edge technologies in 50+ countries.
Prof. Yu Jihong is a full Professor at the Department of Chemistry, Jilin University, and serves as Director of the International Center of Future Science and Vice President of the Chinese Chemical Society. She leads the State Key Laboratory of Inorganic Synthesis and Preparative Chemistry. Her research focuses on designing nanoporous materials for energy and environmental applications, with over 320 publications in top journals like Science and Nature Communications. Education: BS (1989), MS (1992), PhD (1995) from Jilin University Postdoctoral: Hong Kong University of Science and Technology (1996–1997), Tohoku University (1997–1998) Research interests include inorganic synthesis, porous materials, catalytic materials, and environmental applications. Her work bridges computational methods with experimental synthesis, yielding innovations in zeolite structures and catalytic systems. Awards: IUPAC Distinguished Women in Chemistry Award (2017), TWAS Fellow (2016), Chinese Academy of Sciences Academician (2015), and multiple national science prizes. She is an Associate Editor of Chemical Science and leads editorial boards for Materials Horizons and others. Her articles emphasize novel synthetic methods, catalytic systems, and sustainable materials. Key themes include accelerating zeolite crystallization, designing nanocatalysts, and developing porous membranes for environmental applications.
Didier Sornette is Professor on the Chair of Entrepreneurial Risks at ETH Zurich since 2006, with concurrent affiliations as Professor at the Swiss Finance Institute, Special Professor at Tokyo Tech's Institute of Innovative Research, and Chair Professor (part-time) at Southern University of Science and Technology (SUSTech) in China. He founded the Financial Crisis Observatory (FCO) in 2008 to rigorously test financial market predictability during bubbles and co-developed the collaborative platform xYotta since 2012. Research Focus: Predictability and control of crises in complex systems, including financial crashes, earthquakes, social network dynamics, and medical applications (immune systems, epilepsy). Key Concept: Coined 'Dragon-kings' to describe extreme events with identifiable precursors, emphasizing their predictability. Scientific Awards AAAS Fellow (2013) Member of the Swiss Academy of Engineering Sciences (2019) E. N. Lorenz Lecture (2010), Ehrenfest Colloquium (2011) He has mentored 36 PhD students, supervised 120 master theses, and guided 38 post-docs (as of December 2019).
Peng Shige is a Professor of 1st class at the School of Mathematics, Shandong University, China. He has held the Distinguished Professor title under the Ministry of Education (Cheung Kong Scholarship) since 1999. His academic journey includes degrees from Shandong University (Physics diploma, 1971-1974), Paris-IX (1985), and Aix-Marseille University (PhD 1986, Habilitation 1992). Research focuses on nonlinear expectations, stochastic calculus, partial differential equations, and financial mathematics. Key contributions include foundational work on backward stochastic differential equations (BSDEs), the g-expectation framework, and the G-expectation theory extending probability axioms to nonlinear settings. These innovations have advanced stochastic control, financial risk modeling, and differential games. Honors include the 2020 Future Science Award, 2011 Princeton Global Scholar, and 2005 Chinese Academy of Sciences Academician status. He delivered a plenary lecture at the 2010 International Congress of Mathematicians. Peng's work integrates theoretical breakthroughs with applied domains like financial engineering. His research has been widely cited (~8k citations) and shaped modern stochastic analysis methodologies.
