Abstract: Cryptocurrency investors face significant challenges in detecting fraudulent schemes, which can lead to substantial financial losses. Existing fraud detection methods primarily analyze blockchain transaction records, inherently requiring that some victims have already suffered losses before fraud is identified. In this talk, I will introduce our research on early fraud detection through smart contract code visualization, including visualizing code behaviors and smart contract execution simulations. It eliminates the dependency on transaction data, enabling investors to proactively identify potential frauds before any transactions occur. Our visualization approaches provide an intuitive way of fraud risk assessment for common cryptocurrency investors.

Speaker Bio: Dr. Yong Wang is a tenure-track assistant professor at the College of Computing and Data Science, Nanyang Technological University, Singapore. Before that, he was a faculty member at the School of Computing and Information Systems, Singapore Management University (SMU). He obtained his PhD degree from the Hong Kong University of Science and Technology. His research interests include data visualization, HCI and human-AI collaboration, with a special focus on AI-powered data visualization and visual analytics for FinTech, quantum computing and online learning. He was recognized as the AI 2000 Most Influential Scholar Honorable Mention in Visualization in 2024. His work has been published at premier venues of visualization and human-computer interaction (e.g., IEEE VIS, IEEE TVCG, ACM CHI and EuroVis) and has received multiple paper awards, including Best Paper Honorable Mention Award at PacificVis 2025 Journal Track, Best Paper Honorable Mention Award at ACM CHI 2022, Best Paper Honorable Mention Awards at IEEE VIS 2021 and Best Paper Award at ACM IUI 2017. He has served as a program committee for IEEE VIS, EuroVis, PacificVis, CIKM, ACM IUI, ChinaVis, and a reviewer for multiple visualization conferences and journals.

Abstract: In the digital economy era, the effective utilization of data as a key production factor has become an important engine driving economic development. However, facing the explosive growth of data, its potential value has not been fully released. Particularly in the industrial application of data intelligence and visualization technology, significant challenges remain: high technical barriers, insufficient response to customized needs, weak deep analysis capabilities, and lagging practical applications of AI and natural language processing technologies. This report will focus on the three dimensions of data governance, analysis, and visualization, combining data insight product implementation practices to systematically elaborate on enterprise-level intelligent analysis solutions in the digital 3.0 era. By building a service system that encompasses core characteristics such as visualization presentation, intelligent decision-making, real-time response, simplified interaction, and security assurance, it provides implementable paths for releasing enterprise data value and promoting industrial digital transformation.

Speaker Bio: Ke Xu, Associate Professor and doctoral supervisor at the School of Intelligent Science and Technology, Nanjing University. He received his PhD from the Hong Kong University of Science and Technology in 2019 (supervisor: Professor Huamin Qu) and his bachelor's degree from Nanjing University in 2015. He has served as a Huawei Cloud technical expert, postdoctoral researcher at New York University, and visiting scholar at Harvard University, dedicated to research in big data analysis, artificial intelligence, visualization, and scientific intelligence. He has published over 10 papers in important international academic journals and conferences in data science such as IEEE TVCG, ACM CHI, VIS, and has applied for 13 patents. He has received the ACM CHI Best Paper Nomination Award. He was selected for Huawei's 'Genius Youth' program and served as a technical expert in the data intelligence field at Huawei Cloud. As a main founder, he participated in creating Huawei Cloud's first data intelligence cloud service DateArts Insight, contributing industry-leading data visual analytics and BI Copilot solutions, and achieved commercial applications on 50+ clients including Huawei ERP and Industrial and Commercial Bank of China.

Abstract: Data visualization is transitioning from data-driven to intelligent generation integration. As a leading enterprise-level visualization platform in China, Alibaba Cloud DataV leverages Tongyi large models and cloud-native architecture to explore the generative capability of 'natural language → visual expression', promoting freer and more efficient visualization expression. This sharing will demonstrate the team's technical exploration path and industrial implementation experience.

Speaker Bio: Head of DataV data visualization product line and leader of Alibaba Cloud frontend technology domain. Founded DataV product from zero to one, promoting widespread application and commercialization of data visualization technology. The product has cumulatively supported the construction and release of over one million visualization applications on the cloud, creating benchmark applications for data visualization in multiple fields. Led the team to dominate the writing of multiple domestic data visualization industry standards, continuously promoting the development of standardized and scaled applications of data visualization.

Abstract: Graph visualization technology has wide applications across various industries. This report will combine the speaker's engineering practice experience from the past 3-5 years to introduce application cases of graph visualization technology in multiple industries, including: network security, cloud computing, data governance, etc. The cases include: graph analysis product prototype development, graph analysis-related software function module development, new graph layout algorithm development, etc.

Speaker Bio: Ying Zhao, PhD, Professor and doctoral supervisor at the School of Computer Science, Central South University. Her main research areas include: visualization and visual analytics, human-computer interaction, and big data technology. She has led over 10 industry-academia-research cooperation projects with companies such as Qianxin, Huawei Cloud, Alibaba Cloud, CETC, and Bosch. She has won 6 awards in the IEEE VAST Challenge 2012-2017 international visual analytics challenge, received Best Paper Nomination Awards at IEEE VIS 2020 and 2022, Best Paper Nomination Award at IEEE PacificVis 2018, and Best Paper Awards at ChinaVis 2018 and CSS 2013.