From August 15 to 16, the 220th “Science and Technology Frontier Forum” organized by the Academic Division of the Chinese Academy of Sciences (CAS) was held at Nanjing University’s Suzhou Campus. The theme of this forum is “Data Science and Applications.” Tan Tieniu, Chair of NJU CPC Council and Academician of the CAS, as well as CAS academicians Guo Huadong, Xu Zongben, and Mei Hong served as the Executive Chairs of the forum.
Twenty academicians and seventy-four experts from domestic and international universities and research institutions gathered in Suzhou to conduct in-depth exchanges on fundamental theories, key technologies, innovative applications, and safety governance in data science. The forum provided suggestions for building China’s data science discipline, achieving breakthroughs in core technologies, and promoting industrial innovation and development.
In his welcome speech on behalf of the Forum Organizing Committee and NJU, Tan Tieniu welcomed the attendees. He noted that the CAS Academic Division’s “Science and Technology Frontier Forum”, established in 2011, is a high-level academic series activity advocating academic democracy and diverse perspectives. Since the 18th National Congress of the Communist Party of China, General Secretary Xi Jinping has delivered a series of important remarks on the development of data science and technology. Notably, at the founding conference of the International Data Organization, he sent a congratulatory letter, emphasizing that the world is accelerating into the intelligent era, where data is becoming increasingly important as both a basic resource and an innovation driver. He stressed the need for a digital economy based on data and the importance of ensuring security throughout data governance processes. These remarks have provided fundamental guidance for the development of data science and technology. The CAS Academic Division’s choice of “Data Science and Applications” as the theme of this forum aims to implement the General Secretary’s directives and carries significant practical importance. Tan expressed hope that the attending experts would engage in extensive discussions, contributing their wisdom and fostering an open, equal atmosphere to jointly explore frontier issues in data science and further advance related disciplines and technologies.
CAS Academician Ding Chibiao delivered a speech on behalf of the CAS. He outlined CAS’s “AI for Science” initiative, which aims to embrace paradigm shifts in scientific research brought about by artificial intelligence. This initiative has a “1+M+N” framework: “1” refers to the establishment of a universal foundation; “M” involves creating about ten major strategic areas empowered by AI; and “N” refers to supporting thousands of scientific application scenarios. In scientific data, CAS has undertaken several national tasks, such as building national scientific data centers, public service platforms, and scientific corpora, while actively forming a data system comprising a general center, domain-specific centers, and operational centers. CAS aims to continue adhering to open collaboration by working with domestic and international universities and research institutions to promote the coordinated and healthy development of AI for Science and data science applications.
Data has now become a crucial production factor. Data science is playing an increasingly important role in supporting the development of the digital economy, driving changes in scientific research paradigms, and enhancing the modernization of national governance. The forum was divided into three themes: “Data Theory and Algorithms” “Data Applications and Systems” and “Data Security and Governance”, closely aligned with national strategies of building digital China, developing data resource applications, and advancing AI innovation. The forum featured 12 academician-led reports and three concentrated discussions, systematically reviewing the current landscape and emerging trends in data science and analyzing key scientific challenges and technological bottlenecks.
On the morning of August 15, the forum held the “Data Theory and Algorithms” theme event, chaired by CAS Academician Xu Zongben.
CAS Academician Zhang Pingwen presented on “Mechanism and Data-Integrated Computation—A New Paradigm in Applied Mathematics”, discussing the fusion of mechanism-driven and data-driven scientific computation paradigms. He elucidated the pivotal role of mathematical theory in designing integrated algorithms, error analysis, and ensuring convergence.
CAS Academician Chen Songxi introduced advancements in the construction of ultra-high-resolution statistical data assimilation and high-quality reanalysis scientific datasets. He explained how high-dimensional statistical research enhances data assimilation, improving product precision and forecasting capabilities.
CAS Academician Li Hui gave a talk titled “Engineering Big Data and Knowledge Discovery”, exploring the new paradigms and approaches to knowledge discovery brought by AI and data science in fields such as civil engineering, energy systems, and aerospace systems.
National Academy of Sciences (USA) Academician Jianqing Fan presented on “Intelligent Data Science and Socio-Economics”, introducing applications of statistical learning and strategy optimization in areas such as socio-economic index construction, financial market analysis, and fraud detection in financial statements. After the reports, the attendees engaged in an extensive discussion on issues like mechanism-data integration, high-dimensional data analysis, engineering knowledge discovery, and intelligent data science.
The afternoon session focused on the “Data Applications and Systems” theme, chaired by CAS Academician Huang Wei.
CAS Academician Guo Huadong discussed “Earth Big Data Driving Sustainable Development Goals”, exploring how earth big data supports the monitoring and evaluation of United Nations sustainable development goals, global data platforms, and international scientific cooperation.
Academician Fang Binxing of the Chinese Academy of Engineering (CAE) elaborated on a data security protection framework covering the entire lifecycle—collection, creation, storage, processing, transmission, sharing, usage, archiving, and disposal—centered on its security, compliance, and usability attributes.
CAE Academician Zheng Qinghua presented a report titled “Principles and Applications of Big Data Knowledge Engineering.” He explored how massive amounts of data are transformed into machine-representable, computable structured knowledge and introduced the “Knowledge Forest” theory and its applications in fields such as intelligent education and tax projects.
Foreign CAS Academician Fan Wenfei focused his report on “From High-Quality Data to Trustworthy, Controllable, and Usable AI.” He analyzed the significance of high-quality data assets, reliable analytical algorithms, and independently controllable data infrastructure for building trustworthy AI systems. Following the reports, participating experts exchanged views on topics such as unlocking data value, knowledge engineering, data security, and trustworthy AI.
On the morning of August 16, the forum held the “Data Security and Governance” theme event, chaired by CAS Academician Guo Huadong.
CAS Academician Zhou Zhixin delivered a talk titled “Applications and Governance of Space-Based Remote Sensing Data for AI,” analyzing the challenges of acquiring high-quality remote sensing data and efficiently applying it on a large scale in the AI era.
CAS Academician Guan Xiaohong presented a report titled “Technical Support and Security Governance in Digital Government,” discussing the system architecture, organizational structure of digital government, as well as key technologies and management strategies for ensuring data security and AI system security.
CAE Academician Wu Shizhong delivered a talk titled “Open Scientific Issues in Security Evaluation of Large Language Models.” He analyzed matters such as defining and measuring the security boundaries of large models, the transition from static black-box correlation analysis to dynamic game evaluations, as well as scaling up security evaluations and achieving cross-model generalization.
CAE Academician Yun Xiaochun gave a presentation titled “High-Quality Datasets for Network Security in the AI Era”, emphasizing that high-quality datasets are fundamental to the construction of cybersecurity capabilities in the AI era and are crucial for improving national competitiveness and driving industrial transformation. Experts subsequently held discussions on topics such as data governance systems, AI security assessments, the development of high-quality datasets, and data security technologies.
During the forum’s conclusion, Tan Tieniu noted that the forum was efficiently organized and highlighted the in-depth exchanges among academicians and experts on major frontier topics in data science and applications. This demonstrated the CAS Academic Division’s effort to build a high-level academic exchange platform, promote interdisciplinary collaboration, and stimulate technological innovation. Regarding the future development of data science, Tan emphasized the importance of recognizing data as a core element of the digital economy and innovation. He called for accelerating the establishment of a clearly defined, fully-developed theoretical and methodological framework for data science, fostering its development into a more mature scientific discipline. He also urged for utilizing data as a “common language” across disciplines, promoting interdisciplinary collaboration and the integration of teaching and research. Furthermore, he stressed the need to enhance data quality, advance open sharing, and advocate “co-construction, coexistence, co-prosperity, and co-governance” to unlock the value of dormant data resources.
Tan further highlighted the importance of optimizing digital infrastructure construction, promoting collaboration between data centers, supercomputing centers, and intelligent computing centers to enhance seamless service capabilities while avoiding inefficiency and redundancy. He underscored the need to balance development and security by embedding safety mechanisms throughout the data value chain, particularly addressing specific security requirements in key sectors such as finance and healthcare. Lastly, he called for strengthened international cooperation in the data field and the establishment of talent pipelines to ensure the long-term development of data science.
During the forum, a tree planting activity was held, hosted by Suo Wenbin, Member of the Standing Committee of the CPC NJU Committee. 12 participating academicians planted trees at the Academicians’ Trees near Zhuangli Mountain in the Suzhou campus, adding new vitality to the university’s landscape. The tree planting activity symbolized the academicians’ wishes for academic prosperity, talent cultivation, and the innovative development of data science. 120 domestic and international academicians have previously planted trees there.
This forum was hosted by the CAS Academic Division and co-organized by the CAS Information Technology Science Division, the CAS Academic and Publication Work Committee, Nanjing University, the CAS Institute of Automation, and the journal Science China. The forum covered multiple disciplines, including mathematics, statistics, computer science, earth sciences, engineering, economics, social sciences, and public governance. It showcased the interdisciplinary, fundamental, and strategic role of data science and contributed to the high-quality development of data science in China. It also provided further support for the original development of fundamental theories, breakthroughs in key technologies, high-quality data provision, and the construction of data security governance systems. The forum promoted the integration of data resources, AI technologies, and economic and social development, offering strong support for building a digital China, achieving high-level scientific and technological self-reliance, and strengthening its position as a leading nation in science and technology.
