Beijing Key Laboratory of Topological Statistics and Applications for Complex Systems has been officially inaugurated at Beijing Institute of Mathematical Sciences and Applications (BIMSA)
Recently, the Beijing Key Laboratory of Topological Statistics and Applications for Complex Systems was officially inaugurated at the Beijing Institute of Mathematical Sciences and Applications (BIMSA) .The laboratory is established under the auspices of BIMSA and jointly co-constructed with the School of Mathematics of Renmin University of China. As a key emerging interdisciplinary research institution strongly supported by the Beijing municipal government, the laboratory aims to fill critical academic gaps in the field of topological statistics, promote the study and resolution of complex problems in the era of big data and artificial intelligence, and build a world-class research platform.
In response to the challenges posed by the age of big data and artificial intelligence, the establishment of the laboratory represents a proactive effort to address the unprecedented growth in data complexity. Traditional statistical methodologies exhibit clear limitations when dealing with high-dimensional, dynamic, heterogeneous, and noisy data, highlighting an urgent need for theoretical innovation and breakthroughs. Against this backdrop, topological statistics has emerged as a cutting-edge interdisciplinary field that integrates the strengths of topology and statistics, offering a novel perspective for tackling fundamental challenges in modern data analysis.
Beijing Key Laboratory of Topological Statistics and Applications for Complex Systems focuses on topological statistics within applied mathematics and aligns closely with major national strategic needs. By targeting the intrinsic properties of big data, the laboratory pioneers new approaches and constructs interdisciplinary modeling frameworks that integrate statistics with multiple branches of mathematics. It strives to achieve transformative breakthroughs in three major research directions:
- The development of a generalized statistical physics theory, integrating interdisciplinary elements such as evolutionary game theory and niche theory, to construct dynamic holographic interaction network models for high-dimensional data (idopNetwork), thereby uncovering the underlying laws and trends of complex systems;
- The establishment of new theories in topological statistics, introducing topological concepts and methodologies into the framework of statistical physics to enable precise characterization and analysis of high-dimensional data structures;
- The creation of novel statistical topology theories, developing topology-based analytical tools for complex networks with higher-order interactions, providing robust mathematical support for the study of complex systems across multiple domains.
The laboratory has already demonstrated successful applications at the intersection of topology and statistics. Building upon a new topological theory (GLMY theory) proposed by internationally renowned mathematician Professor Shing-Tung Yau, and combined with the idopNetwork statistical model developed by Professor Rongling Wu’s team, the laboratory leverages the topological properties of complex networks to investigate information transmission and functional regulation mechanisms in biological systems. This modeling framework has been successfully applied to metabolic network studies related to inflammatory bowel disease (IBD), leading to the proposal of a novel therapeutic strategy based on network-structure regulation. The results were published in PNAS and have received widespread international recognition.
Looking ahead, the Beijing Key Laboratory of Topological Statistics of Complex Systems is committed to building an integrated research pipeline that links theory, application, and translation across high-, mid-, and applied-level statistical research. The laboratory places strong emphasis on cultivating interdisciplinary talent with expertise spanning topology, statistics, and biomedicine.
On the theoretical front, it will develop a series of new theories and methodologies to analyze, characterize, and interpret big data, ultimately establishing a comprehensive theoretical system for topological statistics.
On the application front, the laboratory will employ these new theoretical tools—beginning with topological data analysis (TDA)—to uncover hidden natural and social laws underlying complex systems, strengthen computational simulation studies, and evaluate the robustness and efficiency of new methods.
On the translational front, the laboratory will develop software packages to promote the practical deployment of new methods, enabling real-world applications that generate economic, social, and ecological benefits.
The laboratory will focus on constructing and analyzing high-resolution biological network models, applying topological statistical methods combined with multi-scale integrative analysis to data spanning molecular to organismal levels, thereby achieving a comprehensive understanding of biological complexity and advancing personalized health management and precision drug design. At the same time, it seeks to extend the application of topological statistics to materials science, environmental science, economics, and other fields, providing innovative tools and methodologies for addressing real-world complex problems.
The laboratory is chaired by Professor Shing-Tung Yau as the Chair of the Academic Committee, with Professor Rongling Wu serving as Director and Professor Xinqi Gong as Deputy Director. The research team brings together leading scholars from biomedicine, algebraic topology, and computational science, including Professor Jie Wu, Professor Yuval Peres, Professor Shing-Tung Yau, and other world-class researchers. This internationally oriented and highly original team provides strong intellectual support for the laboratory’s long-term development.
The establishment of the Beijing Key Laboratory of Topological Statistics and Applications for Complex Systems marks a major breakthrough in this emerging field, filling important academic gaps while promoting advanced data-analysis methodologies. It will significantly enhance the ability to analyze and interpret complex datasets, strengthening Beijing’s and China’s leadership in big data technologies and applications. Moreover, its applications will further accelerate advances in artificial intelligence, machine learning, and biomedicine, supporting strategic development in intelligent healthcare and the health industry, and contributing Chinese insight and innovation to global scientific progress.