With increased demand for Big Data research and talents in national economic and social development, and under the guiding principle of integrating statistics and data science and combining theoretical research and practical application, the laboratory has established the following four research directions:

 (1) Statistical Machine Learning

Study basic theories and methods of statistical machine learning for Big Data, develop and improve the theoretical foundation and methodology of Big Data analysis, based on the three main characteristics of Big Data—massive amounts of data, complexity and low value density, and integrate the features and advantages of statistics and data science disciplines.

 (2) Statistical Calculation of Big Data

Explore concrete implementation and calculation methods of relevant statistical theories in the face of massive amounts of data, study convergence theory, computational complexity theory and algorithm effectiveness theory of relevant algorithms, and implement a statistical machine learning toolset based on a Big Data processing platform.

 (3) Big Data Knowledge Project

Driven by applications and based on Big Data statistical theories and methodologies, research data management, knowledge map construction and knowledge base-based service navigation, to achieve a leap from data to knowledge, and ensure effective transformation from Big Data statistical theory to data science, and from data science to data engineering.

 (4) Application of Intelligent Decision-making

Keeping in mind various challenges such as high complexity, incomplete information, redundancy, diversification and fragmentation during the problem resolution decision-making process, research on Big Data-based intelligent decision-making theories and methodologies, integrate superior discipline resources of East China Normal University and facilitate in-depth application of research results in the fields of finance, education, medicine, ecology and industry.