Department of Economic and Social Statistics
The Department of Economic and Social Statistics has been reputed as the traditional advantage of research and teaching since the discipline of Statistics was formed in September 1950. It is regarded as one of the pillars supporting the School’s top position in Statistics in China. The Department offers Bachelor’s, Master’s and Doctoral Degrees in Economics. The Department’s strong research areas include the system of national accounting, macro-economic statistics, official statistics, innovation study, industrial competitiveness, text mining and big data application, and market research. It collaborates with the United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (UNU-MERIT), Vrije Universiteit Brussel (VUB), and the University of Pisa.
Apart from research, the Department also offers the course of Statistics for non-statistics majors in the University and leads the research and administrative work of the NBS-RUC Research Data Center and the Institute of Official Statistics co-funded by the National Bureau of Statistics and the University. A unique advantage of the Department is the long-term close relations with the central government ministries and institutions like the National Development and Reform Commission, Ministry of Commerce, National Bureau of Statistics, People’s Bank of China, and General Administration of Customs in official statistics. The Department has already developed its features in designing sampling programs, analyzing data, and supporting policymaking in the State governance.
Department of Risk Management and Actuarial Science
The Department of Risk Management and Actuarial Science is formerly known as the Teaching Research Section of Risk Management and Actuarial Science. In 1992, we established the Risk Management and Actuarial Science Program, which is one of the earliest actuarial education and research programs in China. The Society of Actuaries (SOA) has recognized our Actuarial Science program as a UCAP-AC program (Universities and Colleges with Actuarial Programs: Advanced Curriculum) since 2016. Our Actuarial Science Program won the 2018 CAS University Award.
At present, the Department consists of eight faculties, and offers Bachelors, Masters and Ph.D. programs in Risk Management and Actuarial Science. The Department has obtained great achievements in actuarial theory researches and insurance applications. At the same time, the Department has trained many capable graduates who have become chief actuaries in several Chinese insurance companies.
The faculties consistently collaborate with insurance companies and actuarial institutions, such as PICC, Swiss Re, China Association of Actuaries, CAS, SOA, etc. We have the leading researches in life insurance, annuity, pension, agriculture insurance, general insurance, optimal reinsurance, financial risk, catastrophe risk, insurance solvency, actuarial data science, etc. In the future, our researches will continue to interact with statistical theories and data science technologies to address challenges in actuarial science faced by China and the world; our education will continue to train actuarial students with multiple skills.
Department of Mathematical Statistics
The Department of Mathematical Statistics, formerly known as the Teaching Research Section of Statistics and the Teaching Research Section of Probability and Mathematical Statistics, was founded in 1998 as a traditional statistic teaching and research team of Renmin University of China. After several generations of hard work and unremitting efforts, it has developed into a professional base for teaching, scientific research and talent training of probability statistics, sampling theory, and complex data analysis with a solid foundation in China.
At present, the Department consists of nine teachers, with Master’s and Doctoral programs in Statistics and Mathematics. All teachers and students uphold the fine tradition of rigorous scholarship, the pursuit of excellence, hard work, and courage to contribute, actively carry out practical and innovative teaching activities, and strive to climb the peak of science. Professor Dai Shiguang, a famous statistician, is an academic leader of the older generation of probability theory and mathematical statistics and enjoys a high reputation in the domestic statistical field. Now, many outstanding young and middle-aged teachers are also emerging, rapidly growing into the backbone of teaching and scientific research. Through long-term exploration and repeated practice, they have gradually formed a unique academic style and school running characteristics and accumulated fruitful scientific research and teaching achievements. In probability theory and method, sampling theory and mathematical statistics, which have traditional advantages and innovative ability, the results are particularly remarkable. To meet the needs of discipline construction in the new era, in recent years, our research has been expanding to the international frontier field, forming cooperation research with many famous international universities. The main directions include random analysis, high-frequency data, high-dimensional data model, complex sampling theory and application, and network data analysis.
Department of Biostatistics and Epidemiology
The Department of Biostatistics and Epidemiology, School of Statistics, Renmin University of China, was established in June 2020. Its predecessor is the Teaching and Research Section of Medical and Biological Statistics, founded in April 2006. It is dedicated to teaching and researching of statistical methods in the fields of public health and biomedicine.
Epidemiology and health statistics are essential subjects in medical science. As more epidemiological data appears, the combination of epidemiology and statistics is becoming increasingly important. Under this background, the major of Epidemiology and Health Statistics of the Renmin University of China was born in 2006 and qualified to award students Master’s Degrees in Medicine. With the deepening of China’s marketization, informatization, and internationalization, more and more demands are put forward on quantitative analysis. This subject, as a combination of statistics and epidemiology, plays a prominent role in scientific management and decision-making. The master students are widely required in pharmaceuticals, hospitals, and many other fields. Since founded of this major, there are more than ten graduating classes with Master’s Degrees in Medicine. In June 2020, the Teaching and Research Section of Medical and Biological Statistics upgraded to the Department of Biostatistics and Epidemiology. It will be of great practical and long-term significance to improve the quality and level of talent, intersection, and integration of multi-disciplinary in China.
Department of Data Science and Big Data Analytics
The Department of Data Science and Big Data Analytics at the Renmin University of China was officially launched in 2020. It was originated from the initiative of the five-university joint master program on big data analytics in 2014 and the undergraduate program in data science and big data technology in 2017. Our mission is to educate future data scientists. We dedicate to providing a solid foundation in data science for students with specialized domain knowledge such as business analytics, financial technology, health informatics, engineering systems, mathematics, and computer science. We embrace the opportunities and challenges to develop a world-class center of data science with lasting regional and global impact on society.
Our research interests include but are not limited to, big data mining and statistical machine learning, text mining, consumer behavior big data analysis, deep learning, distributed computing methods, spatial-temporal big data analysis, and large-scale knowledge graph. Our research papers are published on many leading international computer and statistical journals. We are conducting many research projects for government and companies.
We offer the following courses to our students: probability theory, mathematical statistics, statistical computing, machine learning, data science practice, and big data distributed computing.
