1. Complex Engineering Management

In this direction, SME is oriented towards the national strategic needs, focusing on the interactive research on the theory and practice of construction management of Type-One complex major projects. Through engagement in large research projects, it raises new research questions and develops innovative theoretical research. In this way, SME gradually develops a Chinese discourse system of major engineering management theories on this discipline. In view of the complexity of major projects, it has applied the complex system theory to carry out research on the basic theoretical system of major project management, and its faculty members have led and completed a number of general, key, and major projects of the National Natural Science Foundation of China. 

Professor Sheng Zhaohan’s Fundamental Theories of Mega Infrastructure Construction Management (English edition) was published in Springer International Series on Operations Research and International Science as not only an important theoretical achievement with independence and originality in the current theoretical research of engineering management, but also a significant contribution of China’s engineering management studies to the progress of international engineering management theories. In the meantime, the SME faculty has actively transformed research results in this field into guiding principles in practice. Apart from directly serving such major projects as Guangle Expressway and Hong Kong-Zhuhai-Macao Bridge, they have also made recommendations to the State Council for internal reference on issues such as the pollution treatment at Taihu Lake, construction of the Bohai Bay Passage, and risk prevention and control strategy of major projects of the Belt and Road Initiative. These research results have won by multiple times the first prize of the Science and Technology Progress Award by the Ministry of Education, the special prize of China Highway and Transportation Society, and the special prize of the Science and Technology Progress Award of Guangdong Province. 

Now, facing the implementation of big data technology and “new infrastructure” strategy, the faculty is actively integrating big data, block chain, artificial intelligence, and other technologies to carry out theoretical research and practice of intelligent engineering construction and operations management.

2. Operations and Supply Chain Management

In this direction, SME strives to meet the needs of manufacturing and service systems, relies on technologies and methods like optimization, information, system, and control, and conducts theoretical and applied research on behavioral decision-making and intelligent logistics management in operations and supply chain management. It prepares students for senior operations management who are inter-disciplinary and can effectively plan, organize, implement, and control the operations process.

The faculty members in this direction have made a series of important achievements in theoretical research, practice, and education, well regarded at home and abroad and widely recognized by colleagues. Professor Shen Houcai was selected as a member of the Teaching Guidance Committee of College Industrial Engineering under the Ministry of Education from 2019 to 2022. Professor Xiao Tiaojun has been selected as one of the Highly Cited Chinese Researchers in decision sciences by Elsevier for four years in a row. Professor Li Jingquan established CMST Nanjing Intelligent Logistics Co., Ltd. as a founder to carry out research and practice of intelligent logistics and provides consulting and decision-making services for CMST Intelligent Transportation, with great contributions to the rapid development of the enterprise and significant economic and social benefits. Professor Li has thus won honors including Top Ten Individuals in Chinese Logistics of the Year by China Federation of Logistics and Purchasing and the first prize of the Science and Technology Progress Award of the same organization for many times. Young faculty members have won prizes such as the Science and Technology Award for Young Researchers of the Operations Research Society of China, the Best Paper Award of the International Consortium of Chinese Mathematicians, and the champion of the Global Optimization Challenge hosted by JD.com, as well as honors of being selected into the Outstanding Young Scholars in Social Sciences Project of Jiangsu Province and the Young Talents Supporting Project of the China Association for Science and Technology.

3. Financial Technology and Financial Engineering

In this direction, SME upholds the goal of preparing for the development of the time and conducting research based on the major needs of the country and major problems of society, being oriented towards the international academic frontiers and trying to cultivate high-level personnel and create new theories in the fields of capital market, commercial banking, and financial technology. In this way, the school seeks to promote the healthy development of China’s financial industry.

The faculty in this direction is one of the earliest teams in China to conduct behavioral finance research and has been serving the Chinese capital market for a long time. The faculty has worked with the China Securities Regulatory Commission, the Shanghai Stock Exchange, and the China Financial Futures Exchange on more than 20 projects, participated in the formulation and revision of regulatory policies and securities trading regulations and guidelines, and made significant contributions to the design of landmark mechanisms and products in the Chinese capital market including the Shanghai-Hong Kong Stock Connect, the Shanghai-London Stock Connect, 50 ETF options, and the Science and Technology Innovation Board. As the supporting unit of Jiangsu Provincial Think Tank of the Science and Technology in Finance, SME has undertaken the formulation and promotion of the Jiangsu Provincial Plan for Science and Technology in Finance during the 12th and 13th Five-Year Plans and participated in the formulation of Nanjing Municipal Finance Plan, providing strategic foresight and feasible policy recommendations for the construction of a new system of science and technology in finance in Nanjing and Jiangsu Province and achieving good social benefits. Considering the needs of economic development in Jiangsu Province, SME proposed to issue ETF products for services in Jiangsu Province with Huatai Securities as the platform and achieved results highly rated by the CPC Jiangsu Provincial Committee.

4. Smart Manufacturing and Decision Intelligence

The rapid development of big data and artificial intelligence has had a huge impact on the management discipline and also brought new ideas for solving management problems. In this direction, SME focuses on machine learning, data analysis, and optimization methods. It strives to meet the development needs of management theories and technologies under the big data environment, and it studies optimization and decision-making methods with wide applicability based on cyber-physical systems and has achieved well regarded innovative results. Meanwhile, SME carries out inter-disciplinary applied research, especially on the issues of management optimization under the new manufacturing production modes and has produced large social benefits in defense and national security, intelligent manufacturing, and intelligent agriculture.

To solve large-scale non-separable convex optimization problems in management, finance, and engineering, the faculty in this direction has converted them into a series of sub-problems that are easier to solve with lower dimensions and designed relevant practical numerical algorithms. It has laid a foundation for management theory research and application practice in the big data environment and developed several core optimization ideas and algorithms in the field of big data analysis. The results have received wide attention from scholars at home and abroad. The faculty has been long engaged in data-driven uncertain reasoning and decision-making as well as the theory and technology of command and management in hybrid human-computer systems, with large academic and social influences in related fields. 

In addition, reinforcement learning methods have developed rapidly in recent years, especially in combination with deep learning, and it has been considered one of the ways to achieve general artificial intelligence and an important method to solve optimization decision problems (especially Markov decision problems) for management application. The research team in this direction is one of the earliest teams engaged in reinforcement learning research in China, and its quantum reinforcement learning methods and incremental reinforcement learning methods are not only applied to human behavior learning and operations optimization, but also widely used in other inter-disciplinary fields, providing efficient and feasible solutions to optimization and decision-making problems in open, dynamic, and complex environments.