•     Dr. Quan-lin Li received his doctorate degree from Institute of Applied Mathematics, Chinese Academy of Sciences, Beijing in 1998. After then, he was an associate professor at the State Key Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing from July 1999 to December 2003. From December 2003 to October 2009, he was an associate professor at Department of Industrial Engineering, Tsinghua University. From October 2009 to January 2019, he was a full professor at School of Economics and Management, Yanshan University. Up to now, he has been a full professor at the School of Economics and Management, Beijing University of Technology.


        Since September 1999, Quan-lin Li has visited in some universities such as Winnipeg University in Canada, Carleton University in Canada, University of Hong Kong, Hong Kong University of Science and Technology, Chinese University of Hong Kong, Complutense University of Madrid in Spain, University of Macau and so forth. His research interests include stochastic models, Stochastic processes, queuing networks, Markov decision processes, game theory, computer networks, network security, network resource management, network entropy decision-making, mean-field theory, nonlinear Markov processes, supermarket models, work stealing models, RFID technologies, Internet of Things, big data, cloud computing, blockchain, data center networks, healthcare,  COVID-19 stochastic modeling, bike sharing systems, sharing economy,supply chain management and so on.


         For his theoretical research, Li Quan-Lin systematically developed The RG-factorization method of stochastic models, and set up the basic theory of RG-factorizations. By using RG-factorization method, it is lucky to be able to solve some difficult and complicated stochastic systems, such as queuing networks, computer networks, network security, Internet of Things, cloud computing, data center networks, stochastic modeling of blockchain, inventory control, sharing economy, bike sharing systems, and healthcare systems. The RG-factorizations strongly support performance evaluation, optimization and dynamic decision, risk management and others, and also provide effective computational methods and algorithms for  dealing with large-scale or complex-structured stochastic models with numerical platforms. On this research line, Quan-Lin Li published an English monograph Constructive Computation in Stochastic Models with Applications: RG-Factorizations by Springer, the first edition in 2010, and the second edition in 2021.



  • [1] National Natural Science Foundation of China. Research on black hole effect, multi-stable domain and networking resource loss evaluation of large-scale networks. 2017.01-2020.12.

    [2] National Natural Science Foundation of China. Nonlinear Markov process and super-exponential structure of supermarket networks under real-time queuing control. 2015.01-2018.12.

    [3] National Natural Science Foundation of China. Research on random load balancing strategy and supermarket models of large-scale parallel queuing network. 2013.01-2016.12.

    [4] National Natural Science Foundation of China. Research on multi-level approximation methods of self-similar networks and their performance models. 2009.01- 2011.12.

    [5] National Natural Science Foundation of China. Stochastic models in network security and key techniques for performance evaluation. 2007.01-2009.12.


    [6] National 973 Program (Tsinghua Sub-project). Stochastic methods in life science and network technologies. 2007.01-2011.12.

    [7] National Natural Science Key Fund Project (Tsinghua Sub-project). Design, construction, modeling and analysis of engineering gene regulatory networks. 2008.01-2011.12.


    [8] Hebei Natural Science Foundation Project. Research on multi-chain coupled queuing network and medical insurance incentive mechanism of hierarchical diagnosis and treatment and two-way referral. 2018.01-2020.12.

    [9] Hebei Higher Education Innovation Team Leading Talent Program. Research on nonlinear calculation of large-scale network and risk           management of port coal supply chain management. 2014.01-2016.12.

    [10] Hebei Natural Science Foundation Project. Research on hierarchical calculation and data management technologies for multi-dimensional                 stochastic models in network security. 2012.01-2014.12.

  • 2018

    Award Name: Best Paper Award.  The 7th International Conference on Computational Data and Social Networks.

    Paper Name: Blockchain Queue Theory

    Authors Name: Quan-Lin Li, Jing-Yu Ma, Yan-Xia Chang


    Award Name: International INFORMS Paper Award

    Paper Name: Operational Performance Evaluation of Reverse Referral Partnership in the Chinese Healthcare System

    Authors Name: Na Li, Nan Kong, Quan-Lin Li, Zhibin Jiang


    Award Name: The Second Prize of Hebei Science and Technologies (Natural Science)

    Project Name: Research on Basic Theory of Numerical Calculation of Multidimensional Stochastic Models

    Award Winners: Quan-Lin Li, Chuang Li, Na Li, Nai-shuo Tian


    Award Name: The Leading Talents Program of the Innovation Team of Hebei Higher Education Institutions

    Project Name: Research on Nonlinear Calculation of Large-Scale Supermarket Network and Risk Management of Port Coal Supply Chain Management

    Award Winner: Quan-Lin Li


    Award Name: The Second Prize of Beijing Science and Technologies (Natural Science)

    Project Name: Basic Research on Computer Network Service Quality (QoS) Evaluation and Control

    Award Winners: Chuang Li, Feng-yuan Ren, Hao Yin, Quan-Lin Li 


    Award Name: The First Prize of the Ministry of Education Science and Technologies (Natural Science)

    Project Name: Stochastic Models and Performance Evaluation of Computer Systems

    Award Winners: Chuang Li, Quan-Lin Li, Hao Yin, Feng-yuan Ren, Zhi-guang Shan, Zhang-xi Tan, Ya-ya Wei, Yang Qu


    Award Name: New Century Outstanding Talents of the Ministry of Education

    Project Name: Research on the Calculation Method of Stochastic Network

    Award Winner: Quan-Lin Li




    Award Name: Excellent courses in Beijing

    Course Name: Operations Research

    Award Winners: Xiaobo Zhao (Stochastic models), Hongxuan Huang (Optimal theory), Quan-Lin Li (Decision method)


  • 2012, 2014, The 8, 9th International Conferences on Matrix-Analytic Methods in Stochastic Models. Technical Programme Committee, TPC member 


    2007-2019, The 7, 8, 9, 11, 12th International Workshop on Retrial Queues. Technical Programme Committee, TPC Chairman or member 


    2015-Now, The 14, 15, 16, 17, 18, 19, 20th International Conference (hosted in Russia) on Information Technology and Mathematical Modeling. International Program Committee, TPC member


    2006-2017, The 3th to 12th International Conference on Queueing Theory and Network Applications. Technical Programme Committee, TPC member


    1999-Now, The Vice Chairman, the Reliability Society of China Operations Research Society

    2008-Now,  The Commentator of the American MathSciNet. Reviewer


    The 8th International Workshop on Retrial Queues Conference. Chairman


    The 12th International Conference on Queueing Theory and Network Applications Conference. Chairman.

    • Stochastic Models

      In the study of stochastic models, our works focus on setting up a unified theoretic framwwork through using the RG-factorizations of, such as, Markov processes, Markov reward processes, Markov decision processes, stochastic games, evolutionary game and so forth.  See Li's 2010 book: Constructive Computation in Stochastic Models with Applications: The RG-factorizations. Springer.

      0 2021-09-29
    • The censoring technique

      The censored Markov chain, also called watched Markov chain, was first considered by Lévy [1951, 1952, 1958]. Since then, the censored Markov chains have been very useful in the study of Markov chains. Kemeny, Snell and Knapp [1976] applied the censoring technique to show that each recurrent Markov chain has a positive regular measure unique to multiplication by a scalar. Freedman [1983] used the censoring technique to approximate countable Markov chains for the limiting behavior.

      0 2021-09-29
    • RG-factorizations

      Using the censoring technique, we systematically devoloped two types of RG-factorizations. These RG-factorizations are very useful in the study of, such as, QBD processes, Markov processes, Markov renewal processes, Markov reward processes, Markov decision processes, stochastic game theory and their practical applications. Our recent works indicate that the two types of RG-factorizations play a different important role in the study of stochastic models.

      0 2021-09-29
    • QBD processes

      QBD processes with either finitely-many levels or infinitely-many levels have provided a useful mathematical tool in the study of stochastic models, such as queueing systems, manufacturing systems and computer networks. Chapter 3 of Neuts [1981] gave a complete picture of level independent QBD processes. Li's 2010 book provides a detailed analysis for level dependent QBD processes and various useful generalized models.

      0 2021-09-29
    • Block-structured Markov renewal processes

      Block-structured Markov renewal process is a generalization of Markov renewal process. The block-structured Markov renewal process was given a detailed analysis in Li and Zhao [2004] and Chapter 7 in Li's 2010 book: Constructive Computation in Stochastic Models with Applications: RG-Factorizations.

      0 2021-09-29
    • Markov reward processes

      Markov reward processes can accurately model practical systems that evolve stochastically over time. A Markov reward process consists of two elements: A Markov environment and an associated reward structure. Chapter 11 in Li's book (Constructive Computation in Stochastic Models with Applications: RG-Factorizations) provides an excellent survey on this research direction.

      0 2021-09-29

Name:  Quan-Lin Li  (李泉林)
Degree:    Ph D.
Position:  Professor
                School of Economics and Management

Address:  Beiijing University of Technology, Beijing 100124, China
Phone:     86-13521978091 
Email:       liquanlin@tsinghua.edu.cn           liquanlin@bjut.edu.cn



dblp-Computer Science 


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