Curriculum Vitae

School of Systems Science

Beijing Normal University

Tel: +86-10-58807876(O), +86-18610014018(M)

E-mail: Jinshanw@bnu.edu.cn

• Education

  • 2011, PH.D. in Condensed Matter Physics, Department of Physics & Astronomy, University of British Columbia (UBC)
  • 2003-2004, one year in a PH.D. program in Simon Fraser University (SFU), and then transferred to UBC
  • 2006, M.Sc. in Condensed Matter Physics, Department of Physics & Astronomy, UBC
  • 2002, M.Sc. in Statistical Physics, Physics Department, Beijing Normal University(BNU)
  • 1999, B.S. in Physics, Department of Physics, BNU

• Employment

  • 2016-, Professor, School of Systems Science, BNU, Beijing, China
  • 2011-2016, Associate Professor, School of Systems Science, BNU, Beijing, China
  • 2004-2011, Teaching Assistant, Department of Physics & Astronomy, UBC
  • 2003-2004, Teaching Assistant, Department of Physics, SFU
  • 2002-2003, Lecturer and Research Associate, Department of Systems Science, BNU

• Professional experience

  • Professor

    • Teach Invitation to Systems Science, Learning How to Learn and Think
    • Study Quantum Transport and Non-equilibrium Statistical Physics, Scientometrics, Game Theory, Network Science

  • Associate Professor

    • 2012 Spring, Physics and Mathematics in Studies of Complexity II, graduate course, Department of Systems Science, BNU.
    • 2011 Fall, Physics and Mathematics in Studies of Complexity I, graduate course, Department of Systems Science, BNU.
    • 2011- , Non-equilibrium statistical physics and Quantum transport project, PI, funded partially by National Natural Science Foundation of China.
    • 2011- , Network-based learning strategies of Chinese characters, PI, not yet funded by any agencies.
    • 2012- , Study concept mapping technology and generate collections of concept maps, PI, funded partially by university research fund from BNU.

  • Lecturer

    • 2003, Math Model, undergraduate course, Department of Systems Science, BNU.
    • 2002, Econophysics, a course for graduate students, Department of Systems Science, BNU, 2002,9-2003,1. I designed and established this course from scratch. A review paper ([19] in the publication list) on Econophysics prepared for the class was post on arXiv. Since then many have used it as an introductory material for the subject.

  • Research Associate

    • 2002-2003, under Prof. Zengru Di's supervision, lead a team working on empirical studies of and modelling weighted complex networks
    • 2002-2003, help Prof. Zengru Di to organize a proposal for National Fund of Natural Science in China, The statistical properties of firm sizes and its theoretical model, funded at 2003,9.

  • Research Assistant

    • 2004-2011, as a graduate student in Prof. Mona Berciu's group, working on various projects related to quantum transport
    • 1999-2002, as a graduate student (master) in Prof. Zhanru Yang's group, during the later years of and one year after my graduation (2001-2003), I lead a team working on physical models on complex networks

• Skills in numerical computation

  • High-performance computational software: BLAS, Lapack, Petsc, Slepc, gsl, xmds
  • Programming language: C, Java, Linux shell script

• Award

  • University Graduate Fellowship (UGF) from UBC, 2006-2009
  • Graduate Fellowship from SFU, spring 2004
  • Canron Limited - Sidney Hong Memorial Grad Scholarship, Spring 2004
  • Westak International Sales Inc. Grad Scholarship in Expert Systems, Spring 2004
  • Scholarship for Excellent Graduate Students from BNU, 2000
  • Award for excellent undergraduate students from BNU, 1998

• Research Contribution

  • Relational Thinking (Lynkage) applied to scientometrics, economics, menaingful learning and the studies of systemmic safety

    Physics is all about interaction. By calculating indirect interaction from direct interactions, via such as Green’s function, physics, epsecially the field of statistical physics, establishs bridges between macroscopic behaviors and microscopic structures of systems. In fact, more generally, the idea and techniques of the combination of direct and indirect interactions, which we call relational thinking or lynkagem can be applied to systems beyond physical ones and it serves as the basic ways of thinking of systems science. It is natrually cross-disciplinary. We have applid this idea and related techniques to studies in physics, economics, scientometrics, language and learning, and the studies of systemmic safety, for instance

    • Lynkage applied to scientometrics, to reveal the interconnections among scientific fields[3，4，15]. Citations among papers can be used to reveal information of interdependence of scientific fields. If concept networks can be constructed from papers and their citations, this technique will even be able to help researchers to do better researches and to help R&D administrators to facilate a better development of science and technoligy.
    • Lynkage applied to the learning of Chinese characters[21]. Chinese characters are meaningfully connected to each other via their shapes, pronunciations, and meanings. We illustrate the basic idea and algorithms to make use of those connections to help teaching and learning Chinese characters better? We can use those connections both locally and systemmatically. Now we are working on experimental examination of the idea and the algorithms.
    • Lynkage applied to the studies of systemmic safety[6,7]. Disturbance, especially the propagation of destructive disturbances, is an important and typical problem in the security discipline. Our lynkage ideas and techniques can also play a role.

    It is one of my research pursuits and dreams to extend the above thinking mode and analysis method to other fields, so that as many researchers and research questions as possible can adopt it.

    Recently, based on our previous work of learning Chinese characters over the Chinese character network, and the concept of meaningful learning and concept maps of experts in education, especially David Ausubel and Joseph Novak, we have established the "Institute of Educationa System Science" (IESS) in the School of Systems Science at Beijing Normal University. We hope that the institute will carry out systematic and scientific educational research aimed at "helping teachers to teach better and helping students to learn better".

  • Quantum Transport

    In my Ph. D. work at UBC I aimed to establish a theoretical framework for finding the non-equilibrium stationary states of quantum systems starting mostly from first principles. Approaches exist for this problem such as the Landauer-Buttiker formula and the non-equilibrium Green's function method. We decided to use the open-system scenario, which is not widely used because of the difficulty in solving the resulting open-system master equation. Using direct methods, one needs to solve an eigenvalue problem of size 4^N where N is the size of the system measured in qubits. We first searched for efficient methods to solve this problem and then applications of this framework on physical models. The following lists several projects I have worked on.

    • Using a BBGKY-like method for solving the open-system master equation [21] the task of solving an eigenvalue problem of size 4^N becomes a problem of solving a linear system of size N² by converting the open-system master equation into linear equations of Green's functions. The equations of different Green's functions (single-particle ones, tow-particle ones and so on) are coupled. The cluster expansion, originally used for the equilibrium BBGKY method, is used to truncate the coupled equation. The accuracy of this method is around 2%.
    • The second order form of the BBGKY-like method requires solving a linear system of size N⁴ but improves accuracy even further. Such a form also gives the two-particle correlated Green's functions beyond the Hartree-Fock approximation. Manuscript in preparation.
    • A coherent-state representation approach was also explored to solve the above problem of size 4^N by simulating a stochastic differential equation with 2N complex variables by converting the open-system master equation into a generalized Fokker-Planck equation. Analytical expression of the non-equilibrium stationary states are derived for some systems. The accuracy of this method is around 6%. Manuscript in preparation.

  • Network Science and its application

    Network Science is all about interaction, such interaction that is beyond physical interaction and is not usually studied by physicists, such as how others' action and opinion act on your decision, how learning one concept can help you to learn other related concepts. Works in this direction concerns both the tools, concepts and methodologies about network, and the applications, how network concepts and methodologies can solve problems in other fields.
    • Network Science helps to improve learning Chinese[18] and science. Chinese characters are connected to each other meaningfully: One character quite often becomes a component of another character and it indicates meaning or pronunciation of the composed character. How often is such relation, how to present the relation, and how to make use of the relation in learning characters? Those are the questions we investigated in this work.
    • Network Science is applied to Scientometrics[12]. How one field of science affect another, how science lead to innovations in technology, can such questions be answered based on publication data, such as publication records from ISI and Patent database? Those are the questions we are trying to answer in this project.
    • Evolutionary model for weighted networks [22,26,28]: Inspired by social networks and the above weighted networks of econophysicists, a new model of weighted networks was proposed. It is based on local rules, which means that nodes in the network only need to know limited information about their neighbors and at most their next neighbors. That is in this model a data centers providing global information is not required. We went one step further and conjectured that the well-known mechanism of global preferential attachment (that the richest gets richer while the poorest gets poorer) can be an emergent phenomenon rooted from local rules. We tested and confirmed this conjecture on our own model and several others.

  • Quantum Game Theory[Preprint 3]

    In physicists' terminologies, classical games can be regarded as games based on classical objects. The state of the object changes according to players' choice of strategies. These strategies are described by operators acting on the object to modify its state. The final state of the object determines the payoff for every player. The coin flipping games is a perfect example of this picture. The coin is a classical two-state system, which is denoted by physicists as a mixture state of "heads" and "tails". Flipping and non-flipping correspond respectively to the Pauli matrixand identity matrix. A natural question then arises of what happens if the classical coin is replaced by a quantum spin.

    I found that the answer is very non-trivial: a probability distribution over the strategy space, which is the description of a general strategy in classical game theory, is no longer capable of describing games with quantum objects. A density matrix over a basis of the strategy space has to be used. The same transition happens from Classical Mechanics to Quantum Mechanics. A probability distribution is replaced by a density matrix, which allows superpositions while the former allows only probability summations.

  • Quantum Foundation[Preprint 1]

    Partially inspired by the above work on quantum game theory, I was motivated to study the difference between a probability distribution and a density matrix. Can the former be converted to the later equivalently or vice versa? Luckily I found that the same question has been asked and investigated by physicists on the question of validity of hidden variable theory. In a hidden variable theory, there is no superposition principle, but classical probability summations are allowed. In a sense, the hidden variable theory is searching for a map from a density matrix to a classical probability distribution.

    On one hand there is a theorem stating that all convex theories, which includes quantum mechanics, can be embedded into a classical probability theory with constraints (see for example, A. S. Holevo, Probabilistic and Statistical Aspects of Quantum Theory). On the other hand, Bell's inequality rules out all local hidden variable theories. The constrained classical theory has to be non-local. Of course many believe that physical theory should be local, but some are still willing to sacrifice locality. I investigated the question of what are the necessary intuitions, including for example the sense of locality, one has to give up in order to have such a classical theory for quantum systems. I found that there are many other unacceptable features of the classical theory by explicitly constructing such a theory for systems of one spin half and two spin halfs. Those unwanted features make the theory even harder to understand than the usual quantum mechanics.

• List of publications

  • Refereed Journals

    1. Menghui Li, Kai Liu, Yukun Song, Ming Wang and Jinshan Wu, Serial Interval and Generation Interval for Imported and Local Infectors, Respectively, Estimated Using Reported Contact-Tracing Data of COVID-19 in China, Frontiers in Public Health, 8, 942(2021). DOI:10.3389/fpubh.2020.577431
    2. Jinzhong Guo, Xiaoling Liu, Liying Yang, and Jinshan Wu. Are Contributions from Chinese Physicists Undercited? Journal of Data and Information Science 4(4) : 84-95(2019).
    3. Jinshan Wu. Infrastructure of Scientometrics: The Big and Network Picture, Journal of Data and Information Science, 4(4), 1-12 (2019).
    4. Zhesi Shen, Fuyou Chen, Liying Yang, Jinshan Wu, Node2vec Representation for Clustering Journals and as A Possible Measure of Diversity, Journal of Data and Information Science, 4(2), 79-92(2019), https://doi.org/10.2478/jdis-2019-0010 .
    5. Zhesi Shen, Liying Yang, Zengru Di, Jinshan Wu. Large enough sample size to rank two groups of data reliably according to their means. Scientometrics 118: 653-671 (2019). https://doi.org/10.1007/s11192-018-2995-0 .
    6. Kai Liu, Wang Ming, Weihua Zhu, Jinshan Wu, Xiaoyong Yan. Vulnerability analysis of an urban gas pipeline network considering pipeline-road dependency. International journal of critical infrastructure protection, 23, 79-89(2018). https://www.sciencedirect.com/science/article/pii/S1874548217300926 .
    7. Kai Liu, Ming Wang, Yinxue Cao, Weihua Zhu, Jinshan Wu, Xiaoyong Yan. A Comprehensive Risk Analysis of Transportation Networks Affected by Rainfall-Induced Multihazards. Risk Analysis 38. 1618-1633(2018). https://onlinelibrary.wiley.com/doi/abs/10.1111/risa.12968 .
    8. Xiaoling Liu, Mihai Păunescu, Viorel Proteasa, Jinshan Wu, Minimum Representative Size in Comparing Research Performance of Universities: the Case of Medicine Faculties in Romania, Journal of Data and Information Science, 3(3),32-42(2018), https://doi.org/10.2478/jdis-2018-0013 .
    9. An Zeng, Zhesi Shen, Jianlin Zhou, Jinshan Wu, Ying Fan, Yougui Wang, H Eugene Stanley. 2017. "The science of science: From the perspective of complex systems." PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS, 714, 1-74 (2017).
    10. Jinshan Wu, Is there an intrinsic logical error in null hypothesis significance tests? Commentary on: “null hypothesis significance tests. a mix-up of two different theories: the basis for widespread confusion and numerous misinterpretations”, Scientometrics 115: 621-625 (2018), https://link.springer.com/article/10.1007%2Fs11192-018-2656-3.
    11. Zhesi Shen, Liying Yang, Jinshan Wu, Lognormal distribution of citation counts is the reason for the relation between Impact Factors and Citation Success Index, Journal of Informetrics, 12(1), 153–157(2018). https://doi.org/10.1016/j.joi.2017.12.007
    12. Menghui Li, Liying Yang, Huina Zhang, Zhesi Shen, Chensheng Wu, Jinshan Wu, Do mathematicians, economists and biomedical scientists trace large topics more strongly than physicists?, Journal of Informetrics 11(2), 598-607(2017), https://doi.org/10.1016/j.joi.2017.04.004.
    13. Hongguang Dong, Menghui Li, Ru Liu, Chensheng Wu, Jinshan Wu, Allometric scaling in scientific fields Scientometrics 112, 583-594(2017). doi:10.1007/s11192-017-2333-y
    14. Zhenquan Lin, Shanci Hou, Jinshan Wu, The correlation between editorial delay and the ratio of highly cited papers in Nature, Science and Physical Review Letters, Scientometrics 107, 1457-1464 (2016) doi:10.1007/s11192-016-1936-z
    15. Zhesi Shen, Liying Yang, Jiansuo Pei, Menghui Li, Chensheng Wu, Jianzhang Bao, Tian Wei, Zengru Di, Ronald Rousseau, Jinshan Wu, Interrelations among scientific fields and their relative influences revealed by an input–output analysis, Journal of Informetrics 10, 82-97(2016). doi:10.1016/j.joi.2015.11.002
    16. Wenjie Dai, Xin Wang, Jinshan Wu, Logical gaps in the approximate solutions of the social learning game and an exact solution, PLoS ONE 9(12): e115706 (2014). doi:10.1371/journal.pone.0115706
    17. Zehui Deng, Jinshan Wu, and Wenan Guo, Renyi information flow in the Ising model with single-spin dynamics, Phys. Rev. E 90, 063308 (2014), http://dx.doi.org/10.1103/PhysRevE.90.063308
    18. Qiang Zhang, Tianxiao Qi, Keqiang Li, Zengru Di and Jinshan Wu, Games on graphs: A minor modification of payoff scheme makes a big difference EPL 107 10002 (2014) doi:10.1209/0295-5075/107/10002
    19. Qian Zhuang, Zengru Di, Jinshan Wu, Stability of Mixed-Strategy-Based Iterative Logit Quantal Response Dynamics in Game Theory, PLoS ONE 9(8): e105391 (2014). doi:10.1371/journal.pone.0105391
    20. Tian Wei, Menghui, Li, Chensheng Wu, Ying Fan, Zengru Di, Jinshan Wu, Do scientists trace hot topics?, Scientific Reports, 3, 2207 (2013), DOI: 10.1038/srep02207.
    21. Xiaoyong Yan, Ying Fan, Zengru Di, Shlomo Havlin, Jinshan Wu, Efficient learning strategy of chinese characters based on network approach, PloS ONE, 8, e69745 (2013) DOI: 10.1371/journal.pone.0069745.
    22. Jinshan Wu and Mona Berciu, Heat transport in quantum spin chains: the relevance of integrability, Phys. Rev. B 83, 214416 (2011).
    23. Jinshan Wu and Mona Berciu, Kubo formula for open finite-size systems, Europhysics Letters, 92(2010), 30003.
    24. Jinshan Wu, Non-equilibrium stationary states from the equation of motion of open systems, New Journal of Physics, 12(2010), 083042.
    25. Menghui Li, Liang Gao, Ying Fan, Jinshan Wu and Zengru Di, Emergence of global preferential attachment from local interaction, New Journal of Physics, 12(2010), 043029
    26. Yanqing Hu, Jinshan Wu and Zengru Di, Enhance the efficiency of heuristic algorithms for maximizing the modularity Q, Europhysics Letters, 85(2009), 18009
    27. Ying Fan, Menghui Li, Peng Zhang, Jinshan Wu and Zengru Di, The effect of weight on community structure of networks, Physica A, 378(2007), 583-590.
    28. Ying Fan, Menghui Li, Peng Zhang, Jinshan Wu and Zengru Di, Accuracy and precision of methods for community identification in weighted networks, Physica A, 377(2007), 363-372.
    29. Menghui Li, Jinshan Wu, Dahui Wang, Tao Zhou, Zengru Di and Ying Fan, Evolving model of weighted networks inspired by scientific collaboration networks, Physica A, 375(2007), 355-364.
    30. Menghui Li, Ying Fan, Dahui Wang, Daqing Li, Jinshan Wu and Zengru Di, Small-world effect induced by weight randomization on regular networks, Physics Letters A, 364(2007), 488-493.
    31. Menghui Li, Dahui Wang, Ying Fan, Zengru Di and Jinshan Wu, Modelling weighted networks using connection count, New Journal of Physics, 8(2006), 72.
    32. Peng Zhang, Menghui Li, Jinshan Wu, Zengru Di and Ying Fan, The analysis and dissimilarity comparison of community structure, Physica A, 367(2006), 577-585.
    33. Menghui Li, Ying Fan, Jiawei Chen, Liang Gao, Zengru Di and Jinshan Wu, Weighted networks of scientific communication: the measurement and topological role of weight, Physica A, 350(2005), 643-656.
    34. Ying Fan, Menghui Li, Zengru Di, Jiawei Cheng, Liang Gao, and Jinshan Wu, Networks of Econophysicists, International Journal of Modern Physics B, Vol. 18, Nos. 17-19 (2004) 2505-2511.
    35. Jingzhou Liu, Jinshan Wu and Z. R. Yang, The spread of infectious disease on complex networks with household-structure, Physica A, 341(2004), 273-280.
    36. Jinshan Wu and Zengru Di, Complex networks in statistical physics, Progress in Physics (Chinese), 24-1(2004), 18-46.
    37. Jinshan Wu, Zengru Di and Zhanru Yang, Division of labor as the result of phase transition, Physica A, 323(2003), 663-676.
    38. Jinshan Wu, Jingdong Bao and Zhanru Yang, Improved Metropolis method for systems with discrete states, Chinese Journal of Computational Physics, 19-2(2002), 103-107.

  • preprints on arXiv

    1. Jinshan Wu and Shouyong Pei, Could a Classical Probability Theory Describe Quantum Systems?, arXiv:quant-ph/0503093.
    2. Yougui Wang, Jinshan Wu and Zengru Di, Physics of Econophysics, arXiv:cond-mat/0401025.
    3. Jinshan Wu, A series of papers on Game Theory: A new mathematical representation of Game Theory I, II arXiv:quant-ph/0404159, arXiv:quant-ph/0405183.

  • Funded Projects

    1. Evaluation of research papers based on their contents, concept map of the discipline and an impact propagation algorithm, NSFC, 2021-2024.
    2. Solving quantum master equations in coherent-base representation, NSFC, 2013-2015.
    3. Second order BBGKY solution of quantum master equations, China Scholarship Council, 2012-2014.
    4. Content-based Scientometrics, Beijing Institute of Science and Technology Information, 2013-2016.

  • Published books

    1. Jinshan Wu, Teach Less, Lean More (in Chinsese), Posts & Telecom Press, 2017
    2. Jinshan Wu, Quantum Mechanics of two-level systems (in Chinese), Chinese Science Press, 2017
    3. Jinshan Wu, Invitation to Systems Science (in Chinese), Chinese Science Press, 2018

  • Taught courses

    1. Quantum Mechanics
    2. Mathematical Modeling
    3. Learning How to Learn and Think
    4. Invitation to Systems Science
    5. Advanced Statistical Mechanics

  • Talks, Public Lectures and Conference Presentations

    1. “Lynkage=Connections¹+Connections²+Connections³+...”, a lecture for general public, August 2016
    2. “Fun with Physics: Experiments and Thinking”, a public lecture for kids 8-16 years, July 2015
    3. “Thinking in Terms of Relations: Concept Mapping”, a public lecture for elementary school students, multiple times, various places
    4. “Teach Less, Learn More with Concept Mapping and Concept Maps” a public lecture/workshop for school teachers, multiple times, various places
    5. Talk at APS March Meeting 2009, Heat transport in quantum spin chains: the relevance of integrability, March, 2009
    6. Invited talk at Beijing Normal University, games on quantum objects, Aug. 2007
    7. A presentation file for a talk on Quantum Games in Math@SFU, for non-physicists
    8. an outline for a talk on Quantum Games in Phas@UBC, for physicists
    9. A talk on Quantum Games for "Complex systems forum in Shanghai" (PDF, in Chinese)
    10. A presentation on quantum games in the "Internaltional conference on Econophysics in Shanghai"(PDF, in English)
    11. A lecture note (in PDF, in Chinese) for "BNU summer school on Complex Systems" : Games on Quantum Objects: from the viewpoint of a second-year undergraduate

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