I am a professor of physics and systems science in the School of Systems Science at Beijing Normal University. Currently I am working in quantum transport, game theory, scientometrics, general input-output analysis, Chinese characters and more general learning theory (The latter three might be seen as applications of network science to problem solving in various disciplines).
Supervising actively graduate students and post-docs.
Physics is all about interactions. It is also interaction that makes the world diverse (instead of homogeneous), beautiful and worth studying. Statistical physics starts from theories and their related computational techniques for collections of non-interacting units (thus non-interacting systems) and then moves to dealing with interacting systems, where one unit of the system is connected to others. Dealing with such interactions at microscopic level is called mechanics (we have classical and quantum mechanics), while dealing with such interactions at macroscopic level, sometimes phenomenologically, is called thermodynamics, and here comes the statistical mechanics or statistical physics when asking for the bridge between the micro and the macro level.
First major theme that I am working on is theoretical and computational foundations of statistical physics: why the Boltzmann distribution is valid for equilibrium statistical systems and what is the correspondence for non-equilibrium but still stationary systems, especially when the system has quantum nature and is interacting?
Second, beyond physics objects, there are other interacting systems, can the theories and computational techniques from statistical physics be applied to them, such as interactions among rational (full or partial) and intellectual agencies. This is where I started to look into game theory, a theory about agencies, which are quite often human being, with conflicting interests.
There are other more general interacting systems too, such as a collection of Chinese characters (they are different from a collection of light bulbs), a set of research papers, a set of all kinds of industrial products, a set of science concepts. This drives me into the third topic that I am actively working on now and hopefully for the future: network science and its application to (also back action from) scientometrics, knowledge management, meaningful learning and input-output analysis.
Recently, inspired and developed from our previous studies on applications of network science, or big physics, or systems science, to scientometrics, knowledge management, meaningful learning, and input-output analysis, we have established the Institute of Educational System Science (IESS) to work a new model of education and also a new model of scientometrics. Please visit the IESS website for more details.
Sometimes, my thoughts get stuck in foundations of quantum mechanics too. It is such a fascinating field and it drives me into excited states all the time.
I enjoy reading and working on creative questions which also have fundamental importance -- those might improve our understanding of the world, natural or social. I like those even more if results/methods developed from those investigations have some practical potential.
Here are the more detailed description of each topic.
A new model of Education, to help teachers to teach better and to help students to learn better (IESS website）
The task and methods to construct a human knowledge highway (concepts and links between concepts extracted from textbooks and research papers, levels of knowledge annotated）
Algorithms over the human knowledge highway for optimal learning orders and for efficient diagnostical tests
Behaviral studies and neuroscience studies of meaningful learning in Lab
Experimental studies of meaningful learning in classrooms
The task, methods and system of annotating the levels of teaching and learning
The final product "Lynkage Academy": learning resources (textbooks, course vidoe, homework questions, projects) attached to the human knowledge highway, algorithms aided, plus personalized help from teaching and learning experts, for teachers/students to teach/learn better
The task and methods to construct a human knowledge highway (concepts and links between concepts extracted from textbooks and research papers, levels of knowledge annotated, papers attached to concepts and links of the human knowledge highway, also including information on academic genealogy and citations）
Algorithms over the human knowledge highway to help scientists to identify research questions and methods
Algorithms over the human knowledge highway to help R&D administrators to do better management of science and technology researches and development
Test the algorithms via possible experiments or retrospective historical studies
The final product “Lynkage Research”:Scientisits, scientific data and publications attached to human knowledge highway, algorithms aied, for scientists to perform better researches
Operator Representation, also named as Hamiltonian Formalism, of Game Theory (PDF file of the revised manuscript): The old but detailed version of this general framework: A new mathematical representation of Game Theory, I, exemplified (PDF); A new mathematical representation of Game Theory, II, mathematical version, Definition and proof of Nash Equilibrium in the operator representation, and Quantum Nash Proposition (PDF)
General input-output analysis: concept network and learning, Learning of Chinese characters, Scietometric, input-output analysis in Economics, Flux Balance Analysis
Miscellaneous ( ^_^, no review and no projects, just idea, let me wish they will become projects one day )
Structural Chinese: Chinese is a language with many structures at all levels, from radicals to Chinese characters and from characters to words. We may discover them through the network analysis and make use of them in teaching Chinese via designing better textbooks.
Times Series Analysis of Music: Times series analysis of sounds and songs gives us pitches and notes, what we can see from a time series analysis of those sequences of pitches?
Thinking in Universal Language: Computers speak machine-dependent binary languages. But they communicate and we communicate with them too via high-level programming languages. Human being speaks different languages and every individual thinks in its own languages, which sometimes appears to be its native language. Thinking in its own does not pick up which language to use, but most time it relies on certain languages. This seems very much like the relation between the abstract vectors in Hilbert space and their explicit representations whenever we write them down to manipulate them. So could human being think and communicate via a common language, the one corresponding to the abstract vectors, not any representations? If possible, what are the features of such common language, which carries thoughts directly not via any social languages?
If you are interested in any of those not-yet-started projects and you think you might proceed faster than me, I am happy to share my thoughts.
If you are looking for a PH.D., a post-doc position, or even a faculty position in physics (with specialty in quantum transport, statistical physics), systems science (with specialty in game theory, scientometrics, natural language processing, input-output analysis) or mathematics (with specialty in numerical linear algebra, stochastic process), please send me an email or visit this web page.
