张江 - 北京师范大学 - 系统科学学院

个人简介

Work Experience 2017.7~present Professor, School of Systems Science, Beijing Normal University. Teaching "Artificial Intelligence" and "Data Driven Artificial Intelligence" for graduate students and "Thinking in complexity" and "Matlab?" for college students. 2012.7~2017.7 Associate Professor, School of Systems Science, Beijing Normal University. Teaching "Artificial Intelligence" for graduate students and "Thinking in complexity" and "Matlab?" for college students. 2008.6~2012.7 Assistant Professor, Department of Systems Science, School of Management, Beijing Normal University. 2006.4~2008.4 Post doctoral research in complex systems research center, Academy of Mathematics and Systems Science, China Academy of Sciences. Visit Experience 2010.10~present Visited Santa Fe Institute for several times, Santa Fe, New Mexico, U.S.(Record of experience) 2014.12~2015.2 Visited Arizona State University, Tempe, U.S. 2011.9~2011.10 Visited Fribourg University, Fribourg, Switzerland. 2007.7~2007.8 Visited Center for Study Complex Systems, University of Michigan, U.S. Projects 2016.12~2017.6 Project “Elementary School Textbook for UBTech Robots STEM”, supported by UBTech company, 1,000,000 RMB 2017.1~2020.12 Project: “Research on collective attention flows on the WWW”, supported by National Natural Science Foundation of China, the Grant No. is 61673070, 610,000 RMB 2015.9~2017.9 Project "The structure, evolution, and applications of open flow networks", Beijing Normal University Project 2014.1~2016.12 Project “Allometric Growth of Complex Networks” supported by Beijing Higher Education Young Elite Teacher Project (http://www.bjedu.gov.cn) under the Grant No.YETP0291, 150,000 RMB 2011.1~2013.12 Project "Research on Allometric Scaling of Weighted Food Webs" supported by National Natural Science Foundation of China, the Grant No. is 61004107, 210,000 RMB Awards 2008 First-class award in Contest of Basic Skills of Teaching for Young Faculty, Beijing Normal University 2006 C Xu Guo Zhi post-doctoral fellowship in Institute of Systems Science

研究领域

（1）复杂系统自动建模根据复杂系统可观测变量的时间序列自动构建复杂系统模型，通过图网络、因果推理、信息论、深度学习等技术自动地学习动力学、并进行行为预测、推断隐藏的网络结构、节点状态等未知信息，甚至自动发现具有因果特性的宏观变量，并辨识是否存在涌现现象。（2）复杂网络上的机器学习机器学习为我们提供了新工具来处理并解决复杂网络中的推断，例如：复杂网络分类、网络补全、连边预测等。（3）规模标度(Scaling)分析在城市系统、生物系统、企业和网络中，通过在数据中发掘整体层面的标度律，这些规律可以表征复杂系统的宏观普遍模式，也可以为微观层面的机制提供一些洞察。（4）开放流网络通过将复杂开放系统建模为有向加权网络，并在网络中添加两个特殊节点：源和汇，我们可以针对一类具有守恒特性的流结构进行建模，潜在应用包括：在线教育和学习系统中的注意力流分析，在线论坛、网站中的注意力流分析，国际贸易系统中的商品流分析和生态系统食物网中的能量流分析等。

近期论文

查看导师最新文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

Tensor networks for unsupervised machine learning. Phys. Rev. E 107, L012103 – Published 31 January 2023 以复杂思维考察制度涌现。外国经济与管理 2023 年第 45 卷第 01 期, 页码：23 - 37 Neural Information Squeezer for Causal Emergence. Entropy 2023, 25(1), 26 Universal framework for reconstructing complex networks and node dynamics from discrete or continuous dynamics data. Phys. Rev. E 106, 034315 – Published 16 September 2022 Completing Networks by Learning Local Connection Patterns. arXiv:2204.11852v2 [cs.LG] Solving nonequilibrium statistical mechanics by evolving autoregressive neural networks. arXiv:2208.08266 [cond-mat.stat-mech] Scaling laws and a general theory for the growth of public companies. arXiv:2109.10379 [physics.soc-ph] Neural Enhanced Dynamic Message Passing.AISTATS(2022). PMLR 151:10471-10482, 2022 Discovering latent node Information by graph attention network. Scientific Reports 11, 6967 (2021). Ruiqi Li; Lei Dong; Jiang Zhang; Xinran Wang; Wen-xu Wang; Zengru Di; H.Eugene Stanley ; Simple spatial scaling rules behind complex cities, Nature Communications, 2017, 8: 0-1841 （期刊论文） Lifei Wang; Rui Nie; Zeyang Yu; Ruyue Xin; Caihong Zheng; Zhang Zhang; Jiang Zhang; Jun Cai ; An interpretable deep-learning architecture of capsule networks for identifying cell-type gene expression programs from single-cell RNA-sequencing data, Nature Machine Intelligence, 2020, 2 : 0-693 - 703 （期刊论文） Mengyuan Chen; Yan Zhang; Zhang Zhang; Lun Du; Shuo Wang; Jiang Zhang ; Inferring network structure with unobservable nodes from time series data, Chaos, 2022, 32 (013126) （期刊论文） Shuo Wang; Yanran Li; Jiang Zhang; Qingye Meng; Lingwei Meng; Fei Gao ; PM2.5-GNN: A Domain Knowledge Enhanced Graph Neural Network For PM2.5 Forecasting, SIGSPATIAL '20: 28th International Conference on Advances in Geographic Information Systems, Seatle, USA, 2020-11-3至2020-11-6 （会议论文） Zhang Zhang; Yi Zhao; Jing Liu; Shuo Wang; Ruyi Tao; Ruyue Xin; Jiang Zhang ; A general deep learning framework for network reconstruction and dynamics learning, Applied Network Science, 2019, 4(110): 0-110 （期刊论文）

学术兼职

集智俱乐部创始人，集智学园（北京）科技有限公司创始人，集智科学研究中心理事长