2005年获中国农业大学信息与电气工程学院计算机科学与技术学士学位,同年考入资源与环境学院硕博连读。2007.11-2009.11获国家留学基金委公派留学资助,作为联合培养博士生赴法国巴黎中央理工大学应用数学实验室学习两年,并于2010年获法国奖学金继续在法学习近一年。2011年到中科院自动化研究所从事博士后工作,2014年留所工作至今。主要研究方向为智慧农业和植物生长建模相关研究。主持国家自然科学基金委青年项目1项,新一代人工智能重大项目子课题1项,国重复杂实验室青年基金项目1项,参与国家自然科学基金、科技部、中科院以及横向课题等项目10余项。发表论文40余篇,其中SCI/EI论文15篇,包括 Plant Phenomics, IEEE/CAA Journal of Automatica Sinica, IEEE Transactions on Cybernetics, Frontiers in Plant Science, Annals of Applied Biology, Field Crops Research等,授权发明专利7项。
计算植物,智慧农业
1. 2021.12-2024.12,科技创新“2030”新一代人工智能重大项目子课题,2021ZD0113701, 农作物水稻和大豆环境及生命状态识别,在研,主持
2. 2022.01-2024.12,中科院-荷兰“垂直农场”领域合作项目,, 159231KYSB20200010, TWINERGY:以数字孪生提升垂直农场能源利用效率,在研, 参与
3. 2020/01-2022/12,中国科学院与泰国科技发展署合作研究资助项目,GJHZ20176,基于作物生长的温室环境控制系统研究,结题,参与
4. 2019/01-2022/05,中国科学院A类先导项目子课题,基于复杂系统平行理论的防风固沙效应可视化模拟与智能决策, XDA20030000,结题,参与
5. 2018/01-2020/12,国家自然科学基金青年项目,31700315,油菜产量构成因素形成的时间动态和空间特征模型研究,结题,主持
6. 2015/01-2017/12,国家自然科学基金青年项目,31400623,基于三维空间结构和光线追踪算法的树木冠层光分布研究,结题,参与
7. 2015/01-2015/12,复杂系统管理与控制国家重点实验室青年研究基金,99S9021F4N,结题,主持
1. Wang, X. J., Hua, J., Kang, M. Z. Functional-Structural Plant Model 'GreenLab': A State-of-the-Art Review, Plant Phenomics, 2023, 5
2. Wang, X. J.; Kang, M. Z., Sun H. Q., Wang F.-Y. DeCASA in AgriVerse: Parallel Agriculture for Smart Villages in Metaverses, IEEE/CAA Journal of Automatica Sinica, 2022, 9(12): 2055-2062.
3. Kang M. Z., Wang, X. J., Wang H. Y., et al. The Development of AgriVerse: Past, Present, and Future. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023, 53(6): 3718-3727.
4. Kang M. Z., Wang X. J.*, Qi R., et al. 2021. Analyzing and optimizing yield formation of tomato introgression lines using plant model. Euphytica, 217, 100.
5. Fan M. H., Kang M. Z*., Wang X. J*., et al. 2021. Parallel crop planning based on price forecast. International Journal of Intelligent System, 1-22. doi:10.1002/int.22739.
6. Wang X. J., Kang M. Z.*, Yang L. L., Zhang B. G., Huang S. -W., de Reffye P. 2019. Simulation of fruit-set and trophic competition in three cucumber cultivars and optimization of source-sink dynamics using functional–structural plant modelling. Journal of Integrative Agriculture, 19(7): 1789-1801.
7. Weng Y. C., Wang X. J., Hua J., Wang H. Y., Kang M. Z., Wang F.-Y. 2019. Forecasting Horticultural Products Price Using ARIMA Model and Neural Network Based on a Large-Scale Data Set Collected by Web Crawler. IEEE Transactions on Computational Social Systems, 6(3): 547-553. doi: 10.1109/TCSS.2019.2914499
8. Kang M. Z., Fan X.-R. , Hua J., Wang H. Y., Wang X. J.*, Wang F.-Y. 2018. Managing Traditional Solar Greenhouse With CPSS: A Just-for-Fit Philosophy. IEEE Transactions on Cybernetics, 48 (12): 3371 – 3380.
9. Kang M. Z., Hua J., Wang X. J.*, de Reffye P., Jageger M., Akaffou S. 2018. Estimating Sink Parameters of Stochastic Functional-Structural Plant Models Using Organic Series-Continuous and Rhythmic Development. Frontiers in Plant Science, 9: 01688. doi: 10.3389/fpls.2018.01688.
10. Fan X.-R, Wang X. J., Kang M. Z.*, Hua J., Guo. S. S.*, de Reffye P. and Hu B. -G. 2018. A knowledge-and-data-driven modeling approach for simulating plant growth and the dynamics of CO2/O2 concentrations in a closed system of plants and humans by integrating mechanistic and empirical models. Computers and Electronics in Agriculture, 148: 280-290.
11. Wang, X.J., Mathieu, A., Cournède, P.H., de Reffye, P., Zhang, B.G. 2014. Application of a probabilistic model for simulating the number of seeds and pod abortion in winter oilseed rape (Brassica napus L.). Annals of Applied Biology, 165: 414-428. doi: 10.1111/aab.12152
12. Wang, X.J., Mathieu, A., Cournède, P.H., Allirand, J.M., Jullien, A., de Reffye, P., Zhang, B.G. 2011. Variability and regulation of the number of ovules, seeds and pods according to assimilate availability in winter oilseed rape (Brassica napus L.). Field Crops Research, 122(1), 60-69.
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