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Qinli Yang

University of Electronic Science and Technology of China (China) , associated professor

Education Background
2008/10 – 2011/09, University of Edinburgh (UK), PhD
2011/10 – 2013/09, University of Munich (Germany), PostDoc.
2013/09 – 2015/07, University of Electronic Science and Technology of China (China), Lecture.
Since 2015 /08, University of Electronic Science and Technology of China (China) , associated professor.
Brief Research Statement
Dr. Yang is interested in models of complex dynamic systems at an appropriate level of detail for decision support. Her research focuses on hydrology, water resources, flood analysis, environmental remote sensing and data mining. She published more than 20 papers on peer-reviewed international journals and conferences in the fields of water resources and data mining, such as Water Research, Environmental Modelling and software, KDD, ICDM. The findings provide various rapid scientific tools for water resources analysis and assessment, helping water resources managers and planners better understand water bodies and make wiser use of them.

Selected Awards
Ÿ   Best Paper Award in ICDM 2010, Workshop on Biological Data Mining and its Applications in Healthcare.
Ÿ   Best Article for IGI Global’s “Fourth Annual Excellence in Research Journal Awards” 2010

Selected Publications
Ÿ[1]Yang, Q., Shao, J., Scholz, M. and Plant, C.: Feature selection methods for characterizing and classifying adaptive Sustainable Flood Retention Basins, Water Research, 45 (3), 993-1004, 2011.www.sciencedirect.com/science/article/pii/S0043135410007013
[2]Yang, Q., Scholz, M. and Shao, J.: Application of Spatial Statistics as a Screening Tool for Sustainable Flood Retention Basin Management, Water and Environment Journal. 26 (2), 155-164, 2012. http://onlinelibrary.wiley.com/doi/10.1111/j.1747-6593.2011.00272.x/abstract
[3]Yang, Q., Shao, J., Scholz, M., Boehm, C. and Plant, C.: Multi-label Classification Models for Sustainable Flood Retention Basins, Environmental Modelling and Software. 32, 27-36, 2012. http://www.sciencedirect.com/science/article/pii/S1364815212000023
[4]Yang, Q., Shao, J. and Scholz, M.: Self-organizing Map to Estimate Sustainable Flood Retention Basin Types and Variables, Environmental Engineering and Management Journal. 13 (1), 129-134, 2014. http://omicron.ch.tuiasi.ro/EEMJ/issues/vol13/vol13no1.htm
Ÿ[5]Yang, Q., Boehm, C., Scholz, M., Plant, C. and Shao, J.: Predicting Multiple Functions of Sustainable Flood Retention Basins under Uncertainty via Multi-instance Multi-label Learning, Water, 7 (4), 1359-1377, 2015. http://www.mdpi.com/2073-4441/7/4/1359
[6]Scholz, M. and Yang, Q.: Guidance on Variables Characterising Water Bodies including Sustainable Flood Retention Basins, Landscape and Urban Planning, 98 (3-4), 190-199, 2010.
[7]Scholz, M. and Yang, Q.: Novel Method to Assess the Risk of Dam Failure, Sustainability, 3 (11), 2200-2216, 2012. http://www.sciencedirect.com/science/article/pii/S0169204610001891
Ÿ[8]McMinn, W. R., Yang, Q. and Scholz, M.: Classification and Assessment of Water Bodies as Adaptive Structural Measures for Flood Risk Management Planning, Journal of Environmental Management, 91 (9), 1855-1863, 2010. http://www.sciencedirect.com/science/article/pii/S0301479710001106