Lizhi Wang

Title(s):

Professor
Industrial & Manufacturing Systems Engineering
Plant Sciences Institute Faculty Scholar

Office

3016 Black Engr
2529 Union Dr
Ames, IA 50011-2030

Information

Education

PhD, Industrial Engineering, University of Pittsburgh (2007)

BE, Automation, University of Science and Technology of China (2003)

BS, Management Science, University of Science and Technology of China (2003)

Interest Areas

Core Research Area: Electric power and energy systems

Strategic Research Area: Energy infrastructure

Publications

  • Javad Ansarifar, Faezeh Akhavizadegan, and Lizhi Wang, “Performance prediction of crosses in plant breeding through genotype by environment interactions,” to appear in Scientific Reports, 2020.
  • Saba Moeinizade, Aaron Kusmec, Guiping Hu, Lizhi Wang, and Patrick S. Schnable, “Multi-trait genomic selection methods for crop improvement,” to appear in Genetics, 2020.
  • Saeed Khaki, Hieu Pham, Ye Han, Andy Kuhl, Wade Kent, and Lizhi Wang, “Convolutional neural networks for image-based corn kernel detection and counting,” to appear in Sensors, 2020.
  • Saeed Khaki, Zahra Khalilzadeh, and Lizhi Wang, “Predicting yield performance of parents in plant breeding: A neural collaborative filtering approach,” to appear in PLOS ONE, 2020.
  • Faezeh Akhavizadegan, Lizhi Wang, and James McCalley, “Scenario selection for iterative stochastic transmission expansion planning,” vol. 13(5), p. 1203, Energies, 2020.
  • Saeed Khaki, Lizhi Wang, and Sotirios Archontoulis, “A CNN-RNN framework for crop yield prediction,” vol. 10, p. 1750, Frontiers in Plant Science, 2019.
  • Saeed Khaki, Zahra Khalilzadeh, and Lizhi Wang, “Classification of crop tolerance to heat and drought: A deep convolutional neural networks approach,” vol. 9(12), p. 833, Agronomy, 2019.
  • Saba Moeinizade, Megan Wellner, Guiping Hu, and Lizhi Wang, “Complementarity-based selection strategy for genomic selection,” vol. 60(1), p. 149-156, Crop Science, 2019.
  • Javad Ansarifar and Lizhi Wang, “New algorithms for detecting multi-effect and multi-way epistatic interactions,” vol. 35(24), p. 5078-5085, Bioinformatics, 2019.
  • Saeed Khaki and Lizhi Wang, “Crop yield prediction using deep neural networks,” vol. 10, p. 621, Frontiers in Plant Science, 2019.
  • Saba Moeinizade, Guiping Hu, Lizhi Wang, and Patrick Schnable, “Optimizing selection and mating in genomic selection with a look-ahead approach: an operations research framework,” Genes Genomes Genetics, vol. 9(7), p. 2123-2133, 2019.
  • Lizhi Wang and Maryam Nikouei Mehr, “An optimization approach to epistasis detection,” European Journal of Operational Research, vol. 274(3), p. 1069-1076, 2019.
  • more

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