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Gang Shao

University Title:
Assistant Professor
Division/Unit(s):
Research Data
Location(s):
Stewart Center
174C

Professional Information

Faculty Rank:
Assistant Professor
Liaison Areas:
Computer Science
Statistics
Courses Taught:
ILS595 Geospatial Programming and Data Science (Spring 2021)
ILS295 Intro to Data Lifecycle Management (Fall 2020)
Research Areas:
Data Science; Data Science Education; Machine Learning; Artificial Intelligent; Image/video processing; Text analysis; Digital environmental analysis (Precision Ag and Digital Forest)
Education:
Ph.D., Forestry and Natural Resources, Purdue University, 2016
M.S., Forestry and Natural Resources, Purdue University, 2012
B.S., Biomedical Engineering, Northeastern University (CN), 2009
Professional Experience:
Assistant Professor, PULSIS, Purdue University, 2019 - present
Honors and Awards:
Joanne J. Troutner Innovative Educators Award, 2021
IDEA institute on AI, IMLS-funded Fellow 2021

Publications

Selected publications, more on Google Scholar (Journal Impact Factors updated in 2021)

Shao, G., Quintana, J. P., Zakharov, W., Purzer, S., & Kim, E. (2021). Exploring potential roles of academic libraries in undergraduate data science education curriculum development. The Journal of Academic Librarianship, 47(2), 102320. https://doi.org/10.1016/j.acalib.2021.102320 (Journal Impact Factor: 1.533)

Li, S., Liu, Y., Her, Y., Chen, J., Guo, T., & Shao, G. (2021). Improvement of simulating sub-daily hydrological impacts of rainwater harvesting for landscape irrigation with rain barrels/cisterns in the SWAT model. Science of The Total Environment, 149336. https://doi.org/10.1016/j.scitotenv.2021.149336 (Journal Impact Factor: 7.963)

Hu, T., Toman, E. M., Chen, G., Shao, G., Zhou, Y., Li, Y., ... & Feng, Y. (2021). Mapping fine-scale human disturbances in a working landscape with Landsat time series on Google Earth Engine. ISPRS Journal of Photogrammetry and Remote Sensing, 176, 250-261. https://doi.org/10.1016/j.isprsjprs.2021.04.008 (Journal Impact Factor: 8.979)

Guo, T., Johnson, L. T., LaBarge, G. A., Penn, C. J., Stumpf, R. P., Baker, D. B., & Shao, G. (2020). Less agricultural phosphorus applied in 2019 led to less dissolved phosphorus transported to Lake Erie. Environmental Science & Technology, 55(1), 283-291. https://doi.org/10.1021/acs.est.0c03495 (Journal Impact Factor: 9.028)

Shao, G., Stark, S. C., de Almeida, D. R., & Smith, M. N. (2019). Towards high throughput assessment of canopy dynamics: The estimation of leaf area structure in Amazonian forests with multitemporal multi-sensor airborne lidar. Remote Sensing of Environment, 221, 1-13. https://doi.org/10.1016/j.rse.2018.10.035 (Journal Impact Factor: 10.164)

Almeida, D. R. A. D., Stark, S. C., Shao, G., Schietti, J., Nelson, B. W., Silva, C. A., ... & Brancalion, P. H. S. (2019). Optimizing the remote detection of tropical rainforest structure with airborne lidar: Leaf area profile sensitivity to pulse density and spatial sampling. Remote Sensing, 11(1), 92. https://doi.org/10.3390/rs11010092 (Journal Impact Factor: 4.848)

Shao, G., Shao, G., Gallion, J., Saunders, M. R., Frankenberger, J. R., & Fei, S. (2018). Improving Lidar-based aboveground biomass estimation of temperate hardwood forests with varying site productivity. Remote Sensing of Environment, 204, 872-882. https://doi.org/10.1016/j.rse.2017.09.011 (Journal Impact Factor: 10.164)

Other Information

D-VELoP lab workshops on Machine Learning and Data Visualization: https://guides.lib.purdue.edu/d-velop Data Science Libguide: https://guides.lib.purdue.edu/c.php?g=1019894