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Dr. Sushil Kumar Himanshu

Assisstant Professor
Agricultural Systems and Engineering, Department of Food, Agriculture, and Bioresources

Doctor of Philosophy in Water Resources Development & Management, Indian Institute of technology Roorkee, India (July 2013 – Dec 2017)

Master of Technology in Hydrology, Indian Institute of Technology Roorkee, India (2010 – June 2012)

Bachelor of Technology in Agricultural Engineering, Sam Higginbottom University of Agriculture, Technology and Sciences, Prayagraj, India (July 2006 – June 2010)

  • Precision Farming
  • Climate Resilient Agriculture Systems
  • Regenerative Agricultural Practices
  • On-farm Irrigation Water Management
  • Remote Sensing and GIS Applications in Agriculture
  • Applications of Unmanned Aerial Systems (UAS) and Wireless Sensors in Agriculture
  • Big Data Analysis and Applications
  • Machine Learning Applications in Agriculture
  • Hydrologic/Cropping System Modelling
  1. Himanshu SK, Ale S, Bell J, Fan Y, Samanta S, Bordovsky J, Gitz D, Brauer D. (2023). Evaluation of growth-stage-based variable deficit irrigation strategies for cotton production in the Texas High Plains. Agricultural Water Management, 280, 108222. Publisher: Elsevier  
  2. Dayal D, Pandey A, Gupta PK, Himanshu SK. (2023). Multi-criteria evaluation of satellite-based precipitation estimates over agro-climatic zones of India. Atmospheric Research, 292, 106879. Publisher: Elsevier
  3. Bawa A, Samanta S, Himanshu SK, Kim J, Singh J, Ale S, Chang A, Jung J, DeLaune P, Bordovsky J, Barnes E. (2023). A support vector machine and image processing-based approach for counting cotton bolls and estimating lint yield from UAV imagery. Smart Agricultural Technology, 3, 100140. Publisher: Elsevier.
  4. Ale S, Su Q, Singh J, Himanshu SK, Fan Y, Stoker B, Gonzalez E, Sapkota B, Adams C, Biggers K, Kimura E, Wall J. (2023). Development and Evaluation of a Decision Support Mobile Application for Cotton Irrigation Management. Smart Agricultural Technology, 5, 100270. Publisher: Elsevier
  5. Praseartkul P, Taota K, Pipatsitee P, Tisarum R, Sakulleerungroj K, Sotesaritkul T, Himanshu SK, Datta A, Cha-um S. (2023). Unmanned aerial vehicle-based vegetation monitoring of aboveground and belowground traits of the turmeric plant (Curcuma longa L.). International Journal of Environmental Science and Technology, 20, 8673–8686, https://doi.org/10.1007/s13762-022-04545-6. Publisher: Springer
  6. Himanshu SK, Fan Y, Ale S, Bordovsky J. (2021). Simulated efficient growth-stage-based deficit irrigation strategies for maximizing cotton yield, crop water productivity and net returns. Agricultural Water Management, 250, 106840. Publisher: Elsevier . 
  7. Himanshu SK, Ale S, Bordovsky J, Kim J, Samanta S, Omani N, Barnes E. (2021). Assessing the impacts of irrigation termination periods on cotton productivity under strategic deficit irrigation regimes. Scientific Reports, 11, 20102. Publisher: Nature . 
  8. Himanshu SK*, Pandey A, Yadav B, Gupta A. (2019). Evaluation of best management practices for sediment and nutrient loss control using SWAT Model. Soil and Tillage Research, 192, 42-58. Publisher: Elsevier . 
  9. Himanshu SK, Ale S, Bordovsky JP, Darapuneni M. (2019). Evaluation of crop-growth-stage-based deficit irrigation strategies for cotton production in the Southern High Plains. Agricultural Water Management, 225, 105782. Publisher: Elsevier . 
  10. Himanshu SK*, Pandey A, Yadav B. (2017). Assessing the applicability of TMPA-3B42V7 precipitation dataset in wavelet-support vector machine approach for suspended sediment load prediction. Journal of Hydrology, 550, 103–117. Publisher: Elsevier . 
  1. Regenerative Agriculture in ASEAN: Promoting Nature-positive Solutions for Rice Production (REGA-ASEAN).
    Donor: The Rockefeller Foundation, USA
    Budget: USD 300,000 (THB 10,500,00)
  2. Precision Agriculture with Smart Farming Technologies
    Donor: The World Bank through the Indian Council of Agricultural Research (ICAR), India
    Budget: USD 750,000 (THB 35,000,00)
  3. Evaluation of efficient crop-growth-stage-based deficit irrigation strategies for cotton and grain sorghum production in the Texas High Plains
    Donor: United States Department of Agriculture (USDA), USA
    Budget: USD 38,000 (~THB 1,375,000)
  4. Development of Machine Learning Algorithms for Spatial Downscaling of Satellite Precipitation Data Over Thailand to help Farmers Achieve Agricultural Sustainability
    Donor: Asian Institute of Technology, Thailand
    Budget: THB 150,000
  5. Evaluation of Soil Health Benefits of Cover Crops in Cotton Production Systems of the Texas Rolling Plains
    Donor: Cotton Incorporated, USA
    Budget: USD 40,000 (~THB 1,448,000)