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Ph.D.

University of California, Merced, USA

• Electrical Engineering and Computer Science.
  • Developed UAV imagery processing models by using Machine Learning, and Computer Vision algorithms, such as Convolutional Neural Networks (CNN), Scikit-learn, and OpenCV.
  • Conducted data collection and processing using the Unmanned Aircraft System (UAS).

M.S.

California State University, Chico, USA

• Electrical and Computer Engineering.

Research Engineer

Texas A&M University, College Station, Texas, US

• Integrate vertically across machine learning and AI, high performance computing, and data management, to design and produce prototype expert systems which also incorporate interfaces to support user queries and visualization.
• Develop efficient schedules for crop irrigation, specifically to develop an Unmanned Aerial System (UAS)-based crop monitoring system that models crop water use for irrigation scheduling and increased water use efficiency, based on UAS-derived phenotype data and infield weather data.

Summer Intern

Lawrence Livermore National Laboratory (LLNL), Livermore, California, US

• Supporting the optimization techniques for risk-seeking policy gradients project.
• Explore and implement novel and/or existing optimization techniques for use in symbolic optimization software library (Rllib), conduct experiments for discrete optimization tasks, and analyze experimental results and write up findings.

Github link

• A simple, clean github for academics.

• Bayer Crop Science, Grants4Ag Award Recipient.

• First place award in the Food Systems category of Big Ideas Contest at UC, Berkeley.