►Graded HomeWorks, tutored students and helped professor to make quizzes and HomeWorks for two courses: Automata, Computation & Formal Language and Computer Vision

►Developed a web-application using Django and JavaScript in order to allow soil scientists to research and analyze soil samples ►Created a database using MongoDB in order to catalog over 100k soil samples from USDA►Trained and compared several machine learning models using Scikit-learn and Keras for predicting soil properties►Processed the point clouds by Implementing a data analysis pipeline in MATLAB for generating 3-dimensional structure of the maize and sorghum plants

►Assembled a system using LIDAR and turntable and wrote an application in Python/LABVIEW to get the 3-dimensional point cloud of the maize and sorghum plants► Processed the images of plants using deep learning to obtain several meaningful information required by plant scientists. Example of some analysis performed are: count number of leaves from corn images, classify nutrient deficiency of soybean images and count number of wheat spikes in an image►Analyzed hyperspectral images and developed statistical models to predict chemical properties of plant leaf – Nitrogen, Phosphorous, Sodium and Water content