A published study in the October 2016 edition of the International Journal of Computer Applications about classifying species of bacteria from their images. The work explored the use of image key point vectors as feature inputs for a neural network classifier. The work also utilized an early iteration of patch processing for data augmentation. 

A game environment for image segmentation inspired by MineSweeper published in the International Journal of Advance and Innovative Research. The work proposes a novel environment for training image segmentation models via gamification. The image itself becomes the environment, and the task would be to tag pixels of interest, much like the original MineSweeper game.

A peer reviewed poster in the Fall 2019 class of CSE-6242 Data and Visual Analytics at Georgia Tech that attempts to interpret factors contributing to virality of a video on the YouTube platform. The various factors analysed were the length of the title and description, the number of likes, dislikes, and comments. We created cluster matrices, word clouds and other visualization dashboards for representing the data. We used a neural network regressor in order to predict the possible number of views based on these aforementioned parameters.