Daksh Prajapati

Created Linux GUIs using Tkinter for confidential data analysis, incorporating secure multiparty computation and differential privacy. Applied secure multiparty computation protocols for confidential data exchange, integrated differential privacy techniques for individual privacy preservation. Collaborated with backend team to modularize backend through a flexible coded architecture transition. Implemented interactive user-centric features, facilitating dynamic adjustment of fundamental parameters for heightened user customization.

Implemented a live content moderation extension allowing users to instantly blur explicit elements like nudity, violence, and gore in images. Built a CNN model using VGG-16 transfer learning for precise classification of explicit content, effectively addressing limited data availability. Implemented FastAPI for API management, and employed JavaScript to govern extension functionality and real-time blurring capabilities.

Building a Data Analysis Model to predict manufacturing time using MS Azure. Using a pre-existing database with manufacturing time that the company has gathered. This model determines how long it will take a company to produce a certain product of a certain size and quality in a different workshop.