Zubi is a young Ed-Tech startup with the mission to enable young minds to utilise the potentials of emerging technologies. As a curator I developed learning computer fundamentals and artificial intelligence learning modules, assessments and projects for the youth division. I have successfully taught and interacted with 500+ students during my tenure in courses, webinars and interaction sessions. I also founded the "Early Hack" vertical of Zubi with my co-educators and partnered up with schools in tier two cities and taught modules of computer fundamentals.

I worked as a Software Development Intern for AT&T. I worked on a Natural Language Processing project for internal teams of the company where my team and I developed a sentiment analysis based approach to customer segmentation. During the 8 weeks internship, I developed different modules of sentiment analysis to compare and contrast results for telecom industry specific datasets. Following the development of sentiment analysis modules, I worked on developing the customer segmentation modules with my team achieving an overall accuracy of 0.996. The modules were combined and heanded over to testing and automation team for further implementation.

Conducting an AI-focused case study for language-driven engineering (LDE). In particular, I am exploring it's potential in tandem with machine learning.