I like to learn new things and work on innovative ideas. I graduated in May from NC State University with my Master's in Computer Science. Currently I am looking for a full-time job as a Software Engineer.
Experience
1. Talking Pictures LLC Buffalo, NY Software Engineering Intern : July 2020 - Current - Improved the existing search on the website by fine tuning database text indexes in MongoDB. - Implemented a Voice Unit Meter which responds to the intensity of audio from user using p5 JavaScript library. 2. Karma Industries Mumbai, India Software Development Intern : June 2019 - August 2019 - Initiated development for the organization’s tool in Python. - Formulated new data flow and feature selection for existing functionalities to improve existing memory usage 3. Larsen & Toubro Mumbai, India Software Development Intern : June 2017 - August 2017 - Actively participated in design of an innovation platform IdeaScale for the organization. - Engineered functionalities in Java and JDBC for backend - Responsible for designing proxies to ensure network management for incoming traffic.
Projects
1. Project LibX: - Actualized an interactive front-end to fetch user entries in Angular JS paired with PHP, to provide different login and user page prompts for admins, instructors and students. - Designed a SQL schema for storage of data such as images for books, video lecture or notes that instructor can upload, login and maintenance of records. - Formulated a Rapid Automatic Keyword Extraction (RAKE) algorithm in Python to extract keywords from user queries to store into the Database. 2. Software Security - Performed technical security review of OpenMRS. This open-source system provides electronic health care functionality. (http://openmrs.org) - The security review consisted of multiple techniques like static analysis using tools like Fortify and Coverity. - Performed various attacks using tools like ZAP and Defensics to check client side by-passing and fuzzing. Secure coding techniques to avoid Injections, XSS and CSRF. 3. Netflix Prize Challenge: - Enhanced data by adding more features for the movies by scraping info from IMDB. - Designed a KNN based Collaborative Filtering algorithm in Python, to generate a similarity matrix for a dataset of 480,189 users and 17,770 movies. - Obtained an ideal RMSE of 0.84 with the above algorithm. - Performed K-Means Clustering on the predictions to group users who liked a particular genre, was displayed on a plot using matplotlib