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.
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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.
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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