I am a recent graduate from New York University with Master's degree in Computer Science. I am passionate about Software Engineering and Web Development. During my Master's, I took several courses out of interest where I worked from scratch on large scale projects which included programming in Java, Python and JavaScript. I have experience working on AWS cloud platform and have worked on various AWS services such as DynamoDB, Lambda, ElasticSearch, S3, CloudWatch, API Gateway, Athena, Kinesis, Rekognition etc.
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Experience
Statistical and Data Mining Intern, T.C.R., Inc., Weston, USA
June-August 2019
• Automated the data pipeline process to mine, cleanse, manipulate (using Python and R) and visualize data about clinical trials on diseases such as Breast Cancer, Prostate Cancer, Solid Tumors etc. across the US.
• Developed interactive dashboards using Tableau for information such as disease conditions and location centers.
• Allowed users to filter details of clinical trials based on cities and states.
• Communicated results and recommendations to senior leadership through weekly presentations.
Software Development Intern, Infocouture Solutions Pvt. Ltd., Noida, India
January-May 2017
• Developed a mobile application on ’Lead Management System (LMS)’ to be used as a tool that allows sales people associated to create, submit, share and manage their contents online without requiring technical knowledge.
• Technologies: React Native, Android Studio, Visual Studio, JavaScript.
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Projects
YelpCamp: A social media web application for campgrounds
April-May 2020
•Developed and deployed a web application on Heroku where users can sign up to view and create posts forcampgrounds which include features like image upload, price and geo-location using the google maps API.
•Other users can like, comment on posts and receive notifications when a user they follow posted something new.
•Technology stack: Node.js, Express, MongoDB, HTML, CSS, Bootstrap, JavaScript
Smart Door Authentication System
October-November 2019
• Built a distributed system that authenticates people and provides them with access to a virtual door.
• Performed AWS Kinesis Video stream analysis using AWS Rekognition to identify faces and provide an automatic access code for authentication with AWS SNS.
• Used Lambda functions that allow or deny access to visitors and adds them to the database for future training.
• Other services used were AWS S3 bucket, DynamoDB, API Gateway, CloudWatch.
Dining Concierge Chatbot
September-October 2019
• Implemented a serverless, microservice-driven chatbot that sends restaurant suggestions based on preferences provided by the user through conversation.
• Scraped Data from Yelp API for 5,000 restaurants in Manhattan for recommendations of restaurants.
• Deployed webpages on AWS S3 bucket and leveraged REST service Interface, API Gateway with Swagger, DynamoDB, Lambda, ElasticSearch to develop all endpoints for high scalability and reliability.
Twitter data Sentiment Analysis and Visualization using AWS February-March 2019
• Extracted tweets in different languages from Twitter API and translated them to English using AWS Translate API service, then performed sentiment analysis and entity extraction on the tweets using AWS Comprehend service.
• Used AWS S3, AWS Athena and AWS Kinesis Firehose to store, query and stream the data collected.
• Used AWS QuickSight to visualize results and build a natural-language-processing (NLP) powered social media dashboard for tweets.
Oingo: Geo-location based social media application
November-December 2018
• An application to share useful notes of geographical locations with keyword filtering and scheduling capabilities.
• Designed the relational database that stores all the information about users, friendships between users, notes published by users, and filters that users have for what kind of notes they want to receive at different times.
• Created a web-based user interface in which users can register, create a profile, log in, post notes, send and answer friend requests and comment on notes they have received.