I am a Master's in Computer Science student at NJIT university
-
Experience
Internship, Bharat Petroleum Corporation Limited Jun 2017 - Jul 2017
1. Chosen as top 15 interns in a 1 month-summer internship program, held in Mumbai, assigned to a research and developer intern role under computer science department in Bharat Petroleum Corporation Limited.
2. Successfully designed technical research analysis in Java and TCP/IP with technicalities and laws on Voice Over Internet integration with existing telecommunication setup, and created full implementation detailed proposal to increase efficiency for communicating with remote refineries of organization by more than 50% and project was executed in Jan- Dec 2018.
-
Projects
1. Wallet Payment Application (Spring Boot, Angular.JS JavaScript, Oracle DB) May 2020 – Aug 2020
a. Lead a team of 6 to develop, evaluate and deploy a web application for sending, receiving and splitting the amount between the users by communicating, obtaining requirements, finding solutions and implementing them in a clean and concise way
b. As a Back-End developer, designed, build and maintained the main controller and associated APIs to manage the web requests, retrieve the data from database to show on UI and perform application specific operations.
c. As a Front-end developer, developed high performance, multi-threaded user-interface for the application
d. As an UI/UX designer developed mid-fidelity and high-fidelity wireframes for the application
2. Smart Recognition application(AWS, S3, SQS, Java, Linux) Feb 2020 – March 2020
Developed and deployed Java based image rekognition pipeline in AWS using two EC2 instances working in parallel, S3, SQS, and amazon recognition service with IaaS platform of Linux based EC2 instances.
3. Inventory Management System (Spring Boot, HTML, CSS, MySQL) Oct 2019 – Nov 2019
a. Lead a team of 3 to design, build and deploy an inventory system for tracking sales, availability of items in store, no of hours worked by workmen and generating monthly statements thereby improving the productivity and profit by 75%.
b. Created an easily understood and testable codebase that can change as quickly as market conditions require
4. Wine quality prediction (AWS EMR, Apache Spark MLlib, Docker, Python, Linux) Mar 2020 – April 2020
a. Developed Machine Learning model using Apache Sparks MLlib libraries and trained it over AWS EMR cluster in parallel consisting of 1 master and 3 worker nodes for predicting the wine quality of dataset.
b. Defined schemata for critical datasets, collected internal data, performed transformations in AWS cluster, and efficiently store the data for accessibly.
c. Created a docker container for the ML model to simplify deployment and pushed the container to docker hub.
5. Intelligent data storing data structure (Java, Data structures and Algorithms, Linux) Jan 2020 – Feb 2020
Build a Hash Table with array for storing English letter words using collusion resolution by open addressing method with quadratic probing there by improving the expected running time. Overcame the possibility of hash table getting full by implementing functionality to increase size without any loss of data and expected running time.