Software Engineer
Summary
Cut template download latency from 2s to 500ms using Redis caching and parallel Java service calls Written modular microservices services improving code scalability and maintainability Used: Java, Graphql, Python, Nextjs, Typescript
Software Engineer Intern
Summary
Developed Frontend on Supplier Product Addition tool Written Test Cases for Frontend and also developed api using Java Used: TypeScript, NextJs, Java, GraphQl, Docker
Incubation Centre NIT Patna
-Spearheaded the successful activities at Incubation Centre NIT Patna, -Showcasing dedication and commitment
HackSlash
-Demonstrated exceptional leadership skills as the Discipline Lead for Hackslash -Driving innovation and fostering a collaborative environment
Maximum 1407 rating
Got under top 3.1% of global top Leetcoder with rating 1960+
Achieved a competitive ranking of under 8500 on leetcode
Achieved rating of 1808, showcasing exceptional skill and dedication
C, C++, Python, JavaScript, Java, MySql, HTML, CSS, PI/Sql.
Djnago, ReactJS, NodeJS, ExpressJS, Jquery, Mongodb, TailWind CSS, NoSql databases.
Git, Github, Linux, Windows, Amazon Web Services (AWS).
Team management, Leadership, Event Management, Public Speaking.
Web Development, Blockchain, Competitive Programming, Data Structures and Algorithms.
Object-Oriented Programming(OOPs), Operating Systems, Computer Networks, RDBMS, Networks, Network Programming, Database Management Systems(DBMS).
Summary
Made a platform that allows users to post, delete, and comment on ideas Tools & technologies used: JavaScript, HTML, CSS, MongoDB, Redis, Node.js, Express.js, React.js, Socket.js, Google auth, Amazon AWS Platform where users can post, comment and like each other Post, comments Implemented features for users to like posts and comments Integrated real-time chat functionality for seamless communication and collaboration among users
Summary
Developed a cutting-edge LSTM model to classify text as Hate speech or not, achieving an accuracy of 92% Tools & technologies used: Machine Learning, Deep Learning, Google Colab, Python Utilized GloVe and BERT for vectorization and achieved state-of-the-art performance