Rohit Ganguly

• Complex problem-solver with analytical and driven mindset.
• Pursuing the passion for coding for more than 3 years of all together experience
• Dedicated to achieving demanding development objectives according to tight schedules while producing impeccable code.

• CS50 by Harvard(EdX)
• Full Stack Development Bootcamp(Coursera)
• Advanced Python Programming(Coursera)
• Javascript and React Integration(Coursera)
• Cybersecurity (Coursera)

Projects:

Full Functional Ecommerce Application:

Summary of Project Experience:

- Developed e-commerce projects using Next.js as the frontend framework.
- Implemented Stripe API Routes for handling webhooks and processing events during and after checkout.
- Utilized CMS platforms like Contentful or Sanity to efficiently manage and store product inventory.
- Demonstrated proficiency in integrating backend functionality, including authentication, database interactions, and more, using Next.js API Routes.
- Utilized Stripe checkout or payment links for seamless customer payment experiences.
- Explored serverless solutions like Firebase to eliminate the need for a custom backend when applicable.

News/Community App (Reddit Clone)

Summary of Project Experience:

- Developed a content-driven web application using React as the frontend framework, bootstrapped with Vite for faster development.
- Utilized React Router for dynamic routing, enabling users to access individual posts based on their unique IDs.
- Integrated Firestore database from Firebase to store and manage user-generated content, such as videos, links, and short posts.
- Implemented user authentication using Firebase Auth for a secure and personalized user experience.
- Expanded the app's functionality by enabling users to interact with posts through likes and comments, fostering community engagement and interaction.
- Leveraged the flexibility of the chosen stack to create a scalable and interactive platform for content creation and user participation.

Realtime Mood Based Music Player

Summary of Project Experience:

- Contributed to the development of an innovative automation system for generating personalized playlists using AER (Audio Emotion Recognition) and MIR (Music Information Retrieval) technologies.
- Implemented emotion modules such as sadness, joy-anger, joy-surprise, joy-excitement, joy, sad-anger, and anger to accurately detect user emotions from audio input.
- Achieved high accuracy levels ranging from 80% to 90% for real-time emotion detection from audio waves.
- Collaborated on the design and implementation of three core modules: Audio Feature Extraction, Emotion-Audio Recognition, and Emotion Extraction, ensuring seamless integration and functionality.
- Leveraged machine learning algorithms to analyze audio data and fetch desired outputs, tailoring playlists to users' moods and emotions.
- Worked on the software engineering aspects of the project, contributing to the development and optimization of the automation system.