Computer Science Node Js

Shravani Kammari

Hyderabad, Telangana 863-***-**** *******************@*****.*** Linkedin

Professional Summary

Motivated and technically skilled Computer Science graduate with hands-on experience in frontend development, full-stack projects, and AI/ML applications. Proficient in JavaScript, React, Node.js, and Python with a strong understanding of responsive web design, APIs, and security best practices. Passionate about building user-centric, accessible, and scalable software systems. Seeking to contribute to innovative development at Apple by delivering impactful, secure, and optimized applications. Technical Skills

Languages: JavaScript, TypeScript, Python, HTML5, CSS3, Java Frameworks/Libraries: React.js, Angular, Node.js, Express.js, RxJS Tools & Technologies: Git, REST APIs, Figma, Wireframing, MongoDB, Firebase, AWS (EC2/S3), Docker

Concepts: Responsive Design, Accessibility, Cross-Browser Compatibility, Secure Coding Practices Others: Agile, GitHub Actions, Jira, VS Code

Soft Skills:

Problem-Solving Analytical Thinking Team Collaboration Communication Debugging Continuous Learning

Education

Master of Computer Science

Bhavan’s Vivekananda College, Hyderabad, Telangana— 2023–2025 Relevant Coursework: Distributed Systems, Advanced Algorithms, Optimization Techniques, Cloud Computing Bachelor of Technology in Computer Science Government Degree College, Siddipet, Telangana — 2020–2023 Projects

• Visual Description Generation and Audio Synthesis AI Accessibility Project Python, TensorFlow, gTTS, Flask, HTML/CSS/JS

• Developed an AI-driven application that generates image captions and converts them into audio for visually and hearing-impaired users.

• Implemented a Vision Transformer (ViT) for image captioning and multilingual speech synthesis using Google Text-to-Speech API.

• Designed a responsive and accessible frontend using HTML5, CSS3, and JavaScript, ensuring WCAG compliance.

• Built RESTful Flask backend integrated with AJAX for real-time user interaction and efficient data flow.

• Optimized the system to support multiple languages and audio formats, enhancing UX across diverse user groups.

• Deployed the system on local servers and packaged it as a desktop app using Tkinter and PyInstaller.

• Keywords included: accessibility, image captioning, audio synthesis, AI, Python, Flask, responsive UI, REST API, WCAG, speech-to-text, frontend-backend integration, UX/UI. Certifications

− Introduction To Machine Learning - NPTEL (IIT Kharagpur)

− Cloud Based Machine Learning - Gyan Astra IT Solutions

− Data Structures & Algorithms – Coursera

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