The Story So Far
As a CS student focused on AI/ML and Cloud Native development, I specialize in Python-driven solutions and DevOps workflows. From my internship at Infosys to building my own mini-Docker engine, I am obsessed with the 'how' behind the 'what'. A proud open-source contributor and a lifelong student of the tech stack.
Featured Works
Selected projects that define my journey.
- ■Voice-activated Linux assistant for natural-language system control and automation.
- ■Hybrid edge-cloud architecture optimized for low-RAM hardware via the Gemini 1.5 API.
- ■Features sub-second intent routing and persistent SQLite-backed conversational memory.
- ■Extracts video transcripts automatically.
- ■Gemini-powered summarization.
- ■Saves users up to 45% of time in video content review.
- ■Provides ATS feedback & suggestions.
- ■Increases resume selection chances by 50%.
- ■Live content analysis and scoring.
- ■Write anonymous confession in the form of Shayari or Poetry
- ■Generate a unique LoveLink for each confession
- ■Sharable link like ngl.link but with poetic twist.
- ■No login required - privacy focused and free
- ■Securely share one-time secrets like passwords or OTPs
- ■Each secret generates a unique self-destructing link
- ■Secrets auto-delete after being viewed once
- ■No signup needed – fast, lightweight and secure
- ■Decodes WAV audio to PNG.
- ■No hardware dependency.
- ■Supports multiple SSTV transmission formats.
- ■Lightweight FAQ chatbot that serves answers exclusively via REST endpoint.
- ■Handles common queries like 'what's your opening time?' -> returns 'We are open from 8:00 a.m to 10:00 p.m'
- ■Simple JSON request -> JSON response flow : no frontend dependency.
- ■Worked with 3D models & UV texture wrapping.
- ■Integrated image-texture positioning in exact regions of mannequin.
- ■Enabled realistic saree draping on virtual models.
Work Timeline
Architected and deployed an AI-powered Enterprise Intelligence Hub utilizing GraphRAG to transform unstructured support tickets into a zero-hallucination customer query resolution system.
- ●Engineered an enterprise-grade GraphRAG pipeline integrating LangChain and Meta’s Llama-3 via the Groq API to deliver contextually accurate, sub-second natural language queries.
- ●Developed a custom Pandas ETL pipeline to clean and normalize unstructured enterprise data, generating high-density embeddings using Hugging Face models.
- ●Unified the system architecture by implementing a Native Vector Index directly within Neo4j AuraDB, eliminating data-sync latency and deprecating external vector databases.
- ●Built a dynamic Streamlit analytics dashboard featuring real-time KPI tracking, conversational LLM memory, and interactive physics-based network visualizations.
- ●Designed an idempotent graph ingestion layer using Cypher MERGE operations, ensuring fault-tolerant data loading and preventing database duplication.
Currently completing a 45-day internship working on an AI-powered virtual try-on platform for ethnic wear, inspired by Google’s AI Try-On Technology.
- ●Developed and integrated backend APIs to support 3D model manipulation, cloth rendering, and texture mapping.
- ●Used UV-mapped 3D models to wrap saree, blouse, and pallu textures onto accurate body parts of the mannequin.
- ●Implemented precise texture positioning and alignment algorithms to ensure realistic draping and seamless transitions.
- ●Collaborated with AI and design teams to automate cloth fitting using simulated fabric physics and motion data.
- ●Optimized asset loading and rendering time to improve real-time user experience on the platform.
Participated in the global month-long open-source event, contributing bug fixes and enhancements to multiple repositories.
- ●Improved feature implementations, documentation, and accessibility in React + Python projects.
- ●Integrated API and contributed in various python projects, Strengthened Git/GitHub workflow experience.
Contributed to real-world open-source projects focused on education and community development, implementing scalable features and optimizing code structure.
- ●Implemented scalable features, optimized code structure, and resolved existing issues.
- ●Participated in weekly standups, code review cycles, and collaborative development on GitHub.
Collaborated on blockchain-based DApps and smart contract repositories, improving documentation and test coverage.
- ●Wrote documentation for Web3 onboarding and transaction flows.
- ●Improved test coverage for Solidity-based contracts and integrated blockchain UI components.
Focused on open-source projects with social impact, enhancing user experience and accessibility in React-based frontends.
- ●Enhanced user experience and accessibility features in React-based frontends.
- ●Authored beginner-friendly guides and issue walkthroughs to help onboard new contributors.
Tech Toolbox
Professional arsenal of high-performance tools.
- Python
- C
- JavaScript
- HTML
- CSS
- RESTful APIs
- Postman
- NumPy
- Pandas
- TensorFlow
- Matplotlib
- OpenCV
- Streamlit
- MySQL
- AWS
- Git
- GitHub
- Data Structures
- Algorithms
- Networking
- Windows
- Python
- C
- JavaScript
- HTML
- CSS
- RESTful APIs
- Postman
- NumPy
- Pandas
- TensorFlow
- Matplotlib
- OpenCV
- Streamlit
- MySQL
- AWS
- Git
- GitHub
- Data Structures
- Algorithms
- Networking
- Windows
Credentials
Validated proof of digital competence.
Demonstrated proficiency in building, testing, and documenting APIs using Postman.
Completed frontend and backend fundamentals for full-stack development.
Gained foundational knowledge of IoT architecture, microcontrollers, and sensor-based communication.
Covered key concepts in data protection, authentication, phishing, and secure network practices.
Learned budgeting, financial planning, digital transactions, and personal money management.
Completed a course focusing on neural network architectures and their applications in deep learning environments.
Learned fundamentals of generative models such as VAEs and GANs, and their applications in AI.
Gained understanding of RPA tools and how automation improves efficiency in repetitive business processes.
Studied GPT-3 architecture and built practical use-cases involving prompt engineering and NLP.
Covered Scrum principles, Agile roles, sprint planning, and daily stand-ups in a simulated environment.
Learned foundational concepts of Generative AI including ethical considerations, use cases, and evolution.
Introduced to OpenAI's family of GPT models and how to apply them in language generation tasks.
Completed basic training on computer vision, image processing, and neural networks using visual data.