Aryan Aligeti

Dynamic video editor and content creator with a proven track record at self-employment, enhancing brand engagement through innovative social media strategies. Expert in Adobe After Effects and Davinci Resolve, I deliver high-quality narratives while fostering community connections. Adept at script writing, I blend creativity with technical skills to produce compelling content.

Won 1st place with a prize of 1.5 lakhs(150k) in a National Level Hackathon conducted by Chaitanya Bharathi Institue of Technology in collaboration with Microsoft and ByteXL on 2024.

Won 1st Place iin National Level Hackathon conducted by Forge Alumnus Services Pvt.Ltd at IIT Hyderabad witha prize of around 36k

Won 3rd Place in National Level Hackathon conducted by TechXcelerate - Birla Institute of Technology and Science, GOA on Feb of 2025 with Prize of 20K

Won 3rd Place in a National Level Hackathon conducted by Vidyavardhini's College of Engineering and Technology, Maharashtra with a prize of 5k

Personal Expense Tracker | [https://expense-tracker-sigma-green.vercel.app/] | [https://github.com/aryan1429/Expense_tracker]

 Tech Stack: React, Node.js, Express, MongoDB, Recharts, Vercel, Render

• Developed a full-stack web application to provide users with a seamless way to manage personal finances, featuring full CRUD (Create, Read, Update, Delete) functionality for expenses.
• Built a RESTful API with Node.js and Express to handle all backend logic and data manipulation, with data persisted in a MongoDB Atlas cloud database.
• Created a dynamic and responsive single-page application (SPA) with React, utilizing hooks for state management and Axios for asynchronous API communication.
• Implemented a data visualization feature using the Recharts library to render a real-time pie chart of spending distribution by category, offering users immediate financial insights.
• Successfully deployed the application by containerizing the backend on Render and hosting the frontend on Vercel, ensuring continuous integration and delivery.

TextMood DJ 🎧 — Emotion-Based Music Recommendation System [https://github.com/aryan1429/Text-MoodDJ.git]

Tech Stack: Python, Flask/FastAPI, Hugging Face, Whisper, gTTS, ytmusicapi, React.js, Redis/SQLite, Vercel, Render.

• Designed and developed a multimodal AI assistant that analyzes user input (text or voice) using sentiment analysis + speech-to-text (Whisper) to detect emotions in real time.
• Integrated YouTube Music API to dynamically recommend and play mood-matching playlists, songs, or memes based on the detected sentiment.
• Implemented a full-stack architecture with Flask/FastAPI backend (Python, Hugging Face Transformers, ytmusicapi) and a React frontend for an engaging UI.
• Built support for session-based personalization per device, ensuring isolated user experiences across multiple clients.
• Added text-to-speech (TTS) feedback and color-themed UI that changes dynamically with mood (e.g., yellow for happy, blue for sad).
• Deployed on cloud platforms (Vercel + Render), ensuring smooth cross-device accessibility and scalable performance.