Developed a platform for extracting a unique and malleable list of facts from documents based on user questions, improving document analysis and information retrieval processes. Implemented real-time data submission and processing using FastAPI and ReactJS for a smooth user experience. Utilized the OpenAI API for accurate and relevant fact extraction.
Constructed an innovative companion platform by integrating OpenAI's API for real-time, customizable interactions with A.I. characters. To ensure efficient performance and future scalability, I employed a dual-database approach: PrismaDB for relational data and a specialized vector database for A.I. data storage. This optimized both read/write operations and scalability, making the platform both user-friendly and technically robust.
Built a user-centric decentralized NFT marketplace on the Ethereum Sepolia Testnet using Solidity and Javascript, providing a secure platform for the transaction of unique digital assets. Incorporated Apollo Client and TheGraph for efficient state management, facilitating real-time querying and indexing of blockchain data. Employed IPFS for decentralized storage and retrieval of NFT metadata. This project demonstrates my ability to engineer intuitive user interfaces, manage data efficiently, and ensure secure and decentralized data storage.
Designed a Solidity-based Decentralized Finance(DeFi) protocol for a stablecoin, integrating real-time price feeds and employing algorithmic minting for stability. Utilized Forge for streamlined contract deployment on the Sepolia Testnet and comprehensive unit testing, highlighting proficiency in blockchain technologies and commitment to quality assurance.
Pioneered a Python algorithm to streamline shipping container operations, ensuring efficient loading/unloading processes and precise weight distribution. Effectively reduced operational risks and enhanced vessel stability. Incorporated a comprehensive logging system for improved traceability, and collaborated closely with a frontend team to integrate backend functionalities.
Architected an efficient search engine for Reddit using Python's PRAW library and PyLucene, enabling optimal data extraction, organization, and ranking of posts from subreddits. The system mitigates API rate limitations and manages extensive data volumes, providing accurate and efficient information retrieval. The search engine was made user-friendly through a Flask-based web interface, presenting the top 10 relevant posts in response to user inquiries.
The Embedded Systems Running Simulator, designed using the Arduino language, is a real-time athletic experience replicator. It captures the nuances of a runner's movement and environmental conditions. The project expertly integrates multiple hardware components, including breadboards, joysticks, LEDs, and various sensors, transforming real-time data into dynamic visual output on an LED display, and brings to life the interactive aspects of a runner's speed, direction, and rest periods.