Tirth Patel

Developing a decentralized app that used AI to mint NFTs was an incredible learning experience for me. I had to become proficient in several different technologies, including Solidity for building smart contracts, Hardhat for testing and development, React for the UI, MetaMask for secure user interaction, and web3.js for interacting with the Ethereum blockchain. Additionally, I used Node.js to build the backend server that communicated with the blockchain and AI APIs. I also utilized the IPFS protocol for the NFT storage. This project was exciting because I was able to combine the recent craze for AI-generated artwork with NFTs and the blockchain!

When I built this triangular arbitrage bot to exploit market discrepancies in the crypto world, I relied on Python to develop the bot's trading algorithms and leveraged REST APIs to connect it to various exchanges. The Poloniex and Uniswap exchanges were particularly helpful in understanding and executing profitable trades. Not only have I gained valuable insights into algorithmic trading, market dynamics, and risk management, but I've also had a blast identifying profitable opportunities, devising trading strategies, and executing transactions!

Creating this project using HTML, CSS, and JavaScript was a fulfilling experience for me. Not only did it allow me to showcase my portfolio, but it also helped me gain a deeper understanding of front-end. I enjoyed experimenting with different design and functionality options, and I am proud of the final result!

With my extensive experience in the tools and frameworks used in my recent project, I was able to create a web3.0 version of a Discord clone that was nothing short of impressive. Using Solidity to create smart contracts on the Ethereum blockchain was second nature to me, and I was able to create intricate and dynamic contracts that added depth and complexity to my project with ease. My experience with JavaScript allowed me to seamlessly add interactivity and functionality to my project, skillfully combining it with other technologies such as web3.js, React, and node.js. Leveraging my expertise with React, I crafted complex and interactive user interfaces with ease, effortlessly leveraging the power of the framework. Finally, my experience with socket.io allowed me to create a real-time, chat-based platform that could easily handle a large number of users. Overall, my project showcased my proficiency in the tools and frameworks used, and was a testament to my expertise in creating powerful, dynamic web applications.

I worked on a groundbreaking tool that utilized machine learning and OpenCV for dental cavity detection. The aim was to develop a more efficient and accurate alternative to traditional x-ray technology. Our team of 4 trained a machine learning model to identify and classify the cavities, and used OpenCV to highlight their location and direction. To store patient data, we used SQLAlchemy, which allowed us to easily access and manage patient information. We installed a CMOS photodetector which would capture light shone from an NIR LED through the tooth. To power the entire system, we used a Raspberry Pi, which made the project more portable and cost-effective. This project is a game-changer in the dental industry, as it provides a non-invasive and cost-effective solution to cavity detection. I am proud to have been a crucial part of this innovative project and look forward to seeing its impact in the field.

My Hack the North 2021 project involved using Flask API on Google Cloud Platform (GCP) to fetch real-time data from a gyroscope and accelerometer, and then using Python to process the data to classify the pushup form of the user. Our team of 4 used Flask API to create a RESTful API that could receive the data from the sensors and process it at the backend to identify the pushup form. To host our app, we used Firebase, which allowed us to easily deploy and manage our application. We used ReactJS to develop the front-end. This project was challenging yet rewarding, as we had to overcome various technical hurdles and optimize the code to achieve real-time processing.