Developer

Mayank Ravariya  • Peerlist

I spearheaded the development of the IPL Auction Web App to simulate the excitement of a live auction and allow users to build their dream cricket teams from home. This project marked my first foray into the MERN stack, demanding extensive learning and application. Key Features: Real-time Updates: Leveraged WebSockets for dynamic player auctions and transactions, ensuring real-time interactivity. Multi-Slot Capability: Enabled handling multiple simultaneous games for scalable and efficient auctions. User-Friendly Interface: Designed a responsive and intuitive UI for enhanced user experience. Advanced Points Calculation Algorithm: Implemented a sophisticated algorithm considering player stats and strategies for accurate team performance evaluation. Deployment: Successfully deployed the app despite initial hurdles, ensuring seamless functionality integration. Technologies Used: Node.js & Express.js: For backend development and efficient routing. MongoDB: For flexible and scalable database management. WebSockets: For real-time communication and updates. React: For creating a responsive and intuitive user interface. Event Performance: Tested during the IPL Auction Event from March 29-31, 2024, across six offline and two online slots, the app performed flawlessly under load. This project enhanced my backend development skills and proficiency in MongoDB and WebSockets, preparing me for future technical challenges. Special thanks to Oculus S.P.I.T. and our dedicated team for making this possible.

IPL Auction

The primary objective of this website is to recreate the immersive experience of an IPL Auction. The website offers an interactive interface where users can build their dream teams and compete against others to climb the leaderboard, adding an element of excitement and competition. Key Features : 1) Dashboard displays your team of 11 players in the form of interactive cards. On clicking the card, it rotates to reveal the stats of the player. Special border effects for Legendary, Elite, and Women players, along with Power Cards, create an engaging, gamified environment. Real-time updates further enhance the user experience. 2) Calculator is equipped with a Drag-and-Drop feature, providing convenience and ease to users while selecting batsmen, bowlers and all-rounders. An algorithm runs to check whether all the conditions are met while building your team like constraint on the number of foreign players, at least one woman in the team, etc. If any condition is violated, a penalty is applied to the total score before displaying the final leaderboard. 3) The Spectate feature allows you to view the dashboards of other teams, enabling you to plan your moves strategically and monitor your competitors. 4) An admin panel is available to manage the flow of the auction. The admin is responsible for adding a player to a team and deducting the bid amount from their budget on successful purchase. A 'delete' option is also provided to revert changes in case of human errors. Developed using the MERN stack, the client side is deployed on Vercel while the server runs on Render. The website ran smoothly throughout the event, successfully supporting 8 slots of 10 teams each over a span of 3 days.

IPL Auction Website

Studdy Buddy: Revolutionizing Student Collaboration and Organization Studdy Buddy is an innovative platform designed to help students plan, organize, and enhance their study experience through seamless collaboration. Our unique features ensure that students can effectively connect with like-minded peers, stay organized, and achieve their academic goals. Key features of Studdy Buddys include: 1. Student Matching and Recommendations: a. Simple algorithms recommend and match students with peers who share similar interests and study habits. b. Swipe right to send friend requests or swipe left to reject recommendations, simplifying the process of building your study network. 2. Interactive Chat Rooms: a. Chat with friends and create group chats for collaborative discussions. b. Engage in real-time conversations to enhance your learning experience. 3. Live Document Collaboration: a. Collaborate on documents in real-time with your study group. b. Auto-saving feature every 5 seconds ensures that your work is never lost and can be restored even after a reload. 4. AI Chatbot Assistance: a. Advanced AI chatbot built using LangChain, implementing Retrieval Augmented Generation (RAG) for intelligent and contextual support. b. Get immediate help and answers to your study-related questions from the AI chatbot. 5. Goal Setting and Reminders: a. Set academic goals and receive timely reminders via email as deadlines approach. b. Stay on track with your study plans and never miss an important deadline. Studdy Buddys is your all-in-one solution for a more organized, collaborative, and productive study experience. Join us today and revolutionize the way you study!

Studdy Buddy

Study Sync is designed to bridge communication gaps and foster collaboration among students through an innovative web-based platform. We built this project during the SE Hackathon organized in our college, where we secured the 2nd place. Our primary goal was to provide a catchy and attractive interface to students which runs on the principle : Socialize and Study. Key Features : 1) Provide an experience similar to popular social media apps so that student promptly send friend requests to people with similar interests. 2) Students can set personalized goals and time limits. A reminder email will be sent to them to help ensure they completed their tasks on time. Used the node-mailer library for this. 3) Each chat session links to a personal collaborative document for seamless resource sharing and collective work. This enables students to co-edit documents in real-time, ensuring that everyone stays on the same page. 4) Single Prompt, two answers, one from ChatGPT and one from Gemini. Provides an in-app interface which displays both the answers side by side for easier comparison. 5) Students can upload a document and ask questions about its content. Answers are then generated based on the information within the document. We achieved this functionality using Retrieval-Augmented Generation (RAG) technology, implemented with Langchain. Developed using the MERN stack, Study Sync boasts additional tools such as Yarn, Vite, and Socket.io, which help in delivering a robust performance with appreciable pace.

Study Sync

Travel Smart: Revolutionizing Personalized Travel Recommendations Travel Smart aims to revolutionize personalized travel recommendations using state-of-the-art AI technology. Key technical features of Travel Smart include: 1. AI-Powered Chatbot: a. Designed and coordinated the development of an AI-powered chatbot to transform how travelers receive personalized suggestions. b. Enabled real-time interaction with users to provide immediate travel recommendations. c. Enhanced user experience with a conversational interface. 2. Advanced Image Recognition: a. Integrated advanced image recognition capabilities to enhance the chatbot's ability to provide personalized suggestions. b. Enabled users to upload images and receive relevant travel recommendations based on visual content. c. Improved the accuracy and relevance of suggestions through sophisticated image analysis. 3. Innovative AI Models: a. Utilized innovative AI models from Hugging Face API, Gemini API, and OpenAI API to ensure contextually relevant responses and ideas. b. Leveraged machine learning algorithms to understand user preferences and provide tailored recommendations. c. Continuously updated the AI models to enhance the chatbot's performance and accuracy. 4. Contextual Relevance: a. Ensured the chatbot provided contextually relevant responses and ideas through the use of state-of-the-art AI technologies. b. Integrated natural language processing (NLP) to understand and respond to user queries accurately. c. Adapted recommendations based on the context and nuances of user inputs. Travel Smart demonstrates the potential of combining AI with travel planning to create an intuitive and personalized user experience.