Gopal Dwivedi

• Completed Nvidia Fundamentals of Deep Learning program
• Winner of Code Canvas 3.0
• Presented at the International Conference on Information Technology, 04/01/24
• 2nd Runner-up in Code Canvas 2.0
• Participated in IEEE Mega Hackathon 7.0 at BIT Mesra
• Competed in Amity CyberCup 2023
• Participated in Intel AI for All initiative
• Engaged in the AI Global Impact Festival
• Attended AI for Youth Symposium
• Completed online internship with Mindler

Less Time Tution(Gemini, Node js, Javascript, CSS, HTML): an innovative educational portfolio website offering pre-recorded lecture videos covering Applied Mathematics 1 to 4, a personalized exam planner for effective study schedules, and a comprehensive notes section for quick revision The platform integrates a hybrid LLM model (trained data and API calls) to provide real-time query responses, enhancing the learning experience The interactive and reactive UI ensures a seamless, and intuitive user experience 

College Counseling System(Gemini, Javascript, CSS, HTML ) is an interactive web-based platform designed to help students select the best JEE colleges based on their ranks, categories, and quotas. It features dynamic filtering, allowing students to refine their search based on rank range, category, quotas, and branch preferences with real-time updates. The system also includes a college comparison tool that enables side-by-side analysis of multiple colleges based on cutoff ranks, courses, faculty, placements, and campus facilities, presented through visual comparisons like charts and tables. To further enhance user experience, an AI-powered chatbot provides detailed insights on admission processes, faculty, fees, placements, and more, offering instant responses to students' queries. By leveraging past JEE counseling data, this system ensures a data-driven, personalized, and efficient approach to college selection, making the decision-making process seamless and well-informed.

AI-based keyboard(OpenCV, Mediapipe, Python) built a virtual keyboard using machine learning and computer vision with OpenCV and MediaPipe, and used hand gesture recognition techniques as input 

AI system for face detection and attendence (OpenCV, Arduino, Python) automated visitor and student records during the pandemic by storing names, class, entry time, and body temperature in a CSV file using Dlib and OpenCV AI-based Face Mask Detector, OpenCV, Python, Developed a model that detects if a person is wearing a mask or not, using bounding boxes with confidence levels.

• Hindi
• English