Hi, I’m Ragi Sai Ruthvik, a passionate and driven software developer and data science enthusiast with a talent for tackling complex problems and crafting innovative solutions. Currently pursuing my Bachelor of Engineering in Computer Science at Maturi Venkata Subba Rao Engineering College, I’ve developed a solid foundation in programming, data structures, machine learning, and cutting-edge technologies. Beyond coding, I am a skilled chess player, proudly ranked in the top 6% globally on Lichess with a rapid rating of 2093. My dedication to chess has honed my critical thinking, decision-making, and pattern recognition abilities, which seamlessly enhance my approach to solving technical challenges. As a lifelong mathematics enthusiast, I thrive on unraveling intricate problems and applying logical reasoning to both my personal and professional pursuits. With a blend of analytical precision and a passion for innovation, I am constantly striving to push boundaries, master new technologies, and make meaningful contributions in the tech world.
Collaborated with cross-functional teams to develop responsive user interfaces, using Git for version control. Wrote and executed SQL unit tests to validate stored procedures, triggers, and complex queries, ensuring 100% accuracy of database operations.
Developed a FAQ and query handling system using a Rule-Based Machine Learning Model to handle queries about company policies, product details, and support. Reviewed 50+ codes on Machine Learning, APIs, and Data Science in Python.
Achieved a CGPA of 8.96/10, with a focus on coursework in Data Structures and Algorithms, Object-Oriented Programming, Operating Systems, Database Management Systems, Machine Learning, and Artificial Intelligence. Actively engaged in technical projects, internships, and co-curricular activities, showcasing a passion for technology and problem-solving.
Developed machine learning models (Ridge, Lasso, kNN, CNN) in Python to predict chess Elo ratings from PGN game data, achieving improved accuracy on 30K test games. Implemented feature extraction methods like Game2Vec, time series analysis, and move text encoding to capture player advantage and board state patterns.
View ProjectDesigned and implemented a Rubik’s Cube solver using the IDA* algorithm with state representation and pruning techniques. Developed transition tables and efficient data structures to minimize search space and enhance solver performance.
View ProjectCreated an interactive 3D visualization using p5.js, incorporating real-time user inputs such as keyboard, mouse, and microphone for dynamic rendering. Deployed a responsive web app for dynamic, input-reactive, and audio-reactive visual art.
View Project