My name is Ayan Raghunathan, and I am a first-year student at the Georgia Institute of Technology pursuing a degree in Computer Engineering. I am an adept and methodical developer with experience working on a variety of software projects, both independently and in collaborative team environments. Through these experiences, I have built a strong foundation in problem-solving, writing clean and efficient code, and effectively communicating within a group to deliver high-quality results.

I am skilled, driven, and innovative, with a receptive and responsive mindset that allows me to quickly identify areas for improvement and continuously refine my work. I take pride in being detail-oriented while maintaining efficiency, ensuring that my solutions are both robust and scalable. My ability to learn quickly and apply feedback has been key to my growth as a developer and teammate.

I am currently seeking a Summer 2026 internship in software development where I can apply my technical skills, strong work ethic, and collaborative mindset in a professional setting. I am eager to contribute to meaningful projects, learn from experienced engineers, and continue developing my skills by tackling real-world challenges.

Conversion App | July 2024 – September 2024
Creator

• Developed a multi-functional unit conversion application for Android using the Python-based Kivy framework, enabling users to accurately convert values across mass, volume, temperature, and length.

• Designed an intuitive and responsive user interface to ensure ease of use and efficient navigation between conversion categories.

• Implemented modular and scalable code structure to support future feature expansion and maintainability.

• Tested and debugged the application to ensure accuracy of calculations and consistent performance across different inputs.

Arduino Traffic Light System

• Designed and implemented a traffic light control system using an Arduino microcontroller, integrating red, yellow, and green LEDs with a pushbutton for pedestrian interaction.

• Programmed sequential light transitions to simulate real-world traffic flow, incorporating timing control for each signal phase.

• Implemented conditional logic to override the normal light cycle when the pushbutton is pressed, triggering a red-light state to allow for a pedestrian crossing interval.

• Utilized digital input/output operations and debouncing techniques to ensure reliable button detection and system responsiveness.

• Gained hands-on experience with embedded systems concepts, including hardware-software integration, real-time control, and circuit design.

NFL Predictive Model | October 2025 – Present

• Initiated development during an AI-focused hackathon, building a machine learning model to predict outcomes of NFL games using historical data.

• Performed extensive data preprocessing, including cleaning datasets, handling missing values, and structuring raw data for model readiness.

• Engineered meaningful features such as team performance metrics, player statistics, and game conditions to improve predictive accuracy.

• Implemented and experimented with multiple machine learning algorithms to evaluate performance and optimize predictions.

• Currently conducting model validation, hyperparameter tuning, and error analysis to improve generalization and reduce overfitting.

• Designed the backend modeling pipeline with future integration of a user interface in mind, though full UI development is still in progress.