John Rathgeber

About Me

Hi! I'm John, a rising junior at Brown University, originally from Madison, Wisconsin, pursuing a double concentration in Mathematics-Computer Science and Music. I'm passionate about how logic, creativity, and innovation come together to solve problems in Computer Science.

Outside of classes, I do Competitive Programming to hone my critical thinking and coding skills. When I'm not coding, you can find me at the piano practicing my repertoire or composing my own music. My favorite composers are Chopin, Mozart, Beethoven, Bach, and Joplin. I also enjoy going to the gym, playing tennis, and reading in my free time.

I am most skilled in C++ and Python, but I also have experience with languages like Java, Javascript, and SQL. From my previous internships, I have gained valuable skills in problem-solving, working as a team, and project organization which I am currently applying at my internship as a software engineer at Electronic Theatre Controls. As an aspiring software engineer, I look forward to further honing my skills and contributing to impactful projects this summer.

If you'd like to connect, collaborate, or chat, please don't hesitate to reach out. Thank you for visiting my website!

me in front of Orwigheadshot
me playing pianolittle me winning piano award
me doing a funny poseme playing tennis

Projects

Tumor Detection

Tumor Detection

Led a team in developing a Convolutional Neural Network (CNN) to detect brain tumors in MRI scans, achieving a 90% accuracy rate on publicly available Kaggle datasets. Directed all stages of the project, including data preprocessing, model design, and performance evaluation, utilizing Python along with deep learning frameworks such as Keras and TensorFlow. Read the full report.

Causality and Mind Lab Website

Causality and Mind Lab Website

Collaborated with a small team of Full Stack at Brown members to create a website for the Causality and Mind Lab at Brown. Used Next.JS, Typescript, and Tailwind. View the full website.

Wisconsin DOT Position Estimation

Wisconsin DOT Position Estimation

Developed an algorithm that recognizes and maps street signs from a dataset of over 3 million images. This algorithm uses advanced computer vision methods such as monocular depth estimation and YOLO-based sign detection to compute real-world distances using exponential depth fitting and trigonometric projection. See the details.

Contact

Feel free to reach out!

Resume