I'm a Master's student in Computer Science at CSU Chico (projected graduation: Spring 2027), focusing on machine learning and backend systems that power real-world applications.
Right now, I'm a graduate researcher with the Elephant Listening Project, where I work on detecting infrasound elephant vocalizations using deep learning. I handle data preprocessing, model training, and performance evaluation using TensorFlow, NumPy, and pandas on large-scale time-series datasets.
Previously, I was a fellow in Cornell Tech’s Break Through Tech AI program, where I completed a Foundations of Machine Learning certificate and partnered with Fermata Energy on a time series forecasting project for electric vehicle-to-building energy loads.
I also built DJ SongMatch, a web tool that helps DJs curate seamless setlists. I designed the database, developed a Flask backend, and implemented a vector similarity model with FAISS and SQL filtering for real-time music recommendations.
I’m passionate about creating systems that improve workflows and user experience through clean, reusable code and thoughtful automation. I’m a lifelong learner and a proactive team contributor who often steps into leadership roles to help guide projects, support teammates, and keep development moving forward.
I am especially passionate about learning and growing in the cross section between computer science and music/audio. Open to internship opportunitities.
Languages
Python • C++ • JavaScript • HTML/CSS • SQL • Bash
Machine Learning and Data Science
TensorFlow • PyTorch • Keras • XGBoost • CatBoost • FAISS • Deep Learning • CNNs
Data Preprocessing • Feature Engineering • Evaluation • Time Series Forecasting
pandas • NumPy • Scikit-learn • Matplotlib • Seaborn • Librosa
Backend & Dev Tools
Flask • SQLAlchemy • Docker • Git • Jupyter Notebooks
Concepts & Infrastructure GPU/TPU Acceleration • High Performance Computing (HPC) • Remote SSH Access • Linux Environments
Soft Skills
Project Management • Problem Solving • Team Collaboration • Communication • Leadership