- Led summer coding camps for 20+ students and conducted smaller 1-3 student sessions, teaching Python, Java, and Scratch- Collaborated with tutors and parents to tailor lessons, create fun projects, and track progress- Helped students overcome challenges and showcase their work while maintaining an engaging andsupportive learning environment

- Collaborated with Dr. Blinov to design and develop machine learning models for Monkeyflower pigmentation patterns from reaction-diffusion systems- Implemented deep learning algorithms with TensorFlow and created data visualizations using Matplotlib and Seaborn- Applied dimensionality reduction techniques including tSNE and UMAP for data analysis- Conducted data cleaning and preprocessing to ensure high-quality input for ML models- Developed interactive visualizations to communicate research findings effectively

- Partnered with a PhD candidate to investigate binding mechanisms and docking behavior of melanocortin 4 receptor- Learned and applied Linux operating system skills for project-specific tasks- Utilized specialized software including PyMOL for molecular visualization and HADDOCK for protein- protein docking- Employed high-performance computing for advanced molecular simulations- Analyzed complex computational data to derive insights into receptor behavior- Presented technical findings to faculty and PhD researchers, effectively communicating complex concepts