I’m a high school student passionate about computer science, biology, and robotics. With experience in Java, Python, R and software development, I enjoy applying my skills to solve complex problems and collaborate on impactful projects. Currently, I’m working on bioinformatics research, contributing to FRC robotics, and diving deeper into Machine Learning.
- Languages: Python, Java, R, Javascript, HTML, CSS
- Tools: Git, LINUX
- Working on Scientific Article Summarizer
This project leverages E. coli data sourced from both NCBI and the UCI Machine Learning Repository to explore the intersection of biology and machine learning. The goal is to create predictive models, delve into phylogenetic analysis, and conduct comprehensive tests using a combination of biological and computational tools.
This project focuses on reproducing key climate change graphs that have been widely used in scientific and news articles. By leveraging R’s powerful data analysis and visualization capabilities, the project aims to provide clear, reproducible results to help draw trends relating to global warming and climate change.
A collection of Jupyter Notebooks exploring various machine learning concepts, algorithms, and datasets. Includes classification, regression, NLP, clustering, and neural networks created in Python and R. Designed for learning and exploring various Machine Learning algorithms. Projects include detection of exoplanets using transit photometry, breast cancer biopsy classification, and sentiment analysis using natural language processing.
A simple but effective Pomodoro timer built using HTML, JavaScript, and CSS. The Pomodoro Technique is a time management method that breaks work into intervals, traditionally 25 minutes separated by 5 minute breaks.
This repository contains the code for FRC 199’s 2024 robot, for the Crescendo Game. The code uses WPILib and libraries to control the robot and enable autonomous and teleoperated operations. My primary contributions were to the arm and intake/shooter subsystems.
An online foosball game created using Javascript, HTML, CSS, and the Pixi JS library through the More Active Girls in Computing Internship
This project applies machine learning techniques to predict Matrix Attachment Regions in the human genome. Presented at the Southern California Conference for Undergraduate Research (SCCUR), this work demonstrates how computational approaches can enhance biological research.
Exploring the function and significance of Transmembrane Protein 62 (TMEM62) using biological databases and computational tools. This project analyzes gene expression, protein structure, and evolutionary conservation through resources like NCBI, UniProt, and Ensembl to uncover potential roles in cellular processes and disease mechanisms.