Computer Science ∩ Biology — Machine Learning for Medical Innovation
I am a dedicated and enthusiastic high school student eager to contribute my skills and passion to an internship. With technical skills in Python, R, and Java, and research experience in bioinformatics, I bring a strong foundation in problem-solving and data analysis. I excel in collaborative environments and hold leadership roles on my school's FRC robotics and girls' basketball teams.
We present a unified, multilingual AI framework for dysarthria, a speech disorder linked with neurological diseases. Our system implements detection, severity classification, speech restoration, automatic speech recognition, emotion recognition, and voice cloning in one pipeline. Achieving up to 97% accuracy across English, Russian, and German, the project demonstrates strong cross-lingual generalization and transfer learning, enabling accessible diagnosis and removing communication barriers.
Various Machine Learning Notebooks created during the MIT Beaverworks Summer Institute including, Time Series Signal Processing for Sleep State detection, Random Forest Detection of Hyperthyroidism, and Breast Cancer detection with Convolutional Neural Networks.
Proposed a smart contact lens concept to address high complication rates following corneal transplants and injuries. The design integrates electrical stimulation and localized drug delivery within a biocompatible hydrogel framework to improve post-operative care with an active healing approach. Presented research to UC Berkeley professors and undergraduates; recognized for innovation, scientific rigor, communication, and feasibility at Berkeley Bioengineering Competition.
Machine learning-based detection of scaffold/matrix attachment regions (S/MARs) in the human genome, using Random Forest, XGBoost, KNN, and Neural Network models to advance research into chromatin organization and cancer.
Analyzed the NASA OSD-254 dataset to investigate microgravity's effects on skin immune genes in mice. Differential expression revealed upregulation of Skint3 and Skint9, with pathway enrichment confirming activation of epidermal and immune response pathways, suggesting skin–immune adaptation in microgravity and potential targets for astronaut health during long-duration missions.
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.