Isaac Hwang's Resume

Skills

Languages: Python, SQL, Java, C++, HTML, CSS
Libraries: PyTorch, Tensorflow, scikit-learn, pandas, NumPy, Matplotlib, Seaborn
Developer Tools: Git, VS Code, Visual Studio, PyCharm, IntelliJ, Eclipse
Frameworks: JUnit

Education

University of California, Berkeley

Bachelor of Arts in Data Science; GPA: 3.82
Aug. 2023 -- May 2026

Gavilan College

Associate of Science in Computer Programming, Mathematics; GPA: 3.88
Aug. 2019 -- May 2023
Relevant Coursework: Principles of Data Science, Data Structures, Discrete Math & Probability

Experience

Undergraduate Research Assistant

University of California, Berkeley; Data Science Discovery Program, Berkeley, CA
Sep. 2023 -- Jan. 2024

Developed OCR model for Old Assyrian characters with Dr. Adam Anderson, PhD
Utilized OpenCV, SPARQL, pandas, Python
Catalogued the MaiCuBeDa dataset for training

Data Science Intern

San Jose State University, San Jose, CA
June 2022 - Aug. 2022

Trained multiple classification models with scikit-learn with average accuracy of 80% on student performance data
Utilized Seaborn/MatPlotLib to create relevant statistics and visualizations of student data
Presented to Dr. Shih-Yu Chang, PhD at the SJSU CE department

Logistics Lead

Gilroy Hacks, Gilroy, CA
Jan. 2022 -- June 2023

Organized two hackathons raising $1000+ in prizes and 40 participants
Reached out to local community business sponsors and tech companies, personally securing 3 sponsors
Coordinated event logistics, venue organization, and outreach with Gilroy Library and Gavilan College
Developed 3-page work plan for all departments, specifying tasks and roles

Projects

Spam Email Classification Model

April 2024

Trained a logistic regression model on a dataset of 8000+ emails to classify spam emails with an accuracy of 86%
Applied cross-validation and PCA techniques with Scikit-Learn
Visualized dataset features with Seaborn and MatPlotLib
Implemented Regex string manipulation / NLP techniques in feature engineering script

Visually-Impaired Assistance Application

April 2024

Trained machine learning model with PyTorch and TensorflowLite that identifies obstacles in visual field
Built Android application that implements model and communicates obstacle information with vibrations
Wrote script to convert PyTorch models into Tensorflow models
Performed literature review of latest computer vision algorithms recorded in 10-page paper
Presented project to industry experts in computer software