Welcome! I am an undergraduate student at the University of California San Diego, pursuing a B.S. in Computer Science. Currently, I am a member of Dr. Rose Yu’s Spatiotemporal Machine Learning Lab, where I am involved in research related to Deep Learning and Reinforcement Learning for biomedical applications. My primary research interest is in Machine Learning and its applications to complex decision-making problems, particularly in healthcare.

Education

Undergraduate, University of California San Diego (Sept. 2022 - June 2026)
B.S. Computer Science, 3.8 GPA

Honors and Awards

• Regents Scholarship, UC San Diego (2022 - 2026)
• IDEA Scholarship, UC San Diego (2022 - 2026)
• Semi-Finalist, National Merit Scholarship Corporation (2022)

Experience

Undergraduate Researcher
Dr. Rose Yu Spatiotemporal Machine Learning Lab, University of California San Diego

• Collaborated with Abiomed, a Johnson & Johnson Medtech company, on Aortic Pressure Forecasting and Smart Weaning using Deep Learning.
• Focused on developing data-driven recommendations for physicians treating patients with mechanical circulatory support (MCS) devices.
• Assisted with data analysis, preprocessing, and figure creation, contributing to the development of a reward scoring function.
• Currently improving the model and exploring reinforcement learning algorithms such as Model-based Offline Policy Optimization (MOPO) and Model-Based Offline Reinforcement Learning (MOReL).
• Co-authored a paper accepted to the 6th Annual Learning for Dynamics & Control Conference (L4DC) at the University of Oxford, titled “Data-Driven Simulator for Mechanical Circulatory Support with Domain Adversarial Neural Process.”
• Leveraged Knowledge: Python, PyTorch, Jupyter Notebook

Software Development Engineering Intern
Amazon Web Services (AWS) | June 2024 - August 2024

• Worked on the Computer Vision Data Platform Team to contribute to scalable data platforms for AWS services such as Textract and Rekognition.
• Collaborated with Machine Learning Scientists and Dev Ops, reducing engineering effort and optimizing system performance by developing a new internal feature using TypeScript, Java, Docker, and native Amazon tooling.
• Leveraged Knowledge: TypeScript, Java, Docker, AWS Native Tooling

Software Engineering Intern
Parsec Automation Corp. | July 2023 - Sept 2023

• Led the integration of the MQTT networking protocol using C# and Visual Studio, improving real-time data processing efficiency by 20% for clients like Pfizer, Nestle, and Procter & Gamble.
• Developed a generative AI application for SQL querying with a data visualization feature, boosting data interpretability by 40%.
• Leveraged Knowledge: C#, Visual Studio, MQTT, SQL, Generative AI

Software Developer at JuiceMind

• Developed a high-performance ReactJS dashboard querying a Firebase database with over 30,000 users, improving marketing data access.
• Implemented the “Weekly Movers” feature, contributing to a 25% increase in sales by enabling immediate follow-ups on customer engagement.
• Managed the sales pipeline independently, including closing a deal with Girls Who Code.
• Leveraged Knowledge: ReactJS, JavaScript, HTML, CSS, Git, AWS

Instructional Assistant - Computer Science and Engineering Department
University of California San Diego

• Tutored over 700 students in Data Structures and Object-Oriented Programming (Java, C++).
• Provided support through office hours and ticket-based assistance, mentoring students and improving their grades and confidence.

C.R. Laurence Engineering Intern
Summer 2021

• Worked with Autodesk Inventor and iLogic software to design models of industrial products.
• Leveraged Knowledge: Autodesk Inventor, CAD, iLogic

Technical Skills

• Languages: Python, Java, C/C++, C#, SQL, JavaScript, HTML/CSS, R, TypeScript
• Frameworks: React, Node.js, Flask, JUnit, Material-UI, REST API
• Developer Tools: Git, GitHub, Docker, VS Code, Visual Studio, Eclipse, AWS
• Libraries: pandas, NumPy, PyTorch, Matplotlib