2026 — 2027
University of Southern California
Master of Science · Analytics
- Statistical modeling & forecasting
- Machine learning for decision-making
- Data engineering & experimentation
Los Angeles, CA
06 / 07
About
I'm Dingxin Tao.
AI Native developer with a B.S. in Computer Science from UC Irvine, currently pursuing an M.S. in Analytics at USC. My focus is AI applications and full-stack development.
Background
My studies span computer science and analytics. My projects focus on AI applications and web and desktop products, bringing together programming, data handling, and interface design through working features.
The portfolio includes MultiMix, a video-creation workspace; opc-workspace, a local desktop workspace; Omnigate, based on new-api; and As-a, a bilingual professional-services platform. Each project page explains its scope and current status.
AI coding tools are part of my daily development workflow. I use them to analyze code, implement features, and review changes, then check the results by reading code, running checks, and testing manually. This website was built with the same approach.
I'm interested in the process from understanding a requirement to putting an application into use, and am looking to develop further in an AI application, full-stack, or FDE role. The blog documents methods and learning notes for reference and discussion.
Education
Academic background.
- Class of 2027
- Class of 2025
2023 — 2025
University of California, Irvine
Bachelor of Science · Computer Science
- Systems, algorithms & software design
- Machine learning & AI
- Human-computer interaction
Irvine, CA
- Class of 2023
2021 — 2023
Shoreline Community College
Computer Science
- Computer science fundamentals
- Linear algebra
- Probability theory
Shoreline, WA
Academic work
Research & publications
Two papers from my studies in applied machine learning, from an early classification experiment to a review of recommender systems.
- Literature reviewSole author
The Analysis of Recommendation Algorithms in Different Domains and Future Development Trends
Authors: Dingxin Tao
Applied and Computational Engineering, 145, 22–28 · Conference proceedings
A review of recommendation methods across application domains, discussing cold starts, sparse data, privacy, and explainability.
- Exploratory classification studyCo-author and corresponding author
Determining which physical parameters are significant for heart disease
Authors: Zhuoning Li · Dingxin Tao · Jiaao Zheng · Chenhao Zhu
Journal of Physics: Conference Series, 2010, 012062 · Conference proceedings
An early machine-learning study using a publicly available dataset of 297 records to compare classifiers with different feature sets and examine which variables were associated with heart-disease labels.
Projects
Project overview
- 01MultiMix: conversational video creation and asset management.
- 02opc-workspace: a local desktop workspace for one-person businesses.
- 03Omnigate: customization and deployment based on new-api.
- 04As-a: a professional-services platform in Arabic and English.
Approach to collaboration
Discuss concrete problems
Include the use case, relevant code, and expected result when discussing a requirement or review comment, so others can understand and check the issue.
Explain implementation choices
Compare approaches against project constraints, record the reasons and limitations, and revise decisions based on verification and feedback.
Define contributions clearly
Credit open-source projects, distinguish upstream capabilities from custom work, and explain where AI tools contributed.
Consider the user experience
Check readability, interactions, and error feedback across screen sizes, including keyboard navigation, to make features easier to use.