Christopher Ta

Machine learning and software engineer with experience building predictive models, data pipelines, and structured software systems. IEEE-published researcher with hands-on experience applying machine learning to real-world datasets, designing maintainable software architectures, and delivering technical instruction.

Experience

Cal State University Fullerton, Fullerton, CA — Associate Instructor

January 2022 – May 2022

Instructed the Compilers and Languages course to 28 students as a lecturer/professor, accommodating all students in a hybrid setting.

Conference Paper Publication, Fullerton, CA — Data Scientist / Author

March 2023 - June 2023

Authored Exploring Machine Learning Techniques for Fall Risk Prediction using the Berg Balance Scale, focusing on the clinical assessment test, the Berg Balance Scale (BBS). Employed various machine learning models to determine the feasibility of BBS subsets in real-world scenarios.

Software Design, Fullerton, CA — Student Software Engineer

August 2020 - December 2020

Co-developed Money Trail CRM—a console-based client relationship management system in C++, following the model-view-controller design pattern. Developed over five months using the agile unified process.

Education

Cal State University Fullerton, Fullerton, CA — Master of Science in Computer Science

August 2018 - January 2023

Graduate Academic Honor, Degree Verification Link

University of California Riverside, Riverside, CA — Bachelor of Science in Biology

September 2010 - June 2014

Technical Skills

Tools

Visual Studio, Eclipse, Android Studio, Terminal, Git, Microsoft Office, Photoshop, Linux, Windows, Anaconda, Jupyter Notebook, Selenium WebDriver, Docker, Tailscale.

Languages

C++, C, C#, Java, Python, HTML, CSS, JavaScript, Dart, x86 Assembly, LaTeX, GLSL, Bash.

Frameworks

Android, Flutter, Bootstrap.

Soft Skills

Problem Solving, Cross-Functional Team, Adaptability, Flexibility, Time Management, Communication, Leadership

Work Authorization

U.S. Citizen

Certificates

C++, Tensorflow, Keras, Pandas, NumPy