University of California, Riverside
Focused on embedded systems, machine learning, robotics, and systems-oriented engineering work across Python, C/C++, Linux, computer vision, and hardware integration.
Tae Jong Kang
Electrical engineering student at UC Riverside
I'm Tae Jong Kang, an electrical engineering student focused on turning technical ideas into working products. My projects span machine learning, data pipelines, embedded systems, robotics, and computer vision.
Projects
View AllTennis Match Prediction
End-to-end machine learning workflow for tennis match prediction, calibration, and fast model review in a lightweight web UI.
Computer Vision Coffee Sorting
Raspberry Pi and OpenCV system for visual sorting, sensor feedback, and real-time hardware control.
CUDA Mixture of Experts
GPU-accelerated tennis Monte Carlo simulator using CUDA C++, Mixture of Experts routing, softmax expert blending, and CPU vs GPU benchmark comparison.
Professional Experience
View AllIndependent Technical Projects
Designed complete workflows from data ingestion and modeling through interface design and deployment structure.
Research & Publications
View AllServe-based tennis modeling paper using Wsp, dynamic Monte Carlo simulation, synthetic training data, and machine-learning regression to estimate total games, win probability, and over/under outcomes.
Ethical, food-safety, cybersecurity, economic, environmental, and societal impacts of a low-cost optical coffee bean sorter with robotic arm.
How rapid prototyping with PLA/FDM helped build the sorter, and why commercial food-contact designs require safer materials and manufacturing methods.