About

Tzu-Yuan Chen / 陳子元

Tzu-Yuan Chen

Tzu-Yuan Chen / 陳子元

Data Science & Applied Math — M.S. student at NCHU (Taiwan) & UTD (Dallas)

Focused on machine learning, deep learning, numerical analysis, and building data-driven solutions.

Email GitHub CV

About Me

I’m a graduate student from Taichung, Taiwan, pursuing dual master’s degrees in Data Science (NCHU) and Social Data Analytics & Research (UTD, Dallas), with a B.S. in Applied Mathematics from NCHU. I’m currently looking for a data science / ML internship.

Over the past few years I’ve completed 37 projects across a wide range of domains — from quantum computing and deep learning to medical image segmentation, database design, GIS, and AI agent workflows. I pick up new tools and fields quickly, and I enjoy going deep once I’m in. My current research focuses on flight delay prediction for a major U.S. airline, building selective prediction frameworks on 1.1M+ flight records. I’m also working with the Taichung Education Bureau, analyzing the relationship between an adaptive learning platform and student performance across 127 classes.

Outside of research, I worked as a cram-school math/physics/chemistry instructor for middle- and high-school students and at a 3D printing studio. I currently serve as a bilingual teaching assistant for Calculus, Database Systems, and Quantum Computing.

Research Interests

Machine Learning Deep Learning LLM / Prompt Engineering Image Classification & Segmentation Quantum Computing Flight Delay Prediction Numerical Analysis Big Data Analytics Education Data Analytics Database Design Data Visualization Selective Prediction

Skills

Programming

Python R SQL Qiskit Git

Python Libraries

pandas NumPy scikit-learn PyTorch Keras / TensorFlow GeoPandas Selenium BeautifulSoup PyQt6

R Ecosystem

ggplot2 tidyverse Shiny

ML / DL Models

ResNet EfficientNet U-Net GAN Autoencoder SVM KNN Random Forest MLP / DNN XGBoost Kernel Ridge

Techniques

Transfer Learning Focal Loss Image Segmentation Nyström Approximation Distributed Computing Selective Prediction Probability Calibration

LLM & AI

AI Agent Workflows Prompt Engineering RAG LLM API Integration

Tools

Matplotlib Altair ArcGIS Shapely Qt Designer Plotly Quarto LaTeX

Hardware & Platforms

IBM Quantum (IBMQ) Snowflake 3D Printing (FDM)

Site Guide

This portfolio documents my coursework, projects, and experiments across two graduate programs. Here’s what you’ll find:

📐

BS of Applied Math

Undergraduate thesis on Quantum Bayesian Inference using Qiskit & IBMQ hardware.

NCHU · 2020–2024
🧠

MS of DSIC — Overview

Research focus, skills developed, and course highlights for the Data Science program at NCHU.

NCHU · 2024–present
📊

ML & Data Science

Diabetes prediction (90.04%), wildfire analysis (1.88M records), cervical cancer classification.

NCHU · DSIC
🔬

Deep Learning

ResNet (96.44%), U-Net segmentation, Autoencoder, Conditional GAN for biomedical imaging.

NCHU · DSIC
⚡

Big Data Analysis

Nyström kernel approximation (20× speedup), distributed SVM (150× speedup).

NCHU · DSIC
🧮

Data Analysis Math

SVD image compression, Eckart-Young theorem, 8-model digit recognition comparison.

NCHU · DSIC
🌎

MS of SDAR — Overview

Social Data Analytics & Research program at UTD (dual-degree with NCHU).

UTD · 2025–present
🗺️

GIS & Python

GeoPandas mapping, PyQt6 GUI app, web scraping, ArcGIS spatial analysis.

UTD · SDAR
📈

Data Visualization

ggplot2, base R, Shiny dashboards, 6 chart types, Iris data visualization.

UTD · SDAR
🗄️

Information Management

Database design, SQL queries, wardrobe recommendation system (15 tables).

UTD · SDAR

Not all content represents final results. Some materials are exploratory or in progress.