MINH.LY
Backend · Automation · Database Systems · AI Integration

MINH.
LY

I build practical software systems that combine backend development, databases, automation, and AI integration to solve real-world problems. From APIs and workflow automation to relational databases and AI-assisted applications, I enjoy turning ideas into functional software.

scroll
[ 01 ]

Who is typing

// operator
To Minh Ly at the desk — wand in hand, Python in the air, mushrooms in bloom
Ship it ✦

Hi, I’m To Minh Ly (蘇明李), a fourth-year Information Engineering student at Yuan Ze University. I am interested in backend development, automation, relational databases, AI integration, and smart manufacturing.

I enjoy building practical systems that connect APIs, databases, document-processing tools, and local or cloud-based AI models. My projects include an AI learning platform, a LINE chatbot, database-driven workflows, and Python automation utilities.

Backend

FastAPI, Flask, REST APIs, SQLAlchemy, authentication, and application workflows.

Data & Automation

MySQL, database design, stored procedures, triggers, file automation, and document processing.

AI Integration

Local LLMs, LM Studio, OpenAI-compatible APIs, OCR, and AI-assisted applications.

[ 02 ]

Tools & weapons

Python C++ SQL JavaScript FastAPI Flask REST API SQLAlchemy MySQL Docker Git GitHub Actions Postman LM Studio Local LLMs Document Processing Workflow Automation
[ 03 ]

Selected work

AI Course Assistant

Flagship

A local, AI-powered learning platform. Admins create courses and upload documents; students chat with a course-aware assistant, auto-generate summaries and quizzes, reveal answers, export to PDF and review history — all running offline through a local LLM (LM Studio). No data leaves the machine.

  • Course-aware chat over uploaded docs — chunk retrieval → local model as context
  • Multilingual document summaries: English · Vietnamese · 繁體中文
  • Auto quiz generator with click-to-reveal answers + DB caching by doc/lang/count
  • PDF export, chat history in Taiwan time, MathJax formula rendering
  • Admin dashboard with live course / document / quiz statistics
PythonFastAPISQLAlchemyMySQL DockerLM Studio · local LLMJinja2MathJax
View repo Local build · FastAPI · Docker · LM Studio

LINE OpenAI Chatbot

Public

A context-aware LINE chatbot using Flask, the LINE Messaging API, OpenAI integration, per-user conversation history, RESTful history endpoints, and Cloudflare Tunnel for webhook testing.

Python Flask LINE API OpenAI API REST
View repo 01

CSV Database & Query Engine

C++ · CS351

A lightweight CSV-backed mini-database: parses files into memory and runs SQL-like queries — SELECT columns with WHERE filters — from a console REPL. Simulates how a DBMS works internally, with no external engine.

C++ParsingQuery EngineIn-memory DB
View repo 02

Two Sum — Algorithms

C++ · CS351

The classic Two Sum done properly: an O(n) hash-map solution backed by a 20-case test suite (negatives, zeros, duplicates, huge ints), a CMake build and GitHub Actions CI across Linux, macOS and Windows.

C++AlgorithmsCMakeCI/CDUnit tests
View repo 03

IMDb Sentiment Baseline

Public

An ML baseline for IMDb sentiment classification using BoW / TF-IDF and Logistic Regression — training, model saving, evaluation metrics included.

PythonMLscikit-learnNLP
View repo 04

Hotel Management DB

Public

A MySQL database for hotel ops — booking, payment, cleaning, maintenance. Schema design, triggers, procedures, views and demo scripts.

MySQLSchemaProceduresTriggers
View repo 05

Smart File Organizer

Public

A Python tool that classifies and moves files automatically by type or rule — local file management that stops being a mess.

PythonAutomationFile System
View repo 06

CS351 Course Repo

Coursework

The home base for CS351 — assignments, project docs, file organisation and a GitHub-based workflow, linking out to Project 0 and Project B.

CourseworkGitHubDocsC++ · Python
View repo 07
[ 04 ]

How I build

Understand the problem

Identify the user need, expected inputs, outputs, and technical constraints.

Design the workflow

Plan the application flow, data model, API structure, and system components.

Build incrementally

Implement features in manageable steps and keep changes organized with Git.

Test the behavior

Use manual tests, API tools, demo scripts, and automated checks where appropriate.

Document the project

Write setup instructions, architecture notes, limitations, and clear project examples.

Review and improve

Evaluate results, identify limitations, and plan practical future improvements.

[ 05 ]

Education

Yuan Ze University

Bachelor · Department of Computer Science and Engineering (CSE) · Fourth-year student

Department rank: Top 6% — 9 / 150
Best semester average: 97 / 100

Bach Khoa Aptech

College · Computer Science
Languages
Vietnamese Native
Traditional Chinese Intermediate
English Working Proficiency
[ 06 ]

Say hello

GitHubgithub.com/WaterMinh LinkedInin/to-minh-ly PortfolioWaterMinh.github.io