About / Chen Longgang

Break the problem down,
then ship it.

Software engineering master's degree, research in intelligent algorithms, computer vision and data mining. I have worked on data and modelling for a national research project, and on multimodal medical data, knowledge graphs, object detection, analytics and web systems.

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About

I hold a master's degree in software engineering, with research in intelligent algorithms, computer vision and data mining. I have worked on data collection, cleaning, modelling and experiments in research projects, and on object detection, knowledge graphs, analytics and web systems in engineering work.

I work in an engineering-minded way: clarify the problem and constraints first, build the smallest verifiable solution, then optimise. Beyond code, I care about documentation, reproducibility and delivery quality — the things that let someone else pick the work up.

I am currently doing independent work on AI data applications while building up embedded and Verilog skills. My goal is to connect algorithms, data and systems into products that are genuinely usable and maintainable.

This site is a sample of that approach: static-first, content and code in one repository, quality gates automated. It is both a portfolio and an engineering record that keeps being maintained.

Working principles

The habits behind the projects: validate early, document the decisions, keep the result reproducible.

Verify before optimising

Get the smallest closed loop working, validate it with real data or experiments, then invest in performance and architecture.

Documentation is part of delivery

Write down constraints, decisions and reproduction steps so the next person can take over, not just inherit code.

Reproducibility first

Pin dependencies, record environments and keep check scripts; conclusions should be runnable again.

Focus areas

Intelligent algorithms and data engineering
Static-first web systems
Embedded and hardware practice
Technical writing and knowledge sharing

Skills

Languages

Python
C / C++
Java
Shell
SQL
Assembly

Deep learning

PyTorch
TensorFlow
PaddlePaddle
Transformer / Llama
CUDA

Vision & detection

OpenCV
YOLO
Image preprocessing
Annotation & augmentation

Data & modelling

NumPy / Pandas
SPSS / Stata
Classification & clustering
Data cleaning

Systems & tools

Linux
Docker
Git
MySQL
TCP/IP

Hardware & edge

Verilog / SystemVerilog
FPGA flow
Microcontrollers
Edge inference

Education & experience

2025.07 – Present
Independent development
AI data applications
Building AI data applications: collection, cleaning, model training and deployment; continuing to study network engineering and embedded Verilog.
Work
2023.09 – 2024.05
Software, hardware and data analysis
Lanzhou Tianda Zhuoyue Information Technology
Maintained devices and systems, handled day-to-day hardware and software issues, and supported data analysis.
Work
2022.09 – 2025.07
M.Eng. in Software Engineering
Northwest Normal University
Research: intelligent algorithms, computer vision and data mining. Coursework in machine learning, AI and algorithm design.
Education
2016.09 – 2020.06
B.Eng. in Software Engineering
Zhengzhou University
Databases, algorithm design, computer networks, software architecture and software engineering practice.
Education
2024 – 2027
Poverty relapse monitoring and governance model
National Natural Science Foundation of China (72364033) · participant
Collected and cleaned social differentiation data; built classification, clustering and individual identification experiments.
Research

Contact

EmailGU-IDchen@outlook.com

LocationLanzhou, China