I'm a Software Engineering student at Northwestern Polytechnical University (NPU).
My current interests span several areas of software and intelligent systems:
- 🤖 AI Software Engineering & Agent Systems
- ⚙️ C, Linux & Systems Programming
- 🦾 Robotics
- 🚀 Huawei Ascend / CANN & AI Computing
I enjoy exploring software from both high-level engineering systems and low-level implementation details — from multi-agent software workflows to robotics, systems programming, and AI accelerator development.
A long-term software engineering framework exploring how AI agents can collaborate in real development workflows.
Current topics include:
- Multi-agent orchestration
- Specialist agent delegation
- Checkpoint / resume
- Persistent engineering state
- Quality gates
- Hooks and deterministic constraints
- Requirements → Architecture → Implementation → Testing → Review
My goal is to explore how AI-assisted development can become more structured, reliable, testable, and recoverable.
A long-term collection of runnable examples and technical notes on C, Linux, and systems programming.
Topics include:
- C language mechanisms
- Linux system programming
- Memory management
- File I/O
- Data structures
- Reference counting
- Abstraction patterns
- Low-level implementation details
I prefer learning through:
concept → implementation → experiment → debugging → explanation
I'm also studying and building robotics systems, with particular interest in:
- Robot localization
- Visual perception
- Multi-camera vision
- Obstacle avoidance
- Odometry
- ROS 2
- Sensor fusion
- Real-time robot software
I'm especially interested in combining perception, localization, and control into reliable robotic systems rather than treating them as isolated modules.
I'm currently learning the Huawei Ascend AI computing ecosystem, especially:
- CANN
- Ascend C
- Custom operator development
- Host / Device execution models
- AI Core programming
- Tensor memory management
- Queue and pipeline mechanisms
- Operator performance analysis
msprof- Heterogeneous computing
My goal is to understand how AI operators are implemented and optimized closer to the hardware level, rather than only using high-level deep learning frameworks.
- AI Software Engineering
- Agent Systems
- Multi-Agent Collaboration
- Software Architecture
- Testing & Code Review
- Developer Tooling
- C / C++
- Linux
- Systems Programming
- Memory Management
- Computer Architecture
- Programming Language Internals
- Computer Vision
- Localization
- Navigation
- ROS 2
- Embedded Robotics
- Huawei Ascend
- CANN
- Ascend C
- AI Accelerators
- Operator Development
- Performance Optimization
C · C++ · Python · Java · Rust
Linux · Git · ROS 2 · Claude Code · CANN · Ascend C
I'm currently exploring software engineering across multiple abstraction levels:
Higher-level engineering
AI agents, software architecture, automation, testing, and reliable development workflows.
Intelligent systems
Robotics, perception, localization, and autonomous systems.
Lower-level systems
C, Linux, memory, runtime behavior, and systems programming.
AI computing infrastructure
CANN, Ascend C, custom operators, and accelerator-oriented optimization.
I want to understand not only how to build intelligent software, but also how the systems underneath it actually work.
From AI agents to robots, from C to AI accelerators.