About
A personal growth dossier, not just a resume.
This page frames my academic direction, current focus, and working principles for long-term technical growth.
Profile
I am studying Intelligent Science and Technology and gradually building a foundation for algorithms, AI systems, computer vision, deep learning, and research engineering. This homepage is designed to collect learning paths, project records, paper reading, experiment logs, and reflective writing in one coherent place.
Academic Direction
Current Focus
The current stage is about building reliable foundations.
重点不是把每个方向都写得很满，而是把正在学、正在做、准备复现和需要补齐的部分记录清楚。
Systematic data structures and algorithms practice
Computer networks and CS foundations
Deep learning fundamentals
CNN / Transformer study and reproduction
Research paper reading and implementation notes
Lab project progress tracking
Long-term blog and project documentation
Values
Working principles for research and engineering.
These principles are practical reminders for studying, building, documenting, and reviewing work.
Long-termism
Prefer compounding notes, reproducible work, and stable habits over short bursts of output.
Clarity
Write down assumptions, goals, blockers, and next steps so projects remain understandable.
Technical depth
Move from vocabulary to implementation, then from implementation to experiment and explanation.
Continuous learning
Treat coursework, algorithms, papers, and engineering practice as connected tracks.
Research discipline
Record evidence carefully and avoid overstating results before experiments support them.
Engineering reliability
Keep code runnable, documented, and easier to revisit after time passes.