I began with
mathematics.
Then I learned to
question the answer.
As I moved into high school, that curiosity expanded toward data, artificial intelligence, electronic information and engineering.
As my interests expanded, I began applying the same habit of thinking to data, artificial intelligence and engineering.
The question was no longer only “Can I find the answer?” It gradually became “How was this answer produced?”
Curiosity changed shape as I grew.
Mathematics remained the foundation, but each stage introduced a new way of understanding problems.
Mathematics became my first way of understanding problems.
My interest in mathematics began early. During primary school, I received the Beijing Outstanding Student honor and earned first prizes in several mathematics competitions. At that time, I was fascinated by patterns, logic and the clarity of reaching a definite solution.
Solving harder problems required a more disciplined way of thinking.
At the First Mathematics Experimental Class of the High School Affiliated to Renmin University of China, I received systematic training in competition mathematics. The experience strengthened my logical reasoning, mathematical thinking and ability to analyze increasingly complex problems.
Mathematics opened the door to a much larger world.
Entering Yuanpei Academy marked an important shift. My interests gradually expanded from mathematics itself toward electronic information, artificial intelligence, data analysis and engineering practice. Mathematics remained the foundation, but increasingly became a tool for understanding broader scientific and technological problems.
I became more interested in testing conclusions than simply accepting them.
Through data analysis, artificial intelligence research and engineering practice, I began asking a different question: how do we know whether a result is actually trustworthy? This led me toward statistical modeling, AI behavior and intelligent systems.
Getting the answer right was no longer enough.
AI experiments showed me that a fluent answer does not necessarily represent stable judgment.
I became increasingly interested in the assumptions, mechanisms and evidence behind a conclusion.
Turning an idea into a working system.
Through the Underwater Biomimetic Robotic Fish
course jointly developed by
PKU High School and the College of Engineering
at Peking University,
I worked across software programming,
hardware design and engineering practice.
The course brought together
physics, biology, programming
and engineering,
allowing me to experience directly
how theoretical knowledge becomes
a functioning physical system.
PKU High School × Peking University
The questions I want to keep exploring.
Electronic Information & Artificial Intelligence
How intelligent systems process information, make judgments and respond to human interaction.
Computing & Data Science
How data and statistical models can be used to discover patterns, test assumptions and evaluate the reliability of conclusions.
Intelligent Systems & Robotics
How software, hardware, sensing and decision-making can work together inside intelligent physical systems.