There is a huge difference between knowing something and just knowing the name of something.

-- Richard Feynman

Much like a fine meal, becoming a “professionally sound” researcher requires time and rigorous training. It is a necessary seasoning, though never sufficient on its own. The path is rarely as linear as a PhD degree or a list of publications might suggest; the true challenge lies in navigating the pitfalls of the academic landscape.

I strive to avoid the trap of the “expert beginner” (here)—the illusion of mastery that halts growth and obscures the broader scientific picture. Similarly, I prioritize depth over the “sandwich paper” (here) culture often found in engineering and machine learning. In my view, research should be driven by curiosity and impact, not just the accumulation of volume.

I am deeply grateful to the mentors who shaped not only my technical skills but my character as a human being.

• Mr. Zheng Benfa (High School Chemistry): Mr. Zheng planted the “chemistry seed” in my heart. His classes were a blend of excitement and life philosophy; he once explained the competition for electrons in ionic bonds by noting, “Something you get very easily can also be lost very easily.” He taught me that science and life share the same DNA.

• Mr. Yang Hanwen (College Mechanics): Watching Mr. Yang solve complex problems on a blackboard—entirely from memory and with infectious enthusiasm—was a masterclass in rigor and beauty. He didn’t just teach mechanics; he modeled what it looks like to be truly fluent in one’s field.

• Dr. Michael Hillman (Master’s Supervisor): Under Dr. Hillman’s guidance in computational modeling, I learned the art of critical thinking. He taught me to obsess over details, define problems with precision, and distinguish between “doing research” and “doing research well.”

• Dr. Elena Dormidontova (PhD Supervisor): Dr. Dormidontova’s mantra, “We are creating knowledge, not papers,” remains my North Star. She taught me how to balance granular detail with the “big picture,” helping me develop my expertise in the statistical modeling of polymer nanostructures.