Yincheng Zhou
Computer Science & Physics at the University of Pennsylvania.
I came to programming through physics olympiads in China. Five hours, a blank page, a magnet falling through a copper tube. The kind of problem that punishes equation-reaching and rewards sitting with the system long enough to see what it wants to do: what's conserved, what's resisting, where the energy goes. The math comes after the picture, not before it.
That kind of intuition turns out to be most of what I value about software. The systems I find interesting reward the same habit: depth estimators running at the edge of GPU throughput, training pipelines that scale by factors instead of percentages, hot paths measured in microseconds. The questions trade places, but the move underneath stays the same. Get the model right before the code goes wrong.
These days that means sparse depth estimation at the GRASP Lab and GUI agent training at Peking University's HMI Lab.
research
- 2026
writing
- 2026·07 On the price of a static shape
- 2026·07 On the desktop that kept waiting for a human
- 2026·07 Why we searched the desktop instead of rewarding the agent
- 2026·06 Why KV cache reuse is harder for vision than for language
- 2026·06 On knowing what changed in a vision pipeline
- 2026·06 On Olympiad physics and engineering intuition