Yuer Tang

"It started with a simple question: what is the model inside our minds?"

Hi! My name is Yuer Tang and I recently graduated from UCLA, and am an incoming master's student in Electrical Engineering at Stanford University. I am fortunate to be starting a project at the Stanford Vision and Learning Lab (SVL) with Jiajun Wu, Jieneng Chen, and Yining Hong.

During my undergrad, I was fortunate to be advised by Ying Nian Wu at the UCLA Statistics Department, Jiayuan Mao at MIT CSAIL, and Justin Baker at the UCLA Mathematics Department. Outside of this, I enjoy hiking 🥾, sailing ⛵, tennis 🎾, and writing ✍️.

Research Highlights

I believe that for a machine to perceive, reason, and act in the world, it needs an internal model, one built from multimodal experience, not language alone. Such a model should live in a latent space where different modalities meet: vision, touch, proprioception, language. The key question is abstraction. A robot pouring water and a robot planning a meal need the same world, represented at very different levels of detail. I study how to structure these latent spaces so that the right abstraction emerges for the right task. I draw on ideas from cognitive science, neuroscience, and mathematics. In my current work, I explore this through structured latent representations for robotic manipulation, meta-adaptive planning, and mathematically grounded neural architectures.