// PERSON
Yuhan Wang
ROLE LEAD AUTHORAT CORENETIC.AIMENTIONS 2LAST SEEN SEPTEMBER 7, 2026
// BIO
Yuhan Wang is a researcher affiliated with Shanghai Jiao Tong University and CoreNetic.ai, where he serves as lead author on work involving proprioception-anchored cross-modal pretraining for zero-shot sim-to-real transfer in contact-rich robotic assembly. He is best known for PACE, a cross-modal encoder that uses proprioceptive state-transition prediction to produce domain-invariant visual and force/torque representations, enabling policies trained in simulation to deploy on hardware without real-world fine-tuning or object-pose tracking.
Discussed in
// RECENT MENTIONS
// SIGNALS
2 SIGNALS
01
product·arXiv Physical AI·SEPTEMBER 7, 2026
“Policies trained on frozen PACE features are deployed on hardware without real-world fine-tuning or object-pose tracking”
Source→02
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