Yuke Zhu
Leading academic researcher in robot learning; co-director of Robot Perception and Learning lab at UT Austin and affiliated with NVIDIA; senior author on GRAIL.
“Yuke Zhu, UT Austin / NVIDIA. Prolific researcher in robot learning, co-author of LIBERO benchmark”
Source→“Linxi 'Jim' Fan, Dieter Fox, Jan Kautz, Yuke Zhu: NVIDIA. Key researchers behind the GR00T N1.5 VLA model”
Source→“Co-director of the Good Systems Lab at UT Austin, a leading researcher in robot manipulation and learning. Co-advised this work and is a core member of the GR00T team”
Source→“Listed as a co-author from UT Austin and an equal advisor for the paper.”
Source→“Yuke Zhu: NVIDIA. Notable for his extensive work in robotic manipulation, large-scale robot learning, and simulation environments. Co-advisor on the paper.”
Source→“We reproduce this baseline using the GR00T N1.7 implementation and initialize from the pretrained nvidia/GR00T-N1.7-3B checkpoint (Appendix E). NVIDIA's GR00T N1.7 achieves 35% average success as EgoScale — the strongest baseline, but 30 points behind T-Rex.”
Source→“Dream Dojo is a relatively universal world model pretrain. We open-source it so that anyone with a new robot can quickly connect to our world model, fine-tune it, and use it.”
Source→“Jim Fan and Yuke Zhu's research taste and style matched mine quite well. At the time I also really wanted to collaborate with them.”
Source→AI-extracted from podcast / newsletter / paper summaries. May contain errors.