Ran (Thomas) Tian

Robotics × AI  ·  UC Berkeley BAIR  ·  NVIDIA Research  ·  Waymo

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Ran (Thomas) Tian, PhD candidate in robotics at UC Berkeley

About

I am currently a research scientist at NVIDIA Research, working on embodied reasoning and world foundation models with a focus on large-scale RL post-training. I got my PhD from UC Berkeley. I was advised by Prof. Masayoshi Tomizuka and Prof. Andrea Bajcsy at Carnegie Mellon University.

My research lies at the intersection of robotics and AI, with a focus on safe alignment between embodied agents and humans. I tackle the alignment and safety problems that emerge throughout the life-cycle of foundation models in robotics: from training (collecting and quantifying what kinds of embodied data will enable the desired robotics capabilities), to fine-tuning (aligning these models with humans), to deployment (where these models must run in real-time, reliably detect out-of-distribution scenarios, and confidently hand over control to fallback strategies). I ground my work through a variety of applications — from autonomous cars, to personalized robots, to generative AI — and in experiments with real human participants.

During my PhD, I also spent a significant amount of time at Waymo, scaling my research outcomes in driving foundation models, including pre-training, post-training preference alignment, and distillation for onboard deployment. I am fortunate to work at NVIDIA Research, focusing on vision-language-action models for autonomous driving. Previously, I was a research intern at WeRide, Honda Research Institute, and Qualcomm AI Research.

News

Honors & Awards

Selected Publications

For the most up-to-date list, please see my Google Scholar.