Rachel Luo  

 



  ![](/sites/default/files/person/RachelLuo_headshot_square_cropped_0.jpg)

  

 Rachel Luo is a Research Scientist in the Autonomous Vehicles Group at NVIDIA Research. She works on improving the safety and reliability of autonomous systems. Her research interests lie at the intersection of machine learning, computer vision, and robotics, and include topics in uncertainty quantification, distribution shift, and foundation models. Prior to joining Nvidia, Rachel completed her PhD and MS in Electrical Engineering at Stanford University, and her BS in Electrical Engineering and Computer Science at MIT.



   Research Area(s)

[Artificial Intelligence and Machine Learning ](/research-area/machine-learning-artificial-intelligence)

[Autonomous Vehicles](/research-area/autonomous-vehicles)

[Resilience and Safety](/research-area/resilience)

[Robotics](/research-area/robotics)

 

 

  

 Main Field of Interest

[Autonomous Vehicles](/research-area/autonomous-vehicles)

 

  

 Google Scholar

[https://scholar.google.com/citations?user=9TPpYBMAAAAJ&hl=en&oi=ao](https://scholar.google.com/citations?user=9TPpYBMAAAAJ&hl=en&oi=ao)

 

  

 

 

 



 ### Publications

 

### 2025 

[Sim2Val: Leveraging Correlation Across Test Platforms for Variance-Reduced Metric Estimation](/publication/2025-09_sim2val-leveraging-correlation-across-test-platforms-variance-reduced-metric)

[Rachel Luo](/person/rachel-luo), [Heng Yang](/person/heng-yang), [Michael Watson](/person/michael-watson), [Apoorva Sharma](/person/apoorva-sharma), [Sushant Veer](/person/sushant-veer), Edward Schmerling, [Marco Pavone](/person/marco-pavone)