Welcome
Hello! I am a graduate researcher advised by Jeannette Bohg at IPRL Lab, affiliated with the Stanford Artificial Intelligence Laboratory (SAIL). I was also advised by Chelsea Finn at IRIS Lab.
My research interests span robotics, machine learning, and computer vision. I’m interested in enabling robots to learn generalizable representations from diverse data, and refine them through interaction for performing complex real-world tasks. I’m especially interested in:
- Representation learning from diverse data: Extracting useful interaction priors from diverse human and robot data.
- Learning through interaction: Enhancing precision, dexterity, and robustness via sample-efficient online interaction.
- Robust manipulation and control: Scaling dexterous manipulation to challenging dynamic settings.
- Human-robot collaboration: Enabling robots to autonomously complete tasks while adapting to human feedback on the fly.
If these topics also interest you, I would love to hear from you! Feel free to reach me at oliviayl [at] cs [dot] stanford [dot] edu.