Welcome
Hello! I am a Master’s student at Stanford University. I completed my B.S. with Honors in Symbolic Systems and a minor in Mathematics, and am currently pursuing a coterminal M.S. in Computer Science. I conduct research with Stanford’s IPRL Lab, affiliated with the Stanford Artificial Intelligence Laboratory (SAIL), which seeks to understand the underlying principles of robust sensorimotor coordination by implementing them on robots. I am fortunate to be mentored by Jeannette Bohg, and previously by Chelsea Finn, Suraj Nair, and Annie Xie of Stanford’s IRIS Lab.
My research interests span robotics, machine learning, and computer vision. I’m interested in enabling robots to learn generalizable representations from diverse datasets, and refine them through interaction for performing complex tasks in the real world. I’m especially interested in:
- Learning from human data: Enabling robots to leverage skill and object representations learned from human data for downstream tasks.
- Long-horizon planning and reasoning: Improving long-horizon task completion by processing multimodal inputs and environmental feedback.
- Representation learning: Developing robust action and state representations for planning, goal specification, and closed-loop task execution.
If any of the above sounds interesting to you, I would love to hear from you! Feel free to reach me at oliviayl [at] stanford [dot] edu.