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I am a research science manager at Amazon. My research interests are in the areas of control, optimization, and data-based algorithms.

Before joining Amazon, I was a postdoctoral scholar at Caltech, working with Prof. Aaron Ames and Prof. Yisong Yue. My research focused on high-level planning in partially observable environments and on designing control algorithms that allow autonomous systems to perform highly dynamical maneuvers while guaranteeing safety. {: style="text-align: justify"}

During my PhD at the University of California Berkeley, I worked with Prof. Francesco Borrelli in the MPC lab. I developed the Learning Model Predictive Control (LMPC) strategy, which is a model-based policy iteration strategy. This strategy was used to teach an autonomous vehicle how to race!
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A talk on my PhD and postdoc research

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Learning How to Race Experiments
Listen with audio to hear the tires squealing!

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Planning and Control in Partially Observable Environments
The locations of the blue boxes are unknown to the robot

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