Teaya Yang

I am a PhD student majoring in Controls at UC Berkeley, advised by Prof. Mark W. Mueller. I am a member of the High Performance Robotics (HiPeR) Lab and affiliated with the Berkeley Artificial Intelligence Research (BAIR) Lab.

I received my B.S. degree in Mechanical Engineering from Cornell University in 2022, where I conducted undergraduate research under the supervision of Prof. Itai Cohen.

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Research

My research focuses on perception-driven autonomy for uncrewed aerial vehicles (UAVs), with the goal of enabling reliable operation at scale in complex, GPS-denied environments. At the intersection of perception, state estimation, and motion planning, I develop advanced methods that allow UAVs to reason about their environment using onboard sensing. My current work develops information-theoretic methods for perception-aware, multi-agent UAV navigation.

I'm always happy to connect and collaborate. If you're interested in my work, feel free to reach out!

A multi-UAV trajectory planning framework that incorporates vision-based estimator uncertainty through shared feature alignment and perception-aware rewards.

An autonomous system for fruit counting through RGB images with a focus on through-the-canopy data collection.

A simulator for UAV navigation in agricultural environments with built-in support for visual-inertial odometry.

A collision-aware path recovery method for high-speed tensegrity drones using binary contact sensing and vector-field-based navigation.

A simulator for UAVs with a focus on agricultural applications.

A novel design paradigm for multistate machines where state transitions are organized by bifurcations of equilibria.

This website is adapted from Jon Barron. Last updated: Jan, 2026