Welcome!

Hi, I’m Dzung Bui---a robotic PhD. candiate at George Mason University under supervision of Prof. Greg Stein and Prof. Erion Plaku . I am interested in motion planning and decision-making for multi-robot systems (MRS) in uncertain and unfamiliar environments under communication constraints.

My journey has always been shaped by a fascination with robotics and the ways machines can extend human potential. From my bachelor’s degree in mechanical engineering, where I learned how to design and build the physical structure of robots, to my master’s in mechatronics, where I explored control and embedded systems, each step has deepened my passion for creating intelligent machines. Now, as a Ph.D. candidate in computer science, I focus on giving robots the ability to think, adapt, and make decisions—even in uncertain and unfamiliar environments. I believe robots will play an increasingly important role in our society, from supporting humans in dangerous and high-risk jobs to improving lives in healthcare and beyond. My goal is to contribute to this future by developing technologies that push the boundaries of what robots can do. Driven by curiosity and a love for solving complex problems, I am excited to keep learning, innovating, and building toward a world where humans and robots work side by side to achieve more together.

News

- Nov. 2024: I successfully defended my dissertation proposal on "Multi-Robot Motion Planning under Uncertainty and Limited Communication".

- Jun. 2024: Our paper on "Learning-informed Long-Horizon Navigation under Uncertainty for Vehicles with Dynamics" is accepted at IROS 2024, Abu Dhabi, UAE link .

- Apr. 2024: Our paper “Multi-Robot Guided Sampling-Based Motion Planning with Dynamics in Partially Mapped Environments” is published at IEEEAccess 2024 link .

- Jun. 2023: Our paper “Guided Sampling-Based Motion Planning with Dynamics in Unknown Environments” is published at CASE 2023 link .

- Oct. 2022: Our paper “Improving the Efficiency of Sampling-Based Motion Planners via Runtime Predictions for Motion Planning Problems with Dynamics” is published at IROS 2022 link .