Georgia Tech’s Jaden Wang (Zhuochen Wang) has been awarded a NASA Space Technology Graduate Research Opportunity (NSTGRO). The grant supports graduate students who “show significant potential to contribute to NASA’s goal of creating innovative new space technologies for our nation’s science, exploration, and economic future.”

Wang, who is a Ph.D. student in the School of Mathematics and a master’s student in the Daniel Guggenheim School of Aerospace Engineering, will focus on developing mathematically-backed landing solutions for spacecraft. 

“I first became interested in powered descent problems during my Fall 2024 internship with NASA’s Human Landing System at Marshall Space Flight Center,” he says. “With my mathematical background in optimization and topology, and my passion for space exploration, I saw this research topic as a perfect fit when my co-advisor Dr. Panagiotis Tsiotras suggested it.”

Wang is co-advised by School of Mathematics Professor and Hubbard Research Fellow John Etnyre alongside Panagiotis Tsiotras, who holds the David and Andrew Lewis Endowed Chair in the Daniel Guggenheim School of Aerospace Engineering and is also associate director at the Institute for Robotics and Intelligent Machines.

In addition to his Georgia Tech advisors, Wang will collaborate with a NASA Subject Matter Expert, who will connect him with the larger technical community. He will perform part of the research as a visiting technologist at multiple NASA centers, giving him the opportunity to work with leading engineers and scientists and share his research results directly with the NASA community.

From abstractions to space exploration

“NASA’s upcoming missions to the Moon, Mars, and beyond need technology that allows spacecraft to land precisely at their intended sites,” says Wang. “My research will focus on the last stage of landing, called powered descent. This stage powers up engines, which guide the spacecraft into a safe landing using a pre-designed trajectory that autopilot follows.”

This means that researchers need to figure out the correct thrust, direction, and timing to reach a landing spot — all while navigating a landing that uses as little fuel as possible.

“A common approach is to treat this as an optimization problem: minimizing fuel consumption with rigid-body physics as constraints to determine the best thrust profile,” Wang explains. “This can work well, but it has drawbacks. It assumes that there is no uncertainty in the system (for example, that the thrust of the engines is applied perfectly) and it simplifies the motion of the spacecraft by treating it as though it’s traveling through flat space instead of on a true curved geometry. Both shortcuts introduce errors  — our research aims to address these gaps.”

To improve landing precision, Wang will develop a curved-space geometric mathematical model, which takes into account the curved-space geometry of spacecraft motion rather than assuming flat space. To find a fuel-efficient landing trajectory, Wang will develop the model around optimal covariance steering, a stochastic control problem that both minimizes fuel costs while keeping the uncertainty of the spacecraft's exact landing spot within a safe amount.

It’s a problem that leverages his experience in theoretical math and his background in aerospace engineering. “I’m incredibly honored that NASA finds this research exciting and is supporting my pursuit of it,” he says. “There are so many fascinating engineering problems that could benefit from deeper theoretical scrutiny, especially using abstract machineries not typically covered in an engineering curriculum. I hope this inspires more theoretical researchers and graduate students to explore bridging these gaps.”