Mechanical engineering Ph.D. student Md Badrul Hasan recognized for research modeling hurricanes with machine learning

Published: Jan 28, 2025

A woman presents a framed certificate to a man in a suit jacket.
Hasan receives the 2025 Professor Kirti “Karman” Ghia Memorial Award at the SciTech 2025 meeting on Jan. 10. (Photo by David Becker/AIAA)

Mechanical engineering Ph.D. student Md Badrul Hasan has received the 2025 Professor Kirti “Karman” Ghia Memorial Award from the American Institute of Aeronautics and Astronautics (AIAA), for his research modeling the fluid flow inside hurricanes with physics-informed machine learning. 

The award recognizes an international graduate student in the U.S. who has developed an innovative approach to computational fluid dynamics, in which computers are used to analyze and predict how fluids flow, with applications in aerospace engineering, weather forecasting, and more. Hasan, who is from Bangladesh, is the inaugural recipient of the award. His research explores new ways to improve the modeling of energy flow in hurricanes.

Machine learning for better weather forecasting

Hasan and his UMBC mentors—Meilin Yu, mechanical engineering, and Tim Oates, computer science and electrical engineering—looked at the layer of atmosphere in a hurricane that is directly above the ocean surface. Called the hurricane boundary layer, it is where turbulent flows bring heat and moisture from the water into the air, and it plays a crucial role in determining a hurricane’s intensity and track.

Traditional modeling of this layer fails to account for ways that energy within the smaller eddies in a flowing fluid can feed back into larger scale eddies. Hasan, Yu, and Oates explored how physics-informed machine learning models—which analyze large datasets to spot patterns—could better capture this phenomenon. Ultimately, they are looking to integrate their machine learning models into larger physics-based hurricane simulations to improve the simulations’ accuracy.

Satellite shows spinning hurricane off U.S. southeast coast.
Hurricane Humberto, as captured by a NOAA satellite Sept. 15, 2019. (Image credit: NOAA Satellites)

“This work sets up the cornerstone of our ongoing research towards more accurate numerical simulation of hurricane boundary layer flows at the scale of tens to hundreds of miles,” says Yu. “It is also a key step in our renewable energy research, where improving offshore wind farms’ resiliency to tropical storms is our ultimate goal as mechanical engineers. Badrul’s hard work pays off, and we are very proud of him.”

Hasan accepted the award for his work at the 2025 AIAA SciTech Forum, held in early January in Orlando, Florida, where he also presented his research. He says that while the community is filled with many researchers specializing in the traditional physics-based simulations, there is more and more interest in machine learning. 

Hasan says he is grateful for the guidance of Tim Oates, from the computer science and electrical engineering department, in selecting and understanding the machine learning models. 

“It was a great team effort between mechanical engineering and computer science—really productive and rewarding for both sides,” he says.

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