Biography

Howon Lee is a Ph.D. Student in the Guggenheim School of Aerospace Engineering at Georgia Tech. He received a B.S. degree in Mechanical Engineering from Brown University. His research interest currently is application of machine learning to aerodynamic experimental data.

In his free time, Howon enjoys gaming, swimming, and learning about languages.

Research

Howon researches artificial intelligence and machine learning (AI/ML) tools for the aeromechanics predictions of next-generation vertical lift aircraft. The goal of this two-year program is to use AI/ML tools to develop aeromechanics models of vertical lift aircraft, especially next-generation configurations featuring multiple electrically-driven rigid rotors. The models will be developed for: (1) estimation of rotor blade loads from measured blade deformation, and (2) real-time flight dynamics simulations. The research will be carried out in close collaboration between research groups at the University of Texas at Austin (UT) (PI: Prof. Jayant Sirohi) and Georgia Tech (GT) (PI: Prof. Juergen Rauleder).

Publications

Lee, H., Mortimer, P., Seshadri, P., Sirohi J., and Rauleder, J., “Machine Learning Based Approaches for Estimating Airloads in Hover”, 49th European Rotorcraft Forum Proceedings, Bückeburg, Germany, Sept 2023.

Lee, H., Simone, N., Su, Y., Zhu, Y., Ribeiro, B., Franck, J., and Breuer, K., “Leading edge vortex formation and wake trajectory: Synthesizing measurements, analysis, and machine learning“, Phys. Rev. Fluids 7, 074704

Lee, H., Ho, I., and Breuer, K, “Energy harvesting performance of an oscillating hydrofoil with a flexible tip.” AIAA SciTech Forum. 2022. DOI: 10.2514/6.2022-0732

Favorite Cereal

Cocoa Puffs