Publications

Invariance-embedded machine learning sub-grid-scale stress models for mesoscale hurricane boundary layer flow simulation I: model development and a priori studies

Hasan, M. B., Yu, M., & Oates, T.

International Journal for Numerical Methods in Fluids

Accepted arXiv

Invariance-embedded machine learning sub-grid-scale stress models for mesoscale hurricane boundary layer flow simulation: a posteriori integration and evaluation

Hasan, M. B., Yu, M., & Oates, T.

Journal article

In preparation

Detecting stealthy cyber attacks on wind energy assets with ODE physics-informed learning and adversarial hardening

Hasan, M. B., Kalwani, S., Chen, Z., & Yu, M.

Journal article

In preparation

The effects of numerical dissipation on hurricane rapid intensification with observational heating

Hasan, M. B., Guimond, S. R., Yu, M., Reddy, S., & Giraldo, F. X.

Journal of Advances in Modeling Earth Systems, 14, e2021MS002897

DOI

Semi-a priori evaluation of backscatter-admitting machine learning sub-grid scale models in WRF hurricane simulations

Hasan, M. B., Yu, M., & Oates, T.

AIAA Aviation 2026 Forum, AIAA 2026-4769. Presented in San Diego, CA.

DOI

A baseline a posteriori evaluation of machine-learning-predicted eddy viscosity fields in mesoscale hurricane boundary layer simulations

Hasan, M. B., Yu, M., & Oates, T.

ASME 2026 Fluids Engineering Division Summer Meeting. Presented in Bellevue, WA.

Physics-informed machine learning for detecting stealthy long-term cyber attacks on wind energy systems

Kalwani, S., Hasan, M. B., Chen, Z., & Yu, M.

2025 IEEE International Conference on Big Data, Macau, China, pp. 6587–6596

DOI

Evaluating machine learning-enhanced sub-grid scale stress models with invariance embedding for mesoscale hurricane boundary layer flows

Hasan, M. B., Yu, M., & Oates, T.

Proceedings of the ASME 2025 Fluids Engineering Division Summer Meeting, V001T01A001. Presented in Philadelphia, PA.

DOI

Comparison of several machine-learning-enhanced sub-grid scale stress models for mesoscale hurricane boundary layer flow simulation

Hasan, M. B., Yu, M., & Oates, T.

AIAA SciTech 2025 Forum, p. 2212. Presented in Orlando, FL.

Best student paper, AIAA FDTC DOI

Sub-grid scale modeling of mesoscale hurricane boundary layer flows using machine learning

Hasan, M. B., Yu, M., & Xiao, H.

AIAA SciTech 2023 Forum, p. 2487. Presented in National Harbor, MD.

DOI

Machine learning-enhanced turbulence modeling for hurricane boundary layer simulations

Hasan, M. B.

COEIT Research Day, UMBC, Baltimore, MD

Poster Doctoral Student Award

Data-driven modeling of dynamic stall in vertical-axis wind turbines

Schroeder, R., Hasan, M. B., & Yu, M.

COEIT Research Day, UMBC, Baltimore, MD

Poster Undergraduate Student Award

Physics-informed machine learning for turbulence, hurricanes, and wind-energy cybersecurity

Hasan, M. B.

Mechanical Engineering Graduate Seminar, UMBC

Oral

Invariance-embedded machine learning sub-grid-scale stress models for mesoscale hurricane boundary layer simulations

Hasan, M. B.

Research Symposium on Environmental and Applied Fluid Dynamics, The George Washington University, Washington, DC

Oral

Stealthy long-term cyber attacks detection on wind turbines using physics-informed neural networks

Kalwani, S., Hasan, M. B., Chen, Z., & Yu, M.

COEIT Research Day, UMBC, Baltimore, MD

Poster Honorable Mention, Master's Student Award

Assessment of invariance-embedded machine learning models for sub-grid scale stress in mesoscale hurricane boundary layer flows

Hasan, M. B.

COEIT Research Day, UMBC, Baltimore, MD

Oral

Sub-grid scale modeling of mesoscale hurricane boundary layer flows using machine learning

Hasan, M. B.

COEIT Research Day, UMBC, Baltimore, MD

Oral

The effects of numerical dissipation on hurricane rapid intensification with observational heating

Hasan, M. B.

AGU Fall Meeting, New Orleans, LA

Poster

The effects of numerical dissipation on simulating hurricane intensification in a realistic regime

Hasan, M. B.

AGU Fall Meeting, San Francisco, CA

Poster

The effects of numerical dissipation on simulating hurricane intensification in a realistic regime

Hasan, M. B.

Seminar Series, Department of Mechanical Engineering, UMBC, Baltimore, MD

Oral