| A knowledge‐enhanced deep reinforcement learning‐based shape optimizer for aerodynamic mitigation of wind‐sensitive structures S Li, R Snaiki, T Wu Computer‐Aided Civil and Infrastructure Engineering 36 (6), 733-746, 2021 | 51 | 2021 |
| Knowledge-enhanced deep learning for simulation of tropical cyclone boundary-layer winds R Snaiki, T Wu Journal of Wind Engineering and Industrial Aerodynamics 194, 103983, 2019 | 44 | 2019 |
| A linear height-resolving wind field model for tropical cyclone boundary layer R Snaiki, T Wu Journal of Wind Engineering and Industrial Aerodynamics 171, 248-260, 2017 | 43 | 2017 |
| A semi-empirical model for mean wind velocity profile of landfalling hurricane boundary layers R Snaiki, T Wu Journal of Wind Engineering and Industrial Aerodynamics 180, 249-261, 2018 | 41 | 2018 |
| Modeling tropical cyclone boundary layer: Height-resolving pressure and wind fields R Snaiki, T Wu Journal of wind Engineering and Industrial aerodynamics 170, 18-27, 2017 | 36 | 2017 |
| Applications of machine learning to wind engineering T Wu, R Snaiki Frontiers in Built Environment 8, 811460, 2022 | 33 | 2022 |
| Revisiting hurricane track model for wind risk assessment R Snaiki, T Wu Structural Safety 87, 102003, 2020 | 30 | 2020 |
| Hurricane wind and storm surge effects on coastal bridges under a changing climate R Snaiki, T Wu, AS Whittaker, JF Atkinson Transportation research record 2674 (6), 23-32, 2020 | 30 | 2020 |
| Geospatial environments for hurricane risk assessment: applications to situational awareness and resilience planning in New Jersey T Kijewski-Correa, A Taflanidis, C Vardeman, J Sweet, J Zhang, R Snaiki, ... Frontiers in Built Environment 6, 549106, 2020 | 26 | 2020 |
| Active simulation of transient wind field in a multiple-fan wind tunnel via deep reinforcement learning S Li, R Snaiki, T Wu Journal of Engineering Mechanics 147 (9), 04021056, 2021 | 18 | 2021 |
| An analytical framework for rapid estimate of rain rate during tropical cyclones R Snaiki, T Wu Journal of Wind Engineering and Industrial Aerodynamics 174, 50-60, 2018 | 16 | 2018 |
| An analytical model for rapid estimation of hurricane supergradient winds R Snaiki, T Wu Journal of Wind Engineering and Industrial Aerodynamics 201, 104175, 2020 | 11 | 2020 |
| Hurricane hazard assessment along the United States northeastern coast: surface wind and rain fields under changing climate R Snaiki, T Wu Frontiers in Built Environment 6, 573054, 2020 | 10 | 2020 |
| A data-driven physics-informed stochastic framework for hurricane-induced risk estimation of transmission tower-line systems under a changing climate R Snaiki, SS Parida Engineering Structures 280, 115673, 2023 | 8 | 2023 |
| Knowledge-enhanced deep learning for simulation of extratropical cyclone wind risk R Snaiki, T Wu Atmosphere 13 (5), 757, 2022 | 6 | 2022 |
| Real-time repositioning of floating wind turbines using model predictive control for position and power regulation T Jard, R Snaiki Wind 3 (2), 131-150, 2023 | 5 | 2023 |
| Modeling rain-induced effects on boundary-layer wind field of tropical cyclones R Snaiki, T Wu Journal of Wind Engineering and Industrial Aerodynamics 194, 103986, 2019 | 4 | 2019 |
| An improved methodology for risk assessment of tropical cyclones under changing climate R Snaiki, T Wu Proc., 33rd AMS Conference on Hurricanes and Tropical Meteorology, Ponte …, 2018 | 4 | 2018 |
| Climate change effects on loss assessment and mitigation of residential buildings due to hurricane wind R Snaiki, SS Parida Journal of Building Engineering 69, 106256, 2023 | 3 | 2023 |
| Machine learning approximation for rapid prediction of high-dimensional storm surge and wave responses S Saviz Naeini, R Snaiki Canadian Society of Civil Engineering Annual Conference, 701-710, 2022 | 2 | 2022 |
Teng WuAssociate Professor, Civil, Structural and Environmental Engineering, University at BuffaloVerified email at buffalo.edu
