| Partially nonergodic empirical ground‐motion models for predicting horizontal and vertical PGV, PGA, and 5% damped linear acceleration response spectra using data from the … F Sedaghati, S Pezeshk Bulletin of the Seismological Society of America 107 (2), 934-948, 2017 | 63 | 2017 |
| Estimation of the Coda‐Wave Attenuation and Geometrical Spreading in the New Madrid Seismic Zone F Sedaghati, S Pezeshk Bulletin of the Seismological Society of America 106 (4), 1482–1498, 2016 | 43 | 2016 |
| Site amplification within the Mississippi embayment of the central United States: Investigation of possible differences among various phases of seismic waves and presence of … F Sedaghati, S Pezeshk, N Nazemi Soil Dynamics and Earthquake Engineering 113, 534-544, 2018 | 26 | 2018 |
| An Analytical Effective Point‐Source‐Based Distance‐Conversion Approach to Mimic the Effects of Extended Faults on Seismic Hazard Assessment B Tavakoli, F Sedaghati, S Pezeshk Bulletin of the Seismological Society of America 108 (2), 742–760, 2018 | 19 | 2018 |
| Near-source attenuation of high-frequency body waves beneath the New Madrid Seismic Zone S Pezeshk, F Sedaghati, N Nazemi Journal of Seismology 22 (2), 455–470, 2018 | 15 | 2018 |
| Attenuation of Lg waves in the New Madrid seismic zone of the central United States using the coda normalization method N Nazemi, S Pezeshk, F Sedaghati Tectonophysics 712, 623–633, 2017 | 14 | 2017 |
| Comparative study on parameter estimation methods for attenuation relationships F Sedaghati, S Pezeshk Journal of Geophysics and Engineering 13 (6), 912–927, 2016 | 8 | 2016 |
| Investigation of Regional Differences in Strong Ground Motions for the Iranian Plateau F Sedaghati, S Pezeshk World Academy of Science, Engineering and Technology, International Journal …, 2016 | 6 | 2016 |
| Machine learning–based ground motion models for shallow crustal earthquakes in active tectonic regions F Sedaghati, S Pezeshk Earthquake Spectra 39 (4), 2406-2435, 2023 | 4 | 2023 |
| Investigation of coda and body wave attenuation functions in Central Asia F Sedaghati, N Nazemi, S Pezeshk, A Ansari, S Daneshvaran, M Zare Journal of Seismology 23 (5), 1047–1070, 2019 | 4 | 2019 |
| Simulation of strong ground motions using the stochastic summation of small to moderate earthquakes as Green's functions F Sedaghati The University of Memphis, 2018 | 4 | 2018 |
| A study of horizontal-to-vertical component spectral ratio as a proxy for site classification in central Asia F Sedaghati, S Rahpeyma, A Ansari, S Pezeshk, M Zare, S Daneshvaran Geophysical Journal International, 2020 | 3 | 2020 |
| Source-to-site distance conversion for extended faults F Sedaghati, S Pezeshk, B Tavakoli https://www.researchgate.net/publication/321300318_Source-to …, 2017 | 3 | 2017 |
| Ensemble Region-Specific GMMs for Subduction Earthquakes F Sedaghati, S Pezeshk Seismological Research Letters, 2024 | 2 | 2024 |
| Impacts on catastrophe risk assessments from multi-segment and multi-fault ruptures in the UCERF3 model Y Lee, Z Hui, S Daneshvaran, F Sedaghati, WP Graf Earthquake Spectra 38 (1), 128-151, 2022 | 2 | 2022 |
| A Generalization of the Stochastic Summation Scheme of Small Earthquakes to Simulate Strong Ground Motions F Sedaghati, B Tavakoli, S Pezeshk Pure and Applied Geophysics 177, 3713–3732, 2020 | 2 | 2020 |
| Developing Attenuation Relations by Use of Fuzzy Logic and Comparison to Current Relations for the Iranian Plateau F Sedaghati, A Ansari, J Farjoodi https://www.researchgate.net/publication …, 2009 | 2 | 2009 |
| Facial Recognition Adversarial Methods and Defenses F Sedaghati Georgia Institute Technology, 2022 | | 2022 |
| Chicken Audio Detection Using Neural Networks: Application of Autoencoder for Anomaly Detection and Multiclass Classification F Sedaghati Georgia Institute Technology, 2022 | | 2022 |
| Prediction of the Cryptocurrency Behavior Using Sentiment Analysis of Twitter and News Data F Sedaghati Georgia Institute Technology, 2022 | | 2022 |
Shahram PezeshkThe University of MemphisVerified email at memphis.edu
