Investigating an Optimal Computational Strategy to Retrofit Buildings with Implementing Viscous Dampers. - Farzin Kazemi; Neda Asgarkhani; Ahmed Manguri; Robert Jankowski (ICCS (1), 2022)

Introducing a Computational Method to Retrofit Damaged Buildings under Seismic Mainshock-Aftershock Sequence. - Farzin Kazemi; Neda Asgarkhani; Ahmed Manguri; Natalia Lasowicz; Robert Jankowski (ICCS (2), 2023)

Machine learning-based prediction of preplaced aggregate concrete characteristics. - Farzam Omidi Moaf; Farzin Kazemi; Hakim S. Abdelgader; Marzena Kurpinska (Eng. Appl. Artif. Intell., 2023)

Active Learning on Ensemble Machine-Learning Model to Retrofit Buildings Under Seismic Mainshock-Aftershock Sequence. - Neda Asgarkhani; Farzin Kazemi; Robert Jankowski (ICCS (3), 2024)

Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods. - Neda Asgarkhani; Farzin Kazemi; Anna Jakubczyk-Galczynska; B. Mohebi; Robert Jankowski (Eng. Appl. Artif. Intell., 2024)

Machine-learning methods for estimating compressive strength of high-performance alkali-activated concrete. - Torkan Shafighfard; Farzin Kazemi; Neda Asgarkhani; Dooyeol Yoo (Eng. Appl. Artif. Intell., 2024)

Optimization-based stacked machine-learning method for seismic probability and risk assessment of reinforced concrete shear walls. - Farzin Kazemi; Neda Asgarkhani; Robert Jankowski (Expert Syst. Appl., 2024)

Chained machine learning model for predicting load capacity and ductility of steel fiber-reinforced concrete beams. - Torkan Shafighfard; Farzin Kazemi; Faramarz Bagherzadeh; Magdalena Mieloszyk; Dooyeol Yoo (Comput. Aided Civ. Infrastructure Eng., 2024)

Ensemble machine learning models for estimating mechanical curves of concrete-timber-filled steel tubes. - Farzin Kazemi; Neda Asgarkhani; T. Ghanbari-Ghazijahani; Robert Jankowski (Eng. Appl. Artif. Intell., 2025)