| Artificial intelligence, machine learning, and deep learning in structural engineering: a scientometrics review of trends and best practices ATG Tapeh, MZ Naser Archives of Computational Methods in Engineering 30 (1), 115-159, 2023 | 152 | 2023 |
| Discovering graphical heuristics on fire-induced spalling of concrete through explainable artificial intelligence ATG Tapeh, MZ Naser Fire Technology 58 (5), 2871-2898, 2022 | 13 | 2022 |
| Causality, causal discovery, causal inference and counterfactuals in Civil Engineering: Causal machine learning and case studies for knowledge discovery MZ Naser, ATG Tapeh COMPUTERS AND CONCRETE 31 (4), 277-292, 2023 | 10 | 2023 |
| A NOMOGRAM FOR PREDICTING FIRE-INDUCED SPALLING ATG Tapeh, MK al-Bashiti, A Ghasemi, H Hostetter, D Craig, MZ Naser66 | 3 | 2022 |
| A Review of 315 Benchmark and Test Functions for Machine Learning Optimization Algorithms and Metaheuristics with Mathematical and Visual Descriptions MZ Naser, MK al-Bashiti, ATG Tapeh, AD Eslamlou, A Naser, V Kodur, ... arXiv preprint arXiv:2406.09581, 2024 | 1 | 2024 |
| ON THE PREMISE OF A NEW THEORY FOR FIRE-INDUCED SPALLING OF CONCRETE THROUGH EXPLAINABLE ARTIFICIAL INTELLIGENCE MK al-Bashiti, A Ghasemi, ATG Tapeh, H Hostetter, D Craig, MZ Naser66 | 1 | 2022 |
| Simple Visual Aids for Predicting Fire Response of RC Columns: Nomograms via Machine Learning MZ Naser, ATG Tapeh, H Hostetter, MK al-Bashiti, W Qin Emirati Journal of Civil Engineering and Applications 1 (1), 45-69, 2023 | | 2023 |
M.Z. Naser, PhD, PESchool of Civil and Enviro. Engg & Earth Sciences/AI Research Institute for Science & EngineeringVerified email at clemson.edu
