M. Z. Naser - RankMe

27 papers Journal 27

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A review of machine learning with small and limited data. J. Big Data M. Z. Naser
2026	J	`jnl`	Auditing the Shadows: A Review of Methods to Detect Shared Training Data in Large Language Models. ACM Comput. Surv. M. Z. Naser
2026	J	`jnl`	Engineering Reasoning and Instruction (ERI) Benchmark: A Large Taxonomy-driven Dataset for Foundation Models and Agents. CoRR M. Z. Naser, Ahmad Bani Awwad, Zoie McCreery, Radwa Eissa, Ahmad Z. Naser, Gianluca Cusatis, Andrew Metcalf, Kapil Madathil, Jamal Abdalla, Venkatesh Kodur, Mohammad Reza Saeb
2026	J	`jnl`	Epistemic virtues and ethics of explanation in machine learning. AI Ethics M. Z. Naser, Z. K. Naser
2026	J	`jnl`	Fundamental flaws of physics-informed neural networks and explainability methods in engineering systems. Comput. Ind. Eng. M. Z. Naser
2026	J	`jnl`	Philosophy-informed machine learning. Appl. Soft Comput. M. Z. Naser
2025	J	`jnl`	A Guide to Machine Learning Epistemic Ignorance, Hidden Paradoxes, and Other Tensions. WIREs Data. Mining. Knowl. Discov. M. Z. Naser
2025	J	`jnl`	A Look into How Machine Learning is Reshaping Engineering Models: the Rise of Analysis Paralysis, Optimal yet Infeasible Solutions, and the Inevitable Rashomon Paradox. CoRR M. Z. Naser
2025	J	`jnl`	Dataism, skepticism, and intuition for interpretable machine learning. AI Ethics M. Z. Naser
2025	J	`jnl`	Design of masonry structures using conditional generative adversarial networks fused with property text information. Comput. Aided Civ. Infrastructure Eng. Arash Teymori Gharah Tapeh, M. Z. Naser
2025	J	`jnl`	Land use and land cover change detection from multisource satellite imagery - A hybrid convolutional neural network approach. Eng. Appl. Artif. Intell. M. S. Babitha, A. Diana Andrushia, N. Anand, M. Z. Naser, Y. Pari
2025	J	`jnl`	The Engineer's Dilemma: A Review of Establishing a Legal Framework for Integrating Machine Learning in Construction by Navigating Precedents and Industry Expectations. CoRR M. Z. Naser
2024	J	`jnl`	A Review of 315 Benchmark and Test Functions for Machine Learning Optimization Algorithms and Metaheuristics with Mathematical and Visual Descriptions. CoRR M. Z. Naser, Mohammad Khaled al-Bashiti, Arash Teymori Gharah Tapeh, Armin Dadras Eslamlou, Ahmed Naser, Venkatesh Kodur, Rami Hawileh, Jamal A. Abdalla, Nima Khodadadi, Amir H. Gandomi
2024	J	`jnl`	Beyond development: Challenges in deploying machine learning models for structural engineering applications. CoRR Mohsen Zaker Esteghamati, Brennan Bean, Henry V. Burton, M. Z. Naser
2024	J	`jnl`	Large Language Models in Fire Engineering: An Examination of Technical Questions Against Domain Knowledge. CoRR Haley Hostetter, M. Z. Naser, Xinyan Huang, John Gales
2024	J	`jnl`	SPINEX-Clustering: Similarity-based Predictions with Explainable Neighbors Exploration for Clustering Problems. CoRR M. Z. Naser, Ahmed Naser
2024	J	`jnl`	SPINEX-TimeSeries: Similarity-based Predictions with Explainable Neighbors Exploration for Time Series and Forecasting Problems. CoRR Ahmed Naser, M. Z. Naser
2024	J	`jnl`	SPINEX: Similarity-based Predictions with Explainable Neighbors Exploration for Anomaly and Outlier Detection. CoRR M. Z. Naser, Ahmed Naser
2024	J	`jnl`	SPINEX_ Symbolic Regression: Similarity-based Symbolic Regression with Explainable Neighbors Exploration. CoRR M. Z. Naser, Ahmed Naser
2023	J	`jnl`	Can AI Chatbots Pass the Fundamentals of Engineering (FE) and Principles and Practice of Engineering (PE) Structural Exams? CoRR M. Z. Naser, Brandon Ross, Jennier Ogle, Venkatesh Kodur, Rami Hawileh, Jamal A. Abdalla, Huu-Tai Thai
2022	J	`jnl`	Causal Discovery and Causal Learning for Fire Resistance Evaluation: Incorporating Domain Knowledge. CoRR M. Z. Naser, Aybike Özyüksel Çiftçioglu
2022	J	`jnl`	Causality, Causal Discovery, and Causal Inference in Structural Engineering. CoRR M. Z. Naser
2022	J	`jnl`	Simplifying Causality: A Brief Review of Philosophical Views and Definitions with Examples from Economics, Education, Medicine, Policy, Physics and Engineering. CoRR M. Z. Naser
2021	J	`jnl`	Demystifying Ten Big Ideas and Rules Every Fire Scientist & Engineer Should Know About Blackbox, Whitebox & Causal Artificial Intelligence. CoRR M. Z. Naser
2021	J	`jnl`	Explainable Machine Learning using Real, Synthetic and Augmented Fire Tests to Predict Fire Resistance and Spalling of RC Columns. CoRR M. Z. Naser, V. K. Kodur
2021	J	`jnl`	RAI: Rapid, Autonomous and Intelligent machine learning approach to identify fire-vulnerable bridges. Appl. Soft Comput. M. Abedi, M. Z. Naser
2020	J	`jnl`	Insights into Performance Fitness and Error Metrics for Machine Learning. CoRR M. Z. Naser, Amir Alavi