Research website: mznaser.com
Areas of Interest:
My research group is creating Causal & Explainable Machine Learning Methodologies to discover new knowledge hidden within systems belonging to the domains of Structural Engineering and Materials science to help us realize functional, sustainable, and resilient infrastructure. Much of my current projects cover the areas of structural & fire engineering, tailoring properties of construction materials, and retrofitting aging structures.
Ph.D., Michigan State University
M.S., American University of Sharjah, UAE
CE 4/6/8900 Machine Learning for Civil and Environmental Engineers
CE 4/6/8900 Structural Fire Engineering & Safety
CE 8030 Advanced Steel Design
CE 4020 Reinforced Concrete Design
CE 2010 Statics
Professional Engineer (PE)
American Society of Civil Engineers (ASCE)
American Concrete Institute (ACI)
Precast/Prestressed Concrete Institute (PCI)
The Fédération internationale du béton (FIB)
Refereed Journal Articles (published and/or accepted) [orange: denotes a CU student]
J(99). Al-Bashiti, M., Naser M.Z. (2022). Machine Learning for Wildfire Classification: Exploring Blackbox, eXplainable, Symbolic, and SMOTE Methods. Natural Hazards Research. https://doi.org/10.1016/j.nhres.2022.08.001. [Pre-print draft][code] (Open Access)
J(98). Al-Bashiti, M., Naser M.Z. (2022). Verifying Domain Knowledge and Theories on Fire-induced Spalling of Concrete through eXplainable Artificial Intelligence. Construction and Building Materials. https://doi.org/10.1016/j.conbuildmat.2022.128648. [Pre-print draft][code]
J(97). Tapeh A., Naser M.Z. (2022). Artificial Intelligence, Machine Learning, and Deep Learning in Structural Engineering: A Scientometrics Review of Trends and Best Practices. Archives of Computational Methods in Engineering. https://doi.org/10.1007/s11831-022-09793-w. [Pre-print draft]
J(96). Tapeh A., Naser M.Z. (2022). Discovering Graphical Heuristics on Fire-induced Spalling of Concrete through eXplainable Artificial Intelligence. Fire Technology. https://doi.org/10.1007/s10694-022-01290-7. [Pre-print draft]
J(95). Hostetter H., Naser M.Z., Hawileh, R.A. Karaki, G., Zhou, H. (2022). Enhancing fire resistance of reinforced concrete beams through sacrificial reinforcement. Architecture, Structures and Construction. https://doi.org/10.1007/s44150-022-00061-w. (Open Access)
J(94). Naser M.Z. (2022). “Digital Twin for Next Gen Concretes: On-demand Tuning of Vulnerable Mixtures through Explainable and Anomalous Machine Learning.” Cement and Concrete Composites. https://doi.org/10.1016/j.cemconcomp.2022.104640. [Pre-print draft]
J(93). Naser M.Z. (2022). "CLEMSON: An Automated Machine Learning (AutoML) Virtual Assistant for Accelerated, Simulation-free, Transparent, Reduced-order and Inference-based Reconstruction of Fire Response of Structural Members.” ASCE Journal of Structural Engineering. https://doi.org/10.1061/(ASCE)ST.1943-541X.003399.[Pre-print draft]
J(92). Daware A., Peerzada A., Naser M.Z., Rangaraju P., Butman B., “Examining the Behavior of Concrete Masonry Units under Fire and Post-fire Conditions.” Fire and Materials. https://doi.org/10.1002/fam.3085.(Open Access)
J(91). Mathews M., Kiran T., Anand N., Lubloy E., Naser M.Z., Aruraj, P. (2022). “Effect of protective coating on axial resistance and residual capacity of self-compacting concrete columns exposed to standard fire.” Engineering Structures. https://doi.org/10.1016/j.engstruct.2022.114444. (Open Access)
J(90). Andrushia A.D., Anand N., Neebha T.M., Naser M.Z., Lubloy E., (2022). “Autonomous detection of concrete damage under fire conditions.” Automation in Construction. https://doi.org/10.1016/j.autcon.2022.104364. (Open Access)
J(89). Naser M.Z. (2022). “A Faculty’s Perspective on Infusing Artificial Intelligence into Civil Engineering Education.” ASCE Journal of Civil Engineering Education. https://doi.org/10.1061/(ASCE)EI.2643-9115.0000065. [Pre-print draft]
J(88). Saleh E, Tarawneh, A., Naser M.Z. (2022). “Failure mode classification and deformability evaluation for concrete beams reinforced with FRP bars.” Composite Structures. https://doi.org/10.1016/j.compstruct.2022.115651. [Pre-print draft]
J(87). Çiftçioğlu A, Naser M.Z., (2022). “Hiding in Plain Sight: What Can Interpretable Unsupervised Machine Learning and Clustering Analysis Tell Us About the Fire Behavior of Reinforced Concrete Columns?.” Structures. https://doi.org/10.1016/j.istruc.2022.04.076. [Pre-print draft]
J(86). Hostetter H., Naser M.Z. (2022). “Characterizing disability in fire evacuation: A progressive review”. Journal of Building Engineering. https://doi.org/10.1016/j.jobe.2022.104573. [Pre-print draft]
J(85). Saleh E., Tarawneh A., Abedi M., Naser M.Z., Almasabha, G., (2021). “You Only Design Once (YODO): Gaussian Process-Batch Bayesian Optimization framework for Mixture Design of Ultra-High-Performance Concrete”. Construction and Building Materials. https://doi.org/10.1016/j.conbuildmat.2022.127270. [Pre-print draft] [Code] [Database]
J(84). Naser M.Z., Ross B. (2022). “An opinion piece on the dos and don’ts of artificial intelligence in civil engineering and charting a path from data-driven analysis to causal knowledge discovery.” Civil Engineering and Environmental Systems. https://doi.org/10.1080/10286608.2022.2049257 [Pre-print draft]
J(83). Hawileh R.A., Mhanna, H., Al Rashid, A, Abdalla J., Naser M.Z., (2022). “Flexural behavior of RC beams externally bonded with polyethylene terephthalate (PET) fiber reinforced polymer (FRP) laminates.” Engineering Structures. https://doi.org/10.1016/j.engstruct.2022.114036.
J(82). Naser M.Z. (2022). “Demystifying Ten Big Ideas and Rules Every Fire Scientist & Engineer Should Know About Blackbox, Whitebox and Causal Artificial Intelligence.” Fire Technology. https://doi.org/10.1007/s10694-021-01210-1. (Open Access)
J(81). Naser M.Z. (2022). “Deriving mapping functions to tie anthropometric measurements to body mass index via interpretable machine learning”. Machine Learning with Applications. https://doi.org/10.1016/j.mlwa.2022.100259. (Open Access)
J(80). Guzman-Torres J., Naser M.Z., Domínguez-Mota F. (2022). “Effective medium crack classification on laboratory concrete specimens via competitive machine learning”. Structures. https://doi.org/10.1016/j.istruc.2022.01.061
J(79). Daware A., Naser M.Z., Karaki G. (2022). “Generalized Temperature-dependent Material Models for Masonry Using Fire Tests, Statistical Methods and Artificial Intelligence.” Architecture, Structures and Construction.. https://doi.org/10.1007/s44150-021-00019-4. (Open Access)
J(78). Naser M.Z., Kodur, V.K.R. (2022). “Explainable Machine Learning using Real, Synthetic and Augmented Fire Tests to Predict Fire Resistance and Spalling of RC Columns.” Engineering Structures. https://doi.org/10.1016/j.engstruct.2021.113824 [Pre-print draft]
J(77). Vahabi H., Naser M.Z., Saeb M.R. (2022). “Fire Protection and Materials Flammability Control by Artificial Intelligence.” Fire Technology. https://doi.org/10.1007/s44150-021-00014-9. (Open Access)
J(76). McFarland D., Ross B., Naser M.Z., Teuffel, P., Blok, R. (2021). “Evaluation of Physical Parameters and Building Demolition or Adaptation Outcomes in the Netherlands.” Architecture, Structures and Construction. https://doi.org/10.1007/s44150-021-00014-9. (Open Access)
J(75). Zhou H, Li, S, Zhang C, Naser M.Z. (2021). “Modeling fire performance of externally prestressed steel–concrete composite beams.” Steel and Composite Structures. https://doi.org/10.12989/scs.2021.41.5.625. [Pre-print draft]
J(74). Naser M.Z., Alavi A. (2021). “Error Metrics and Performance Fitness Indicators for Artificial Intelligence and Machine Learning in Engineering and Sciences.” Architecture, Structures and Construction. https://doi.org/10.1007/s44150-021-00015-8. [Pre-print draft] (Open Access)
J(73). Degtyarev V., Naser M.Z. (2021). “Boosting machines for predicting shear strength of CFS channels with staggered web perforations.” Structures. https://doi.org/10.1016/j.istruc.2021.09.060.
J(72). Abedi M., Naser M.Z. (2021). “RAI: Rapid, Autonomous and Intelligent Machine Learning Approach to Identify
Fire-vulnerable Bridges.” Applied Soft Computing. https://doi.org/10.1016/j.asoc.2021.107896. [Pre-print draft][RAI v1 as a Software/App]
J(71). Naser M.Z. (2021). “Mapping Functions: A Physics-guided, Data-driven and Algorithm-agnostic Machine Learning Approach to Discover Causal and Descriptive Expressions of Engineering Phenomena.” Measurement. https://doi.org/10.1016/j.measurement.2021.110098. [Pre-print draft]
J(70). Zarringola R., Thai, T., Naser M.Z. (2021). “Application of machine learning models for designing CFCFST columns.” Journal of Constructional Steel Research. https://doi.org/10.1016/j.jcsr.2021.10685.
J(69). Naser M.Z., Kodur V.K.R., Thai H, Hawileh R, Abdalla J, Degtyarev V. (2021). “StructuresNet and FireNet: Benchmarking Databases and Machine Learning Algorithms in Structural and Fire Engineering Domains.” Journal of Building Engineering. https://doi.org/10.1016/j.jobe.2021.102977. [Pre-print draft]
J(68). Naser M.Z. (2021). “An Engineer’s Guide to eXplainable Artificial Intelligence and Interpretable Machine Learning: Navigating Causality, Forced Goodness, and the False Perception of Inference.” Automation in Construction. https://doi.org/10.1016/j.autcon.2021.103821. [Pre-print draft]
J(67). Naser M.Z., Thavarajah P. (2021). “Ceramic tiles as sustainable, functional and insulating materials to mitigate fire damage.” Advances in Applied Ceramics. https://doi.org/10.1080/17436753.2021.193515. [Pre-print draft]
J(66). Daware A., Naser M.Z., (2021). “Fire Performance of Masonry under Various Testing Methods.” Construction and Building Materials. https://doi.org/10.1016/j.conbuildmat.2021.123183. [Pre-print draft]
J(65). Kodur V.K.R., Naser M.Z. (2021). “Fire Hazard in Transportation Infrastructure: Review, Assessment and Mitigation Strategies.” Frontiers of Structural and Civil Engineering. https://doi.org/10.1007/s11709-020-0676-6.
J(64). Naser M.Z., Salehi, H. (2020). “Machine Learning-Driven Assessment of Fire-Induced Concrete Spalling of Columns.” ACI Materials Journal. https://doi.org/10.14359/51728120. [Pre-print draft]
J(63). Naser M.Z., Hawileh R.A., Abdalla J.A(2021). “Modeling Strategies of Finite Element Simulation of Reinforced Concrete Beams Strengthened with FRP: A Review.” Journal of Composite Science. https://doi.org/10.3390/jcs5010019. [Pre-print draft] (Open Access)
J(62). Kodur V.K.R., Naser M.Z. (2021). “Classifying Bridges for the Risk of Fire Hazard via Competitive Machine Learning.” Advances in Bridge Engineering. https://doi.org/10.1186/s43251-020-00027-2. [Pre-print draft] (Open Access)
J(61). Naser M.Z. (2021). “Mechanistically Informed Machine Learning and Artificial Intelligence in Fire Engineering and Sciences.” Fire Technology. https://doi.org/10.1007/s10694-020-01069-8. [Pre-print draft] Selected for Editor’s Choice [link] as well as Fire Science Reviews [link]
J(60). Naser M.Z. (2020). “Machine Learning Assessment of Fiber-Reinforced Polymer-Strengthened and Reinforced Concrete Members.” ACI Structural Journal. https://doi.org/10.14359/51728073. [Pre-print draft]
J(59). Naser M.Z. (2021). Observational Analysis of Fire-induced Spalling through Data Science and Machine Learning. ASCE Journal of Materials in Civil Engineering. https://doi.org/10.1061/(ASCE)MT.1943-5533.0003525. [Pre-print draft]
J(58). Naser M.Z., Thai S., Thai T. (2021). “Evaluating Structural Response of Concrete-Filled Steel Tubular Columns through Machine Learning.” Journal of Building Engineering. https://doi.org/10.1016/j.jobe.2020.101888. [Pre-print draft]
J(57). Solmirzaei R., Salehi H., Kodur V., Naser M.Z., (2020). “Machine learning framework for predicting failure mode and shear capacity of ultra high performance concrete beams.” Engineering Structures. Vol. 224, https://doi.org/10.1016/j.engstruct.2020.111221.
J(56). Naser M.Z. (2020). “Enabling cognitive and autonomous infrastructure in extreme events through computer vision.” Innovative Infrastructure Solutions. https://doi.org/10.1007/s41062-020-00351-6. [Pre-print draft]
J(55). Naser M.Z., Kodur V.K.R. (2020). “Temperature-induced Moment-Shear Interaction in Steel Beams.” International Journal of Steel Structures. https://doi.org/10.1007/s13296-020-00388-4. [Pre-print draft]
J(54). Mansouri I., Mortazavi S., Awoyera P., Naser M.Z. (2020). “Implementation of new elements and materials in OpenSees software for fire engineering.” Structures. Vol. 20. https://doi.org/10.1016/j.istruc.2020.08.021.
J(53). Mhanna H., Hawileh R.A., Abuzaid, W., Naser M.Z., Abdalla J.A. (2020). “Effect of temperature on the mechanical properties of polyethylene terephthalate (PET) FRP Laminates.” ASCE Journal of Materials in Civil Engineering. Vol. 32, https://doi.org/10.1061/(ASCE)MT.1943-5533.0003389. [Pre-print draft] (Open Access)
Books
B(04). Naser M.Z. (Editor), Leveraging Artificial intelligence into Engineering, Management, and Safety of Infrastructure. Taylor & Francis/CRC. 2023. [ISBN: 978-0-367-42210-3] [CRC] [Amazon] [Barnes & Noble]
B(03). Naser M.Z., Corbett G. (Editors), Handbook of Cognitive and Autonomous Systems for Fire Resilient Infrastructures. Springer. 2022. [ISBN-13: 978-3-030-98684-1] [ISBN-13: 978-3-030-98685-8 eBook] [https://doi.org/10.1007/978-3-030-98685-8] [Springer] [Amazon] [Barnes & Noble] [Preface]
B(02). Naser M.Z., Mueller K., The Concrete Industry in the Era of Artificial Intelligence, American Concrete Institute (ACI), 2021. ISBN-13: 978-1-64195-162-3. [flyer] [book]
B(01). Kodur V.K.R., Naser M.Z., Structural Fire Engineering, McGraw-Hill Publication, 2020. ISBN: 9781260128581, ISBN (10-DIGIT): 126012858X.
Contact Information:
Office: 312 Lowry Hall
Phone: (864) 656-3312
email Dr. Naser