| Emerging artificial intelligence methods in structural engineering H Salehi, R Burgueño Engineering structures 171, 170-189, 2018 | 543 | 2018 |
| Machine learning framework for predicting failure mode and shear capacity of ultra high performance concrete beams R Solhmirzaei, H Salehi, V Kodur, MZ Naser Engineering structures 224, 111221, 2020 | 85 | 2020 |
| A comprehensive review of self-powered sensors in civil infrastructure: State-of-the-art and future research trends H Salehi, R Burgueño, S Chakrabartty, N Lajnef, AH Alavi Engineering Structures 234, 111963, 2021 | 39 | 2021 |
| Structural assessment and damage identification algorithms using binary data H Salehi, S Das, S Chakrabartty, S Biswas, R Burgueño Smart Materials, Adaptive Structures and Intelligent Systems 57304, V002T05A011, 2015 | 39 | 2015 |
| Genetic programming in civil engineering: Advent, applications and future trends Q Zhang, K Barri, P Jiao, H Salehi, AH Alavi Artificial Intelligence Review 54, 1863-1885, 2021 | 38 | 2021 |
| Towards packet-less ultrasonic sensor networks for energy-harvesting structures S Das, H Salehi, Y Shi, S Chakrabartty, R Burgueno, S Biswas Computer Communications 101, 94-105, 2017 | 37 | 2017 |
| Data mining methodology employing artificial intelligence and a probabilistic approach for energy-efficient structural health monitoring with noisy and delayed signals H Salehi, S Das, S Biswas, R Burgueño Expert Systems with Applications 135, 259-272, 2019 | 34 | 2019 |
| Structural damage identification using image‐based pattern recognition on event‐based binary data generated from self‐powered sensor networks H Salehi, S Das, S Chakrabartty, S Biswas, R Burgueño Structural Control and Health Monitoring 25 (4), e2135, 2018 | 34 | 2018 |
| Data interpretation framework integrating machine learning and pattern recognition for self-powered data-driven damage identification with harvested energy variations H Salehi, S Biswas, R Burgueño Engineering Applications of Artificial Intelligence 86, 136-153, 2019 | 21 | 2019 |
| Damage identification in aircraft structures with self‐powered sensing technology: A machine learning approach H Salehi, S Das, S Chakrabartty, S Biswas, R Burgueño Structural Control and Health Monitoring 25 (12), e2262, 2018 | 20 | 2018 |
| A machine-learning approach for damage detection in aircraft structures using self-powered sensor data H Salehi, S Das, S Chakrabartty, S Biswas, R Burgueño Sensors and Smart Structures Technologies for Civil, Mechanical, and …, 2017 | 19 | 2017 |
| Integrated structural health monitoring in bridge engineering Z He, W Li, H Salehi, H Zhang, H Zhou, P Jiao Automation in Construction 136, 104168, 2022 | 18 | 2022 |
| Structural health monitoring from discrete binary data through pattern recognition H Salehi, R Burgueño, S Das, S Biswas, S Chakrabartty Insights and Innovations in Structural Engineering, Mechanics and …, 2016 | 18 | 2016 |
| Seismic protection of vulnerable equipment with semi-active control by employing robust and clipped-optimal algorithms H Salehi, T Taghikhany, A Yeganeh Fallah International Journal of Civil Engineering 12 (4), 413-428, 2014 | 17 | 2014 |
| Machine learning-driven assessment of fire-induced concrete spalling of columns MZ Naser, H Salehi ACI Materials Journal 117 (6), 7-16, 2020 | 14 | 2020 |
| An algorithmic framework for reconstruction of time-delayed and incomplete binary signals from an energy-lean structural health monitoring system H Salehi, S Das, S Chakrabartty, S Biswas, R Burgueño Engineering Structures 180, 603-620, 2019 | 11 | 2019 |
| Application of robust-optimum algorithms in semi-active control strategy for seismic protection of equipment H Salehi, T Taghikhany 15th World Conference on Earthquake Engineering, Sep, 24-28, 2012 | 11 | 2012 |
| Localized damage identification in plate-like structures using self-powered sensor data: A pattern recognition strategy H Salehi, S Chakrabartty, S Biswas, R Burgueno Measurement 135, 23-38, 2019 | 10 | 2019 |
| Data-driven failure prediction in brittle materials: A phase field-based machine learning framework EAB de Moraes, H Salehi, M Zayernouri Journal of Machine Learning for Modeling and Computing 2 (1), 2021 | 9 | 2021 |
| Pattern recognition framework using asynchronous discrete binary data for condition and damage assessment in plate-like structures H Salehi, R Burgueño Journal of Intelligent Material Systems and Structures 30 (8), 1200-1215, 2019 | 6 | 2019 |
Rigoberto BurgueñoProfessor and Chair, Civil Engr., Professor, Mechanical Engr.;Stony Brook UniversityVerified email at stonybrook.edu
