Jerome F. Hajjar

About

Jerome Hajjar, CDM Smith Professor and University Distinguished Professor, has been recognized by the American Society of Civil Engineers as a 2026 Distinguished Member for his fundamental contributions to civil engineering education and to design practice through research in steel and composite structures, including structural stability and earthquake engineering, and for leadership of professional and academic committees and boards of direction that advance the practice of civil engineering. During his tenure as chair of the Department of Civil and Environmental Engineering from 2010 to 2025, the department tripled in size and significantly elevated its global research impact. Hajjar, who also serves as director of the STReSS Laboratory, will be officially honored at the ASCE OPAL Gala in October 2026.

Research topics

• Artificial Intelligence
• Computer Science
• Computer vision
• Mathematics
• Data Mining
• Machine Learning
• Engineering
• Geology
• Remote sensing
• Optics

Selected publications

• Automated extraction of structural elements in steel girder bridges from laser point clouds

  Automation in Construction · 2021 · 81 citations

  Senior authorCorresponding
  DOI

• Towards automated detection and quantification of concrete cracks using integrated images and lidar data from unmanned aerial vehicles

  Structural Control and Health Monitoring · 2021 · 61 citations

  Senior authorCorresponding

  Recent advances in visual sensing technology and unmanned aerial vehicle (UAV) provide an effective tool to capture the as-is conditions of infrastructure and thus have gained their popularity in infrastructure inspection and documentation. To facilitate this process, several recent studies have proposed automated methods for detecting concrete cracks from UAV-based images. This study is aimed at proposing a new method for automating both the detection and quantification of concrete cracks. The…

  DOI

• A Synopsis of Sustainable Structural Systems With Rocking, Self-Centering, and Articulated Energy-Dissipating Fuses

  2026-02-01 · 28 citations

  articleOpen access1st authorCorresponding

  This synopsis examines previous research related to seismic energy-dissipating structural systems for buildings. These systems are grouped into self-centering systems, systems exhibiting rocking behavior and systems with energy-dissipating fuse elements. Bracing systems, precast buildings, steel frames with post-tensioning strands, rocking shear walls and some similar structural systems are investigated for self- centering behavior. Rocking motion reduces seismic loading and ductility demands by…

  PublisherOA PDFDOI

• Machine Learning Approach for Sequence Clustering with Applications to Ground-Motion Selection

  Journal of Engineering Mechanics · 2020 · 28 citations

  Clustering analysis of sequential data is of great interest and importance in many science and engineering areas thanks to the explosive growth of time-series data. Effective methods, especially for sequence clustering, are strongly needed to extract features from data for better representation learning. This paper presents an unsupervised machine learning algorithm for sequence clustering based on dynamic k-means. Specifically, the clustering problem is firstly formulated rigorously to an optim…

  DOI

• Wind Fields in Category 1–3 Tropical Cyclones Are Not Fully Represented in Wind Turbine Design Standards

  Journal of Geophysical Research Atmospheres · 2023-08-10 · 20 citations

  articleOpen accessSenior author

  Abstract Offshore wind energy deployment in the U.S. is expected to increase in the years to come, with proposed wind farm sites located in regions with high risk for tropical cyclones. Yet, the wind turbine design criteria outlined by the International Electrotechnical Commission for extreme events may not account for wind field characteristics unique to tropical cyclones. To evaluate if current design standards capture the extreme conditions of these storms, we perform idealized large‐eddy sim…

  PublisherOA PDFDOI

Recent grants

• Collaborative Research: Reconfiguring Steel Structures: Energy Dissipation and Buckling Mitigation Through the Use of Steel Foams

  NSF · $60k · 2010–2013

• Physics-Reinforced Deep Learning for Structural Metamodeling

  NSF · $599k · 2020–2024

• NRI: Large: Collaborative Research: Fast and Accurate Infrastructure Modeling and Inspection with Low-Flying Robots

  NSF · $328k · 2013–2018

Frequent coauthors

• Sanjay R. Arwade

  University of Massachusetts Amherst

  56 shared

• Andrew T. Myers

  ORCID

  53 shared

• Robert J. Dexter

  38 shared

• Wystan Carswell

  37 shared

• Sean C. Cotton

  Thornton Tomasetti (United States)

  35 shared

• Roberto T. Leon

  34 shared

• Tōru Takeuchi

  Osaka University of Pharmaceutical Sciences

  32 shared

• Ryota MATSUI

  31 shared

Labs

• STReSS LaboratoryPI

Awards & honors

• American Society of Civil Engineers Distinguished Member (20…
• William H. Wisely American Civil Engineer Award (2025)
• BSCES College Educator Award (2025)
• Structural Stability Research Council (SSRC) Distinguished M…
• AISC Special Achievement Award (2024)

Similar researchers at Northeastern University

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• Akram N. Alshawabkehh-56
• Ming L. Wangh-53