NEW!! Our paper titled "Context-aware Sequence Labeling for Condition Information Extraction from Historical Bridge Inspection Reports" is published in the Journal of Advanced Engineering Informatics (IF = 3.879). The paper can be accessed and downloaded for 50 days from here.

NEW!! Our paper titled "Mapping Textual Descriptions to Condition Ratings to Assist Bridge Inspection and Condition Assessment Using Hierarchical Attention" is accepted in the Journal of Automation in Construction (IF = 5.669).

NEW!! Our paper titled "Leveraging Mixed Reality for Augmented Structural Mechanics Education" is accpeted for presentation and publication in the proceedings of the American Society for Engineering Education (ASEE) Annual Conference and Exposition.

Our proposed computational framework titled "Using remote sensing and AI for data-driven wildfire modeling and management" was recently awarded a Microsoft AI for Earth Compute Grant for Azure Cloud services. Thanks to Microsoft for the support!

Research paper accepted for publication in the Journal of Transportation Research Record. "Deep Learning-based Visual Identification of Signs of Bat Presence in Bridge Infrastructure Images: A Transfer Learning Approach" is part of research by graduate student Tianshu Li and co-authored by Prof. Devin Harris, and Bridget Donaldson of Virginia Transportation Research Council as part of the project “Development of a Test Method to Determine the Source of Staining on Structures”.

Our recent paper coauthored by Mehrdad Shafiei Dizaji and Devin Harris was published in Engineering Structures. The paper introduces a powerful method that not only detects damage but can also quantify its location and 3D shape via the use of optical cameras and topology optimization. The article can be found here.

Research paper "E-scooter Availability Versus Utilization Insights: A Geospatial Analysis" was accepted for presentation at the 100th Annual Meeting of the Transportation Research Board (TRB ). This work by graduate student Tina Tang presents a data-driven geospatial analysis of dockless micromibity and was co-authored by Prof. Devin Harris, and Amanda Poncy (City of Charlottesville).

Our image-based sensing work was presented at the International Digital Image Correlation Society Conference (iDICS-2020) in a plenary talk by Prof. Devin Harris (“Civil Infrastructure – The Next Big Playground for Image-Based Assessment and Digital Image Correlation“), and a technical talk by Mehrdad Dizaji (“Full-Field Sensing and Topology Optimization for Reconstructing the 3D Geometry of Internal Structural Damage”).

Honored to receive the 2020 Young Professionals Award from the Structural Engineering Institute (SEI) of the American Society of Civil Engineers (ASCE). Special thanks to the SEI Futures Fund and its generous contributors for this great recognition. See news coverage on ASCE website here.

Our paper titled “A Big Data Analytics Strategy for Scalable Urban Infrastructure Condition Assessment Using Semi-supervised Multi-transform Self-training ” is published in Springer's Journal of Civil Structural Health Monitoring. The article is available at https://link.springer.com/article/10.1007/s13349-020-00386-4.

I successfully defended my Ph.D. dissertation titled “Deep Learning for Robust and Efficient Automated Defect Recognition in Critical Infrastructure”. Special thanks to my advisor Prof. Devin Harris and committee members Profs. Scott Acton, Laura Barnes, Arsalan Heydarian, and David Lattanzi.

Received the 2019 CEE Award for Research Excellence in recognition of superior research performance by a graduate student. Special thanks to the Department of Engineering Systems and Environment (ESE) at UVA for this recognition.

My research was recently featured in a March 2019 edition of UVA Today. See full article and coverage. The article discusses the applications of our work in the field of automated structural inspection.