Mani Golparvar-Fard earned his B.Sc. and first M.Sc. in civil engineering from Iran University of Science and Technology (2002), his M.A.Sc. in civil engineering from the University of British Columbia (2006), and his M.S. in computer science and Ph.D. in civil engineering from the University of Illinois at Urbana-Champaign (2010). He joined the department in December 2012, after serving as an assistant professor on the faculty of the Via Department of Civil and Environmental Engineering at Virginia Tech.
His professional experience includes working for Turner construction company. Dr. Golparvar-Fard has several patents and is currently involved in two start-up companies which were founded based on the outcomes of his ongoing research projects.
Some of his honors include receiving the James R. Croes Medal (2013) from the American Society of Civil Engineers (ASCE), the best journal paper award from the ASCE Journal of Construction Engineering and Management (2012), best paper award from 12th International Conference on Construction Applications of Virtual Reality (2012), first-place best poster award from the Construction Research Congress (2012), Paul E. Torgersen Research Excellence Award from Virginia Tech (2011), best poster award from the 10th Annual Construction Industry Institute conference (2010), best student paper award from the 6th International Conference on Innovation in AEC (2010), FIATECH CETI Award in the category of outstanding student researcher and FIATECH scholarship award (2010), first-place best poster award from the Construction Research Congress (2009), William E. O’Neil Pre-Doctoral Fellowship award (2008), and Intel and Shell scholars research program scholarship awards (2008, 2009) from the University of Illinois.
Dr. Golparvar-Fard has research interests in (1) creating and developing computer vision, image processing, and machine learning methods to automatically monitor building and construction performance, and reconstruct as-built 3D/4D building information models from static images as well as video streams; and (2) building information modeling to reason about building elements and systems to support model-based assessment of performance metrics and generate augmented reality visualizations.