Ioannis Brilakis

Short CV

Dr Ioannis Brilakis is a Laing O'Rourke Reader in Construction Engineering and the Director of the Construction Information Technology Laboratory at the Division of Civil Engineering of the Department of Engineering at the University of Cambridge. He completed his PhD in Civil Engineering at the University of Illinois, Urbana Champaign in 2005. He then worked as an Assistant Professor at the Departments of Civil and Environmental Engineering, University of Michigan, Ann Arbor (2005-2008) and Georgia Institute of Technology, Atlanta (2008-2012) before moving to Cambridge in 2012 as a Laing O’Rourke Lecturer. He was promoted to University Reader in October 2017. He has also held visiting posts at the Department of Computer Science, Stanford University as a Visiting Associate Professor of Computer Vision (2014) and at the Technical University of Munich as a Visiting Professor, Leverhulme International Fellow (2018-2019), and Hans Fischer Senior Fellow (2019-2021). He is a recipient of the NSF CAREER award, the 2019 ASCE J. James R. Croes Medal, the 2018 ASCE John O. Bickel Award, the 2013 ASCE Collingwood Prize, the 2012 Georgia Tech Outreach Award and the 2009 ASCE Associate Editor Award. Dr Brilakis is an author of over 190 papers in peer-reviewed journals and conference proceedings, an Associate Editor of the ASCE Computing in Civil Engineering, ASCE Construction Engineering and Management, Elsevier Automation in Construction, and Elsevier Advanced Engineering Informatics Journals, and the chair of the Board of Directors of the European Council on Computing in Construction.

Selected Awards

  • 2019-2027, CDT in Future Infra. and Built Environment-2 (FIBE2), CI, EPSRC
  • 2019-2023, Cloud Building Information Modelling, CI, H2020 MCSA ITN
  • 2017-2020, Autom. Construction Monitoring Via Semantic Info. Modelling, CI, ARC 
  • 2017-2021, AI-Optimised Pathways for Schedule Execution, CI, InnovateUK
  • 2017-2021, PointPix, PI. BP, LOR, Trimble, Topcon, GeoSLAM, and CSIC 
  • 2015-2017, Digitally Enabling the DfMA & Maintenance of Bridges, CI, InnovateUK
  • 2015-2017, SeeBridge, ERA.NET Infravation, CI, European Commission 
  • 2010-2015, Reciprocal R&R for Modelling of Constructed Facilities, PI, NSF 
  • 2010-2013, Machine Vision Enhanced Post Earthquake Inspection, CI, NSF 
  • 2010-2013, CAREER: VPR Models for R. Sensing of Civil Infrastructure, PI, NSF 
  • 2008-2011, Progressive Site Modelling with Videogrammetry, PI, NSF 
  • 2006-2011, Automated Vision Tracking of Project Related Entities, PI, NSF 

Research Interests

Dr Brilakis' research interests lie broadly in the field of construction engineering with a focus on construction automation and information technologies. This includes generating and updating building and infrastructure digital twins; sensing and data collection for civil infrastructure development; infrastructure computer vision and pattern recognition technologies for construction site multimedia data analysis, classification, retrieval, and processing; knowledge extraction and management; intelligent automation of design and construction tasks; infrastructure condition assessment, modelling, and sensing; integration of project information into visualization and simulation models or mixed reality systems; project control systems and field management technologies; and communication, collaboration and coordination technologies.

Selected Publications

  • Konstantinou, E., Lasenby, J. and Brilakis, I. (2019) "Adaptive Computer Vision-Based 2D Tracking of Workers in Complex Environments", J. of Automation in Construction, Elsevier, in press, DOI 10.1016/j.autcon.2019.01.018
  • Agapaki, E., Miatt, G. and Brilakis, I. (2018) "Prioritizing Object Types for Modelling Existing Industrial Facilities", J. of Automation in Construction, Elsevier, 96, December 2018, Pp. 211 – 223, DOI 10.1016/j.autcon.2018.09.011
  • Agapaki, E., Miatt, G. and Brilakis, I. (2018) "Prioritizing Object Types for Modelling Existing Industrial Facilities", J. of Automation in Construction, Elsevier, 96, December 2018, Pp. 211 – 223, DOI 10.1016/j.autcon.2018.09.011
  • Nguyen, B. and Brilakis, I. (2018) "Real-Time Validation of Vision-Based Over-Height Vehicle Detection System", J. of Advanced Engineering Informatics, Elsevier, accepted
  • Vick, S. and Brilakis, I. (2018) "Road Design Layer Detection in Point Cloud Data for Construction Progress Monitoring", J. of Computing in Civil Engineering, ASCE, 32(5), September 2018, DOI 10.1061/(ASCE)CP.1943-5487.0000772
  • Huethwohl, P. and Brilakis, I. (2018) "Detecting Healthy Concrete Surfaces", J. of Advanced Engineering Informatics, Elsevier, 37, August 2018, Pp. 150 – 162, DOI 10.1016/j.aei.2018.05.004
  • Konstantinou, E. and Brilakis, I. (2018) "Matching Construction Workers across Views for Automated 3D Vision Tracking On-Site", J. of Construction Engineering and Management, ASCE, 144(7), July 2018, DOI 10.1061/(ASCE)CO.1943-7862.0001508
  • Sacks, R., Kedar, A., Borrmann, A., Ma, L., Daum, S., Yosef, R., Brilakis, I., Huethwohl, P., Liebich, T., Barutcu, B. and Muhic, S. (2018) "SeeBridge Next Generation Bridge Inspection: Overview, Information Delivery Manual and Model View Definition", J. of Automation in Construction, Elsevier, 90, June 2018, Pp. 134 – 145, 10.1016/j.autcon.2018.02.033
  • Huethwohl, P., Brilakis, I., Borrmann, A. and Sacks, R. (2018) "Integrating RC bridge defect information into BIM", J. of Computing in Civil Engineering, ASCE, 32(3), May 2018, DOI 10.1061/(ASCE)CP.1943-5487.0000744
  • Davila Delgado, J. M., Butler, L. J., Brilakis, I., Elshafie, M. Z. E. B., and Middleton, C.R. (2018) "Structural Performance Monitoring Using Data-Driven and Dynamic BIM Environment", J. of Computing in Civil Engineering, ASCE, 32(3), May 2018, DOI 10.1061/(ASCE)CP.1943-5487.0000749, received the ASCE 2019 J. James R. Croes Medal

Publications as TUM-IAS-Fellow


  • Argyroudis, Sotirios A.; Mitoulis, Stergios Aristoteles; Chatzi, Eleni; Baker, Jack W.; Brilakis, Ioannis; Gkoumas, Konstantinos; Vousdoukas, Michalis; Hynes, William; Carluccio, Savina; Keou, Oceane; Frangopol, Dan M.; Linkov, Igor: Digital technologies can enhance climate resilience of critical infrastructure. Climate Risk Management 35, 2022, 100387 mehr…
  • Assadzadeh, Amin; Arashpour, Mehrdad; Brilakis, Ioannis; Ngo, Tuan; Konstantinou, Eirini: Vision-based excavator pose estimation using synthetically generated datasets with domain randomization. Automation in Construction 134, 2022, 104089 mehr…
  • Fitzsimmons, John Patrick; Lu, Ruodan; Hong, Ying; Brilakis, Ioannis: Construction schedule risk analysis – a hybrid machine learning approach. Journal of Information Technology in Construction 27, 2022, 70-93 mehr…


  • Agapaki, Eva; Brilakis, Ioannis: CLOI: An Automated Benchmark Framework for Generating Geometric Digital Twins of Industrial Facilities. Journal of Construction Engineering and Management 147 (11), 2021, 04021145 mehr…
  • Agapaki, Eva; Brilakis, Ioannis: Instance Segmentation of Industrial Point Cloud Data. Journal of Computing in Civil Engineering 35 (6), 2021, 04021022 mehr…
  • Hong, Ying; Xie, Haiyan; Bhumbra, Gary; Brilakis, Ioannis: Comparing Natural Language Processing Methods to Cluster Construction Schedules. Journal of Construction Engineering and Management 147 (10), 2021 mehr…
  • Pan, Yuandong; Braun, Alex; Borrmann, André; Brilakis, Ioannis: Void-growing: a novel Scan-to-BIM method for manhattan world buildings from point cloud. Proceedings of the 2021 European Conference on Computing in Construction, University College Dublin, 2021 mehr…
  • Swanborough, Jack; Kim, Min-Koo; Agapaki, Eva; Brilakis, Ioannis: Automated optimum visualization system for construction drawing reading. Journal of Information Technology in Construction 26, 2021, 681-696 mehr…