Dimosthenis Kifokeris
Dr. Dimosthenis Kifokeris is Assistant Professor in Construction Production and Management of Construction Projects at Chalmers University of Technology, Division of Construction Management, Department of Architecture and Civil Engineering, Gothenburg, Sweden (02/2019-). His main research interests include construction production, construction informatics (machine learning, blockchain, Internet of Things, and Building Information Models), lean construction, integrated project delivery, constructability, and risk analysis. Dimosthenis participates in domestic and international collaborative research between the academia and the industry. His interdisciplinary scientific perspectives include data science, applied statistics, organizational theory, and strategic management. In his Ph.D. at the Aristotle University of Thessaloniki (A.U.Th.), Greece (07/2014-11/2018), titled "Risk-based Constructability Assessment in Civil Engineering Projects", he implemented unsupervised and supervised machine learning to integrate construction management frameworks. He formerly was a project researcher and academic assistant at Chalmers (11/2018-01/2019), a researcher for TUD COST Action TU1406 (06/2015-04/2019), and a doctoral researcher and teaching assistant at A.U.Th. (07/2014-11/2018). He has also worked as an engineering consultant and construction manager (2008-2018). He has a M.Sc. in Engineering Project Management (2013, A.U.Th.), and a M.Eng. in Civil and Structural Engineering (2012, A.U.Th.). He is currently a member of, among others, SBU, Lean Forum Bygg, CMB, IABSE, IALCCE, and the Technical Chamber of Greece. He has been publishing in top journals and peer-reviewed conference proceedings, and is an active reviewer in Construction Management and Economics, the ASCE Journal of Construction Engineering and Management, the ASCE Journal of Infrastructure Systems, and the Journal of Information Technology in Construction (ITcon).

Showing 24 publications
Challenges in the digital transformation of lean design methods: a case study
Swedish lean construction practices identified in the last decade of research
Machine learning for analysis of occupational accidents registration data
Construction planning with machine learning
Risk source-based constructability appraisal using supervised machine learning
An analysis of the impartial implementation in practice of risk identification in technical projects
A human touch? How machine learning can improve project performance
Building Information Models’ data for machine learning systems in construction management
Blockchain in building logistics: emerging knowledge, and related actors in Sweden
Blockchain in construction – hype, hope, or harm?
Application of linguistic clustering to define sources of risk in technical projects
Bridge quality appraisal methodology: application in a reinforced concrete overpass roadway bridge
Bridge quality appraisal methodology: application in the Strimonas Bridge. Case study.
Constructability: Outline of Past, Present and Future Research
Project performance appraisal frameworks as blueprints for bridge quality control
Lifecycle-based discretization of bridge performance indicators
Seismic design of R/C piers of hollow circular cross sections
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Showing 4 research projects
Quality and self-monitoring as a service
Quality assurance and self-control as a service
Digital business model for large site building logistics