Kofi Asabere Bediako Asare, Ph.D - Christopher C. Gibbs College of Architecture

Kofi Asabere Bediako Asare, Ph.D

Kofi Asabere Bediako Asare, Ph.D

Contact

asare@ou.edu

 

Education

University of Florida, Gainesville, FL:
Design, Construction, and Planning (Emphasis in Construction Management)
Ph.D., 12/2023

Loughborough University, England:
Construction Management
MSc., 12/2019

KNUST, Ghana:
Architecture
M.Arch, 11/2015

KNUST, Ghana:
Architecture
BSc., 06/2013

Research Interests

  • Building Information Modeling (BIM)
  • Virtual Design and Construction (VDC)
  • Digital Twins
  • AI in Construction and Building Operations and Maintenance
  • Sustainability of the Built Environment
  • Human-building interaction

About

Dr. Kofi Asare is an Assistant Professor of Construction Science at the University of Oklahoma and the PI of the Construction Innovation and Analytics Lab (CInnaLAB). Dr. Asare’s research is centered on digitalized and data-driven built environments. His research activity brings together design, construction science, facility management, software engineering, and computer science domains to provide the relevant guidance to facility owners and researchers on how to optimize the performance of their constructed facilities using Building Information Modeling (BIM)- based Digital Twins as Intelligent Realities. Ultimately, his research seeks to harness the benefits of the increasing digitalization of processes in the built environment to ensure that owners of constructed facilities obtain maximum value from their investments while providing a safe and comfortable environment for their patrons through analytics-driven decision-making. In addition, Dr. Asare seeks to create research experiences for undergraduate students through teaching-based research.

Peer-reviewed Publications (Selected):

Asare, K.A.B., Liu, R., and Anumba, C.J. (2024). “Defining a System Architecture for Operational Digital Twins for Predictive Maintenance.” In Digital Twins in Construction and the Built Environment eds. H. Jebelli et al. ASCE: Reston, VA. https://doi.org/10.1061/9780784485606.ch6

Asare, K.A.B., Liu, R., Anumba, C.J., Raja R.A. Issa (2024). “Real-World Prototyping and Evaluation of Digital Twins for Predictive Facility Maintenance.”Journal of Building Engineering, 110890, ISSN 2352-7102. https://doi.org/10.1016/j.jobe.2024.110890.

Asare, K.A.B., Liu, R., and Anumba, C.J. (2024). “Facilities Management Professionals’ Perceptions of Digital Twins as Intelligent Realities.” 2024 Construction Research Congress, Iowa. https://doi.org/10.1061/9780784485262.121

Asare, K.A.B., Liu, R. and Anumba, C.J. (2023). “Building information modelling for airport facility management: the case of a US airport”, Infrastructure Asset Management. https://doi.org/10.1680/jinam.22.00019

Asare, K.A.B., Liu, R. and Anumba, C.J. (2021). “Building information modeling to support facilities management of large capital projects: a critical review”, Facilities, Vol. 40 No. 3/4, pp. 176-197. https://doi.org/10.1108/F-11-2020-0124

Abugu, C., Anumba, C.J., and Asare, K.A.B. (2023). “Investigation of the Costs and Benefits of Digital Twins in Construction.” International Conference on Computing in Civil Engineering (i3ce 2023), Corvallis, Oregon. https://doi.org/10.1061/9780784485231.065

Asare, K.A.B., Issa, R.R.A., Liu, R., and Anumba, C. (2021). “BIM for Facilities Management: Potential Legal Issues and Opportunities.” Journal of Legal Affairs and Dispute Resolution in Engineering and Construction. Vol. 13, Issue 4 (November 2021). https://doi.org/10.1061/(ASCE)LA.1943-4170.0000502

Asare, K.A.B., Liu, R., and Anumba, C.J. (2021). “A Unified Acceptance Model for BIM for FM: Conceptual Development.” International Conference on Computing in Civil Engineering (i3ce 2021), Orlando, Florida. https://ascelibrary.org/doi/abs/10.1061/9780784483893.057

Asare, K.A.B., Ruikar, K.D., Zanni, M., and Soetanto, R. (2020). “BIM-based LCA and energy analysis for optimised sustainable building design in Ghana.” SN Appl. Sci. 2, 1855. https://doi.org/10.1007/s42452-020-03682-2

Research Projects

  • Digital Twins for Infrastructure Upgrading and Retrofitting
  • Generative AI for Predictive Maintenance in Buildings
  • Digital Twins as Intelligent Realities
  • Future-proofing Construction Students Through Context-specific Data Analytics and AI Education
  • Cognitive Digital Twins for Adaptive Indoor Environmental Quality Management

Courses

  • CNS 1312 – Computers in Construction Lab
  • CNS 4970/5970 – Construction Data Analytics and Innovation
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