Research

Area

Automation and sensing in construction engineering and management, IT applications in construction engineering and management, Integration of BIM with data capture technologies, Digital twins and AI applications in construction.

Expertise

Building Information Modeling, BIM, virtual and immersive design and construction applications, automation and IT in construction engineering and management.

Research description

Dr. Guven Isin's research interests are in the areas of IT applications, automation and sensing for construction engineering and management. Her current focus is on the utilization and integration of automation and data capture technologies with BIM for improving processes and operations in construction projects and in the built environment.

Graduate Student Opportunities

Please see the detailed instructions on applying for MSc, MEng and PhD positions.

Research in Automation and Sensing in Construction Engineering and Management

Instructions on applying for MSc, MEng and PhD positions in my research group in the area of Automation and Sensing in Construction Engineering and Management

Candidates should comply with the Department’s admission requirements for MSc, MEng and PhD.

For MSc applications, candidates should have their Bachelor’s completed (or soon to be completed). For PhD applications, candidates should hold a Master’s degree in Civil Engineering, Computer Science, Mechanical Engineering, Architecture or related fields.

Candidates are expected to have excellent written and oral communication skills in English (technical/academic writing experience is preferred), experience in coding/programming, and experience or strong interest in one or more of the following research areas:

Building Information Modeling (BIM) and Virtual Design and Construction (VDC)
  • Virtual, Augmented, and Mixed Reality applications
  • Digital twins
  • Integration of data capture and tracking technologies with BIM
  • As-built modeling of existing buildings and BIM in Facility Management
IT applications in construction
  • Improving construction processes via automation and use of advanced technologies
  • Automated monitoring of construction progress
  • Safety and quality inspections using computer vision
  • Remote supervision, inspection and approval of projects

All interested applicants, please contact Gursans Guven Isin and include the following in your email:

  • CV (with names of at least 2 references)
  • Cover letter (that explains why you are interested in doing a Master’s or PhD in my research group, what topic you are particularly interested in working on, and how you think your experience would contribute)
  • (Unofficial) transcripts
  • Example of your academic writing (e.g. technical report, published conference paper, journal paper) (optional for MEng students)

Due to high volume of emails I receive with regards to graduate admissions, I will not respond to emails sent without these attachments.

Additional Information

The University of Manitoba is committed to the principles of equity, diversity & inclusion and to promoting opportunities in hiring, promotion and tenure (where applicable) for systemically marginalized groups who have been excluded from full participation at the University and the larger community including Indigenous Peoples, women, racialized persons, persons with disabilities and those who identify as 2SLGBTQIA+ (Two Spirit, lesbian, gay, bisexual, trans, questioning, intersex, asexual and other diverse sexual identities).

Application materials, including letters of reference, will be handled in accordance with the protection of privacy provisions of "The Freedom of Information and Protection of Privacy" (Manitoba). Please note that curriculum vitae will be provided to participating members of the search process.

Selected Publications

Fernandes, D., Garg, S., Nikkel, M., Guven, G. (2024). "A GPT-Powered Assistant for Real-Time Interaction with Building Information Models", Buildings 14 (8), https://doi.org/10.3390/buildings14082499

Guven, G., Arceo, A., Bennett, A., Tham, M., Olanrewaju, B., McGrail, M., Isin, K., Olson, A.W., Saxe, S. (2022). “A Construction Classification System Database for Understanding Resource Use in Building Construction”, Scientific Data, Nature, https://doi.org/10.1038/s41597-022-01141-8

Arceo, A., Tham, M., Guven, G., MacLean, H.L., Saxe, S. (2021). “Capturing variability in material intensity of single-family dwellings: A case study of Toronto, Canada”, Resources, Conservation and Recycling, Elsevier, https://doi.org/10.1016/j.resconrec.2021.105885

Nahangi, M., Guven, G., Olanrewaju, B., Saxe, S. (2021). “Embodied greenhouse gas assessment of a bridge: A comparison of preconstruction Building Information Model and
construction records”, Journal of Cleaner Production, Elsevier, https://doi.org/10.1016/j.jclepro.2021.126388

Guven, G., Ergen, E. (2021). “Tracking major resources for automated progress monitoring of construction activities: masonry work case”, Construction Innovation: Information, Process, Management, Emerald Insight, https://doi.org/10.1108/CI-05-2020-0081

Ergen, E., Kula, B., Guven, G., Artan, D. (2021). “Formalization of Occupant Feedback and Integration with BIM in Office Buildings”, Journal of Computing in Civil Engineering, ASCE, 35(1), https://doi.org/10.1061/(ASCE)CP.1943-5487.0000940

Saxe, S., Guven, G., Pereira, L., et al. (2020). “Taxonomy of uncertainty in environmental life cycle assessment of infrastructure projects”, Environmental Research Letters, IOP Publishing, 15(8), https://doi.org/10.1088/1748-9326/ab85f8

Guven, G., Ergen, E. (2019). “A rule-based methodology for automated progress monitoring of construction activities: a case for masonry work”, ITcon, 24:188-208, http://www.itcon.org/2019/11