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Dr Kay Rogage

Assistant Professor

Department: Computer and Information Sciences

I am a Research Fellow in Digital Living. An active member of Northumbria’s BIM Academy Research Team, my work spans across the disciplines of computer science and the built environment with a focus on enabling the interoperability of building models and tools to overcome the technical barriers around data exchange in the built environment. My work also focuses on the automatic augmentation of Building Information Model (BIM) data using Machine Learning techniques.

My previous roles have included Research Associate at Newcastle University and for Royal Institute of British Architects (RIBA) Enterprises developing a number of software products for the National Building Specification (NBS). I have also worked in a number of new digital media organisations such as TH_NK developing solutions for a range of digital formats. As a lecturer at Northumbria’s Computer Information Sciences Department, I apply my research and knowledge to both undergraduate and postgraduate taught programmes.

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  • Please visit the Pure Research Information Portal for further information
  • Automating excavator productivity measurement using deep learning, Mahamedi, E., Rogage, K., Doukari, O., Kassem, M. 22 Apr 2022, In: Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction
  • Incorporating Emerging Technologies in the Forensic Analysis of Construction Project Delays, Boyacioglu, S., Greenwood, D., Rogage, K. 1 Nov 2022, In: IOP Conference Series: Earth and Environmental Science
  • Object-centred automated compliance checking: a novel, bottom-up approach, Doukari, O., Greenwood, D., Rogage, K., Kassem, M. 19 Apr 2022, In: Journal of Information Technology in Construction
  • Automating equipment productivity measurement using deep learning, Mahamedi, E., Rogage, K., Doukari, O., Kassem, M. 26 Jul 2021, Proceedings of the 2021 European Conference on Computing in Construction, University College Dublin
  • Colliding epistemologies, productive tensions and usable pasts in the generation of heritage-led immersive experiences, Swords, J., Nally, C., Rogage, K., Watson, R., Charlton, J., Kirk, D. 1 Feb 2021, In: International Journal of Heritage Studies
  • Digitally-Enabled Design Management, Tallet, E., Gledson, B., Rogage, K., Thompson, A., Wiggett, D. 22 May 2021, Handbook of Research on Driving Transformational Change in the Digital Built Environment, Hershey, PA, IGI Global
  • Evolving Deep Architecture Generation with Residual Connections for Image Classification Using Particle Swarm Optimization, Lawrence, T., Zhang, L., Rogage, K., Lim, C. 28 Nov 2021, In: Sensors

  • Tom Lawrence Evolutionary and Handcrafted Efficient and Accurate Deep Neural Networks for Image Classification Start Date: 28/01/2021 End Date: 23/12/2022
  • Megan Doherty Exploring the expansion of planner’s engagement capabilities via accessing the data from a building information model for public consultation Start Date: 01/10/2018 End Date: 23/12/2022

  • Computing Science PhD December 27 2013
  • Media Studies MA September 01 2007
  • Computing Science BSc June 20 2001
  • Fellow (FHEA) Higher Education Academy (HEA) 2016


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