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About me

Onur Demirci is a permanent (tenured) academic and has two vital roles.

He works as a Senior Lecturer (International Equivalency can be found HERE) and Course Leader in Westminster Business School of Applied Management, the University of Westminster.  He is currently conducting various research projects on the FinTech, PropTech digital innovations (Artificial Intelligence - AI, Big Data and Machine Learning), as part of a broader digital transformation in the property industry. Onur's job is thinking things about digitalisation that most people in the industry are not thinking of - yet.

He is creating algorithms (mathematical models) on the Automated Valuation Models (AVMs), based on Big Data, Artificial Intelligence - AI (Artificial Neural Network) and Machine Learning.

As Course Leader, Onur has the overall responsibility and his principal duties include:

Academic Leadership, Course Management, Quality Assurance & Enhancement, Student Induction & Support, Recruitment & Admissions and Personal Development.

His crucial leadership responsibilities include:

  • Provide academic leadership and direction for the course(s), ensuring that it reflects University and School policy, practice and processes; address and resolve issues relating to the quality of course delivery, student satisfaction, student progress and retention as they arise. 
  • Manage and lead Academicians including Module Leaders, Principal Lecturers, Senior Lecturers, Lecturers and Tutors to understand the philosophy and objectives of the course(s) and the needs of students.
  • Liaise and work with all other members of the course team including research, administrative and any technical staff to ensure that students receive high-quality academic support.
  • Lead the process of validation, revalidation and continuous review of the course, ensuring the content and pedagogy are updated and consistent with the needs of HE regulators, employers and relevant professional bodies.

Onur is an expert on all of the five types of Automated Valuation Models (AVMs). These are hedonic models, econometric forecasts, 'intelligent' systems (Artificial Neural Networks - ANN and Fuzzy Logic), house price index (HPI) models and tax assessed value models (TAV). 

Onur’s research interests are the AVMs, FinTech, PropTech, Artificial Intelligence (AI), Machine Learning, Game Theory, Valuations, Real Estate Finance (predominantly Asset Management - Financial Gearing, Financial Hedging and Derivatives), Property Markets, Big Data and the Geographic Information System (GIS) with a specific focus on the algorithm-based valuation models. 

He supervises and assesses both the Undergraduate and Postgraduate dissertations (thesis).

For further information, please refer to the 'Research' tab.

External Activities

  • Affiliated and Matriculated Member of the University of Cambridge, Homerton College
  • Member of the Oxford Institute for Sustainable Development (OISD)
  • The University of Cambridge, Homerton College Alumni
  • UCL (University College London), The Bartlett Alumni
  • Qualified Teacher Status (QTS) awarded by The Department for Education of Her Majesty's Government
  • Fellow of The Higher Education Academy (FHEA)
  • Fellow of The Royal Statistical Society
  • Fellow of The Royal Geographical Society (with the Institute of British Geographers)
  • Fellow of The Royal Society  for the Encouragement of Arts, Manufactures and Commerce

Teaching

Onur leads and lectures on a number of Undergraduate and Postgraduate modules. 

Undergraduate Teaching:

He is the Module Leader for the following core modules: 

  • a. BSc., Year I, Introduction to Property Investments and Valuations (Core, Double Module, 40 Credits)   
  • b. BSc., Year II, Residential Survey and Development (Core, 20 Credits) 
  • c. BSc., Year III, Property Management [Valuation for Enfranchisement] (Core, Double Module, 40 Credits)
  • d. BSc., Year III, Sustainability and Environmental Policy (Core, 20 Credits)

He is the Module Academic Member for the following modules:  

  • a. BSc., Year I, Introduction to Planning and Sustainability (Core, 20 Credits)
  • b. BSc., Year I, Introduction to Building Technology (Core, 20 Credits)
  • c. BSc., Year II, Commercial Practice [Valuation & Law] (Core, Double Module, 40 Credits)
  • d. BSc., Year III, Global Practice (Core, 20 Credits)
  • e. BSc., Year III, Tech 6 (Core, Double Module, 40 Credits)
  • f. BSc., Year III, Development Project (thesis) (Core, Double Module, 40 Credits)

Postgraduate Teaching:

  • a. MSc., Space Strategies and Legislation (Core, 20 Credits)
  • b. MSc., Valuation and Law (20 Credits)
  • c. MSc., Property Finance: Lending and Risk Strategies (20 Credits)
  • d. MSc., Finance and Asset Management (Core, 20 Credits)
  • e. MSc., Dissertation (Core, Double Module 40 Credits)

He supervises and assesses both the Undergraduate and Postgraduate dissertations (thesis).

He is a personal tutor (University Academic Tutor) to both Undergraduate and Postgraduate students. He has an active interest in a student's academic progress and university experience and is concerned for a student's general welfare.

Onur is also a professional tutor (Apprentice Tutor for the Undergraduate Degree Apprentice students), liaising, working with professional services and the industry.

Research

Onur’s research interests are the AVMs, FinTech, PropTech, Artificial Intelligence (AI), Machine Learning, Game Theory, Valuations, Real Estate Finance (predominantly Asset Management - Financial Gearing, Financial Hedging and Derivatives), Property Markets, Big Data and the Geographic Information System (GIS) with a specific focus on the algorithm-based valuation models. 

Onur is currently conducting various research projects on traditional and mass valuation theories. 

He is creating algorithms (mathematical models) and uses the 'intelligent' systems known as the Artificial Neural Network (ANN) and fuzzy logic.

He is an expert on all of the five types of Automated Valuation Models (AVMs) - Mathematical Models. These are hedonic models, econometric forecasts, 'intelligent' systems (Artificial Neural Networks - ANN and Fuzzy Logic), house price index (HPI) models and tax assessed value models (TAV).