Dr Parag Wate

BEng, MTech, PhD

School of Architecture

Lecturer in Architectural Science

CIV61019 (Building Performance Modelling and Simulation)

ARC6840 (Renewable Energy) Module leader

Research Ethics Co-leader

Parag Wate
p.wate@sheffield.ac.uk
+44 114 222 0302

Full contact details

Dr Parag Wate
School of Architecture
Profile

I am an engineer and a quantitative researcher specialised in developing and applying machine learning and uncertainty quantification techniques for the research problems in the Built environment sector and beyond where complex computer models are employed to inform decision and policy making.

My PhD research was focused on addressing the performance gap between measured and simulated performance of buildings, by a way of quantifying the model and data uncertainties in energy performance predictions. I developed and applied the Emulation-based Uncertainty and Sensitivity Analysis (EmUSA) framework in order to decompose both - epistemic (due to input data parameters) and aleatory (due to stochastic occupants’ behaviours) - type of uncertainties in the dynamic energy load predictions. The EmUSA has been proven to be a computationally efficient and plausible framework to expedite the process of identifying the factors that affect the building energy performance the most. This aids in addressing the performance gap by focusing model validation and calibration efforts on the most performance-influential factors. The EmUSA framework is poised to be massively scaled up to address building stock and urban scale performance gaps!

I was a Marie Curie early stage researcher in the field of Smart Cities with Sustainable Energy Technologies in the European commission’s FP7-ITN CI-NERGY (CIties and eNERGY) project before joining SSoA.

Qualifications

I had worked in the automotive industry for a year after my graduation in electronics engineering in India. In this role, I designed and implemented automated machine operation and control systems projects. Later, as a part of my post graduation (MTech, Gold medallist) in Geoinformatics at Indian Institute of Remote Sensing, I went on to pursue my design and development interests in a computer modelling and simulation environment, in cities’ energy sector. I developed neighbourhood scale 3D building information modelling workflow for solar irradiation simulation models in order to assess urban facades’ solar PV potential. Later on, I was able to win a Marie Curie ITN fellowship to pursue my PhD in Sustainable Energy Technology in DABE at The University of Nottingham. After my fellowship, I worked as a Scientific assistant at HfT Stuttgart, Germany and developed a new Urban Data Model called SimStadt2 data model for simplified and dynamic building performance simulations at varying levels of building architectural geometry details.  

Research interests
  • Physics-informed AI and ML driven Building energy and environmental performance simulation
  • Uncertainty quantification and sensitivity analysis of performance predictions
  • Building performance model validation and calibration
  • Resilience analysis and assessment of building performance under Climate change 
  • Parametric programming and computation for Building Simulation
  • Evaluation of Built Environment Digital Twin frameworks
Publications

Journal articles

Chapters

Conference proceedings papers

Research group

People, environments and performance research group

Grants

Marie Curie Fellowship, joint collaboration between Stuttgart University of Applied Sciences (HfT Stuttgart), Germany and DABE, The University of Nottingham, UK.   

Teaching interests

I am interested in teaching and supporting students in enhancing their problem solving and transferable skills through their coursework, special study projects, dissertations and research topics. I have interests in adapting a well-researched flipped classroom approach to support student-oriented learning.

Teaching activities

CIV61019 (Building Performance Modelling and Simulation), ARC6840 (Renewable Energy)

I’ve been co-supervising Sergio Aguilar on his PhD research project on ‘Balancing affordability and environmental sustainability in incremental housing in Peru: an agent-based approach’. (started in October 2019)

Professional activities
  •  Peer reviewer, Building and Environment (2021-) 

  •  Peer reviewer, Applied Energy (2020-) 

  • Peer reviewer, Architectural Science Review (2021-) 

  • Peer reviewer, Building Research and Information (2021-)

  • Member of Smart Data and Smart Cities Scientific Committee (2020-)  

  • Member of ISPRS Working Group IV/10 on “Advanced geospatial applications for smart cities and regions” (2017-)

  • Member of OGC CityGML Energy ADE Consortium (2014-)