Dr Parag Wate
FHEA, PhD, MTech, BEng
School of Architecture and Landscape
Lecturer in Architectural Science
CIV61019 (Building Performance Modelling and Simulation)
ARC6840 (Renewable Energy)
Module leader
Research Ethics Co-leader
+44 114 222 0302
Full contact details
School of Architecture and Landscape
- Profile
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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 uncertainty 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! Recently, I won an EPSRC Ring-fenced PhD scholarship under me to support the uncertainty scaling up research!
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
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Fellow of Higher Education Academy (FHEA)
PhD Sustainable Energy Technology
MTech Remote Sensing and GIS (Sp. in Geoinformatics, Gold medallist)
BEng Electronics Eng.
- Research interests
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- Physics-informed AI and ML driven Building energy and environmental performance simulation
- Uncertainty quantification and sensitivity analysis of building and urban performance predictions
- Building performance model validation and calibration
- Resilience analysis and assessment of building performance under Climate change
- Parametric programming and computation for Building and Urban Simulation
- Evaluation of Built Environment Digital Twin frameworks
PhD opportunities: If you have interest in any of the topics listed above, please contact me at first instance via e-mail with your CV / portfolio, PhD motivation letter and a research proposal.
Post-doctoral Research Associate opportunities: If you are interested in interdisciplinary topics related to built environment, energy and quantitative methods above, please feel free to write me what excites you most about the interdisciplinarity and what you would like to be known for in the field. We could also discuss in addition various UK and international (including India and Europe-wide) post-doctoral fellowships possibilities.
- Publications
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Journal articles
- Framework for emulation and uncertainty quantification of a stochastic building performance simulator. Applied Energy, 258. View this article in WRRO
- Uncertainty assessment of building performance simulation: An insight into suitability of methods and their applications. Urban Energy Systems for Low-Carbon Cities, 257-287. View this article in WRRO
- Utilities of Virtual 3D City Models Based on CityGML: Various Use Cases. Journal of the Indian Society of Remote Sensing, 46(6), 957-972.
- Implementation of CityGML energy application domain extension (ADE) for integration of urban solar potential indicators using object-oriented modelling approach. Geocarto International, 30(10), 1144-1162.
- An Energy-Related CityGML ADE and Its Application for Heating Demand Calculation. International Journal of 3-D Information Modeling, 4(3), 59-77.
- CityGML at semantic level for urban energy conservation strategies. Annals of GIS, 21(1), 27-41.
Chapters
- Uncertainty assessment of building performance simulation, Urban Energy Systems for Low-Carbon Cities (pp. 257-287). Elsevier
Conference proceedings papers
- Building Science Learning Toolkit: Integration of building physics and performance simulation subject teaching in Architecture curricula. 37TH PLEA CONFERENCE (RE)THINKING RESILIENCE
- Build tight, ventilate right; would still need energy might?. Building Simulation Conference Proceedings, Vol. 18 (pp 2097-2104)
- Urban energy simulation based on 3d city models: a service-oriented approach. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. IV-4/W1 (pp 75-80). Split, Croatia, 7 September 2016 - 9 September 2016. View this article in WRRO
- 3D Data Models for Urban Energy Simulation. Energy Procedia, Vol. 78 (pp 3372-3377)
- Formulation of hierarchical framework for 3D-GIS data acquisition techniques in context of Level-of-Detail (LoD). 2013 IEEE Second International Conference on Image Information Processing (ICIIP-2013), 9 December 2013 - 11 December 2013.
- QUALITATIVE SCREENING METHOD FOR IMPACT ASSESSMENT OF UNCERTAIN BUILDING GEOMETRY ON THERMAL ENERGY DEMAND PREDICTIONS. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XLII-2/W2 (pp 127-134) View this article in WRRO
- Emulation-based Uncertainty and Sensitivity Analysis of a multi-zone dwelling. IBPSA-England Building Simulation and Optimization 2020
- Framework for emulation and uncertainty quantification of a stochastic building performance simulator. Applied Energy, 258. View this article in WRRO
- Research group
- Grants
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EPSRC Ring-fenced PhD Scholarship (The University of Sheffield) Marie Curie Fellowship, joint collaboration between Stuttgart University of Applied Sciences (HfT Stuttgart), Germany and DABE, The University of Nottingham, UK.
- Teaching interests
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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
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CIV61019 (Building Performance Modelling and Simulation), ARC6840 (Renewable Energy)
PhD supervision
Bilal Mahmood (Uncertainty quantification of UK housing stock performance to inform decarbonisation pathways, EPSRC Ring-fenced award, October 2022-26)
Sergio Aguilar (Balancing affordability and environmental sustainability in incremental housing in Peru: an agent-based approach, ESRC WRDTP AQM award, October 2019-22)
- Professional activities and memberships
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Peer reviewer (Building and Environment 2021-, Applied Energy 2020-, Architectural Science Review 2021-, Building Research and Information 2021-)
Member of IBPSA-England Building Simulation and Optimisation Global South 2022 Scientific Committee
Smart Data and Smart Cities Scientific Committee (2020-)
ISPRS Working Group IV/10 on “Advanced geospatial applications for smart cities and regions” (2017-)
Member of OGC CityGML Energy ADE Consortium (2014-)