Staff Profile

Luke is a lecturer focusing on the role of digital technologies and data-centric approaches to civil engineering. He trained as a civil engineer, produced a doctoral thesis on the application of supercomputer architectures to detailed flood simulation and forecasting, and worked in industry as a software engineer and technical architect.

He leads the software and standards components as the Deputy Director of the Urban Observatory, is a member of the governance and executive board for the Data and Analytics Facility for National Infrastructure (DAFNI), a NERC Constructing a Digital Environment Fellow, and a co-investigator for a smart building component of the PETRAS National Centre of Excellence for IoT Systems Cybersecurity.

Current projects

• CHARIoT (PI): Toolkit for local authorities as the trusted independent arbiters of smart city data (Research England, Pitch-In)
  
• TRACK (Co-I): COVID-19 risk model for public transport (EP/V032658/1)
• OpenCLIM (Co-I): Open climate impacts modelling framework (NE/T013931/1)
  
• PYRAMID (Co-I): Platform for dYnamic, hyper-resolution, near-real time flood Risk AssessMent Integrating repurposed and novel Data sources (NE/V00378X/1)
• Flood-PREPARED (Co-I): Predicting Rainfall Events by Physical Analytics of REaltime Data (NE/P017134/1)
• DAFNI (Co-I): Data and Analytics Facility for National Infrastructure (EP/R012202/1)
  

Qualifications

• Doctor of Philosophy, Newcastle University: Computational methods for and applications of high-performance computing in flood simulation (2012 - 2018, part-time)
• Master of Engineering (First-class honours), Newcastle University (2008 - 2012)

Memberships

• Professional Member of the Chartered Institute for IT
• Associate Fellow of the Higher Education Academy

Research interests

• Digital twins
• Real-time simulation
• Microsimulation in fluid and traffic systems
• High-performance computing
• Federated data systems and technical architecture
• Smart cities

Funding

• CHARIoT: Toolkit for local authorities as the trusted independent arbiters of smart city data. HEIF Connected Capability Fund (Pitch-In). PI.
• PPIEM: Privacy-preserving indoor environment monitoring, EPSRC and PETRAS IoT. Co-I.
  
• REBUSCOV: Removing operational, infrastructural and entry barriers to urban scale computer vision deployments through delivery of open-source training datasets and system management tools, HEIF Connected Capabilty Fund (Pitch-In). PI.
• TRACK (Co-I): COVID-19 risk model for public transport (EP/V032658/1)
• OpenCLIM (Co-I): Open climate impacts modelling framework (NE/T013931/1)
  
• PYRAMID (Co-I): Platform for dYnamic, hyper-resolution, near-real time flood Risk AssessMent Integrating repurposed and novel Data sources (NE/V00378X/1)
• Flood-PREPARED (Co-I): Predicting Rainfall Events by Physical Analytics of REaltime Data (NE/P017134/1)
• DAFNI (Co-I): Data and Analytics Facility for National Infrastructure (EP/R012202/1)
  

Previous projects

• TENDERLY: Towards END-to End flood forecasting and a tool for ReaL-time catchment susceptibilitY (NE/K008781/1). Researcher.
• SINATRA: Susceptibility of catchments to INTense Rainfall and flooding. NERC Flooding from Intense Rainfall programme (NE/K008781/1). Researcher.
• Numerical and Laboratory Modelling Study of Meteo-Tsunamis and Harbour Resonance. Royal Society International Exchanges 2013 NSFC (IE131297). Researcher.
• Online Social Networks (OSNs) Based System for Flood Prediction and Management (EP/K003593/1). Researcher.
• Small items of research equipment at Newcastle University: Developing the future research base in Healthcare Technologies, Sustainability and Digital Economy (SIREN) (EP/K031678/1).

Undergraduate teaching

• CEG3305 Computational Engineering Analysis. Lead for water components.
• New module on digital technologies in civil engineering, starting Sept 2021.
  

• James P, Das R, Jalosinska A, Smith L. Smart cities and a data-driven response to COVID-19. Dialogues in Human Geography 2020, 10(2), 255-259.
• Mace JC, Morisset C, Smith L. A socio-technical ethical process for managing access to smart building data. In: Living in the Internet of Things (IoT 2019). 2019, London: IET.
• Smith LS, Turner M. Building the Urban Observatory: Engineering the largest set of publicly available real-time environmental urban data in the UK. In: EGU General Assembly 2019. 2019, Vienna, Austria.
• Smith L, Liang Q, James P, Lin W. Assessing the utility of social media as a data source for flood risk management using a real-time modelling framework. Journal of Flood Risk Management 2017, 10(3), 370-380.
• Rashid AA, Liang QH, Dawson RJ, Smith LS. Calibrating a High-Performance Hydrodynamic Model for Broad-Scale Flood Simulation: Application to Thames Estuary, London, UK. In: 12th International Conference on Hydroinformatics (HIC 2016). 2016, Incheon, Korea: Elsevier Science BV.
• Liang QH, Smith L, Xia XL. New prospects for computational hydraulics by leveraging high-performance heterogeneous computing techniques. Journal of Hydrodynamics 2016, 28(6), 977-985.
• Smith LS, Liang Q. A heterogeneous and parallel computing framework for high-resolution hydrodynamic simulations. In: European Geosciences Union General Assembly 2015. 2015, Vienna, Austria: Copernicus GmbH.
• Liang Q, Smith LS. A High-Performance Integrated Hydrodynamic Modelling System for Urban Flood Inundation. Journal of Hydroinformatics 2015, 17(4), 518-533.
• Smith LS, Liang QH, Quinn PF. Towards a hydrodynamic modelling framework appropriate for applications in urban flood assessment and mitigation using heterogeneous computing. Urban Water Journal 2015, 12(1), 67-78.
• Amouzgar R, Liang Q, Smith L. A GPU-accelerated shallow flow model for tsunami simulations. Proceedings of the Institution of Civil Engineers - Engineering and Computational Mechanics 2014, 167(3), 117-125.
• Zhang HB, Wang YL, Liang QH, Smith LS, Kilsby CG. Non-negative depth reconstruction for a two-dimensional partial inertial inundation model. Journal of Hydroinformatics 2014, 16(5), 1158-1177.
• Smith LS, Liang Q, Quinn PF. A flexible hydrodynamic modelling framework for GPUs and CPUs: Application to the Carlisle 2005 floods. In: International Conference on Flood Resilience: Experiences in Asia and Europe. 2013, Exeter, United Kingdom: Centre for Water Systems, University of Exeter.
• Liang Q, Smith LS. A GPU-Accelerated Hydrodynamic Model for Urban Flood Inundation. In: 35th IAHR World Congress. 2013, Chengdu, China: Tsinghua University Press.
• Liang QH, Smith LS. A GPU-Accelerated Hydrodynamic Model for Urban Flood Inundation. In: PROCEEDINGS OF THE 35TH IAHR WORLD CONGRESS, VOLS III AND IV. 2013, DEPT BUILDING SCI, SCH ARCHITECTURE, SECRETARIAT ISHVAC07, BEIJING, 100084, PEOPLES R CHINA: TSINGHUA UNIV.
• Smith LS, Liang Q. Towards a generalised GPU/CPU shallow-flow modelling tool. Computers & Fluids 2013, 88, 334-343.