Imperial College London

Pedro M. Baiz V.

Faculty of EngineeringDepartment of Computing

Honorary Senior Research Fellow
 
 
 
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Contact

 

+44 (0)7916 253 021p.m.baiz

 
 
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Location

 

ACE ExtensionSouth Kensington Campus

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Summary

 

Summary

Dr. Pedro Baiz was the first Royal Society Entrepreneur in Residence at Imperial College London. He is currently based in the Department of Computing, specifically the Adaptive Emergent Systems Engineering Group and works closely with the newly formed Sustainable Tech Lab at Imperial-X.

His main research interests are in the broad field of Data Technologies (e.g. Machine Learning, Internet of Things, Distributed Ledgers) to support the 17 Sustainable Development Goals (SDGs). His recent research focuses in the growing field of Sustainable Finance in order to help linking "Real Economy" (non-financial) systems with the Financial system. This field is also known as "Sustainable FinTech".  

Non-financial systems include all the potential areas of application for Cyber Physical Systems (Internet of Things) in combination with Data Science techniques, such as: 

  • Energy (e.g. Smart Grid, Smart Energy Systems)
  • Transport (e.g. Electric Vehicles)
  • Materials and Buildings (e.g. Smart Buildings)
  • Agriculture (e.g. Smart Farming)
  • Others

The financial aspects of the research evolve around ESG (Environmental, Social, and Governance) characteristics of investments. His current work is based on international initiatives such as the Task Force on Climate-related Financial Disclosures (TCFD recommendations). Pedro is an advisor to multiple organisation and one of the Sustainable Finance experts at the British Standards Institution (BSI). He represents the UK at ISO TC322 (Sustainable Finance) Chairman Advisory Group and also holds the position of Convener at TC322 TAG 1 (FinTech Technical Advisory Group). 

Publications

Journals

Toolabi M, Fallah AS, Louca L, 2018, Enhanced mixed interpolation XFEM formulations for discontinuousTimoshenko beam and Mindlin-Reissner plate, International Journal for Numerical Methods in Engineering, Vol:115, ISSN:0029-5981, Pages:714-737

Tagarielli V, Matos MAS, Pinho S, et al., 2018, Predictions of the electro-mechanical response of conductive CNT-polymer composites, Journal of the Mechanics and Physics of Solids, Vol:114, ISSN:0022-5096, Pages:84-96

Houston C, Gooberman-Hill S, Mathie R, et al., 2017, Case study for the return on investment of Internet of Things using agent-based modelling and data science, Systems, Vol:5, ISSN:2079-8954

Pathan MV, Tagarielli VL, Patsias S, et al., 2016, A new algorithm to generate representative volume elements of composites with cylindrical or spherical fillers, Composites Part B - Engineering, Vol:110, ISSN:1359-8368, Pages:267-278

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