Maria Xenochristou

Project: Demand forecasting using smart metering data

Supervisors: Professors Zoran Kapelan and Slobodan Djordjevic, Jan Hofman and Dr Chris Hutton
MEng in Civil Engineering from National Technical University of Athens (NTUA), specialising in Hydraulic & Environmental Engineering. Completed a thesis identifying the most important sewer-deterioration factors, as well as assessing the performance and sensitivity of the GompitZ deterioration model.


Work experience
Research assistant on project SEMA at the Berlin Centre of Competence for Water (Kompetenzzentrum Wasser Berlin – KWB), working on sewer deterioration models to assess their accuracy and therefore the potential to use them in order to develop asset management strategies. My main tasks included:
• Developing a sewer-deterioration modelling interface using the R programming language, which enabled an efficient exchange of information between the deterioration model and the model written in R. This allowed not only the automation of the process, and the efficient handling of data, but also a clear view of the results and a great variety of visualising options.
• Creating a new method to benchmark the performance of sewer deterioration models that is based on their respective aim of use, rather than their general accuracy.
• Developing a modelling technique to assess pipe features and environmental factors impacting sewer infrastructure within a German city.
• Presenting the project’s results to all stakeholders and partners, such as Veolia Water.
• Data analyst for the Growth Digital Agency, a Greek start-up. My main duties included:
• Performing analysis and creating data visualisations using the R programming language and Microsoft Excel.
Research Interests:

Smart management of wastewater networks.
• Simulation & modelling of water and wastewater networks to identify system failures (leakages, bursts, and blockages) in near real-time or before they occur, to enable quick or pro-active interventions and minimise the associated costs and consequences.
• Placement of toxic tracers in the wastewater network and automated response planning in order to avoid the consequences to treatment works and the environment, as well as minimise the associated costs.
• Smart management of local VS centralised control of wastewater tanks.
• Automated emergency planning for wastewater networks, in order to avoid e.g. flooding or combined sewer overflows.
• Managing several Google Analytics accounts in order to organise, extract, and analyse the available data.
• Translating inputs from quantitative analyses into specific and actionable business recommendations.
• Designing and implementing reports and real-time dashboards.

WISE 2017 Summer School Presentation: Maria_Xenochristou_Jun17[1]

June 2017 Poster: Maria Xenochristou Jun17