Grigorios Kyritsakas

Department of Civil and Structural Engineering

Research Associate in Drinking Water Quality Analytics

g.kyritsakas@sheffield.ac.uk

Sir Frederick Mappin Building (Broad Lane Building)

Full contact details

Grigorios Kyritsakas
Department of Civil and Structural Engineering
Sir Frederick Mappin Building (Broad Lane Building)
Mappin Street
Sheffield
S1 3JD

Profile

Grigorios is a Post-Doctoral Research Associate. He has recently completed his PhD funded by STREAM/EPSRC and Scottish Water. His doctoral research titled `Exploring machine learning applications for improving drinking water quality´.

Grigorios' research focuses on data analytics applications for improving drinking water infrastructures and drinking water quality and includes:

Advance data analysis of drinking water quality datasets.
Machine learning applications for improving drinking water quality.
Digital transformation of the water infrastructures
Artificial intelligence applications for providing solutions to water engineering problems.

Research interests

Drinking water quality

Machine learning Data analytics

Operation and management of drinking water distribution systems

Digital water

Digital twins

Publications

Journal articles

Boxall J, Speight V, Kyritsakas G, Kazemi E, Husband S, Bright S, Ledgar S, Montgomery L & Flavell K (2022) The application of artificial intelligence techniques to better manage iron in drinking water distribution systems. Institute of Water Journal(7), 28-34. View this article in WRRO

Conference proceedings papers

Kazemi E, Kyritsakas G, Husband P, Flavell K, Speight V & Boxall J (2022) Predicting Iron Exceedance Risk in Drinking Water Distribution Systems Using Machine Learning. 14th International Conference on Hydroinformatics, 4 July 2022 - 8 July 2022.
Boxall J, Speight V & Kyritsakas G (2022) A data-driven model for the prediction of chlorine losses in water distribution trunk mains. 14th International Conference on Hydroinformatics, 4 July 2022 - 8 July 2022.
Kyritsakas G, Speight V, Thom C & Boxall J (2019) A machine learning application on water quality datasets for understanding the factors of bacteriological failures on service reservoirs. Proceedings of the IWA-Aspire Conference. Hong Kong, 31 October 2019 - 2 November 2019.
Kyritsakas G, Speight V, Thom C & Boxall J (2019) Investigating drinking water behaviour treated by different disinfection with the use of a machine learning technique on water quality datasets. datasets’ Proceedings of the 17th International Computing and Control for the Water Industry Conference, 1 September 2019 - 4 September 2019.

Research group

Water Engineering

Water Distribution Research Group